Exiger’s new tool will help fight against modern slavery in the supply chain

Exiger has announced the launch of its no cost, open access website that allows global citizens, companies, governments, and NGOs to review whether a company or its supply chain is linked to state-sponsored forced labour. forcedlabor.ai empowers all companies, regardless of the size of their compliance budget, to make better decisions about who they do business with and ensure that their supply chain isn’t unknowingly profiting from modern slavery.  

“Modern slavery is a blight on humanity,” said Exiger CEO Brandon Daniels. “An estimated 50 million people are trapped in modern slavery, many of whom are hidden in opaque supply chains. As part of our mission to make the world a safe and transparent place to succeed, Exiger has decided to make the world’s largest dataset on companies connected to state-sponsored forced labour available to everyone. Hundreds of thousands of companies and millions of global supply chains are impacted.”

forcedlabor.ai lets companies, citizens, government agencies, law enforcement, NGOs, and civil society enter the name of supplier or company to immediately see potential forced labour connections in their supply chains. Powered by Exiger’s proprietary AI capabilities, results are evidenced-based and actionable. forcedlabor.ai will cover a growing scope and currently encompasses People’s Republic of China (PRC) state-sponsored forced labour, Uyghur Forced Labor Prevention Act (UFLPA) risks and US Customs and Border Protection (CBP) Withhold Release Orders (WRO) exposure across virtually every industry, including retail, automotive, industrials, consumer goods and electronics, and agricultural products.

“The CCP is responsible for one of the gravest human atrocities in recent history: the genocide of Uyghurs,” said Representative John Moolenaar, Chairman of the House Select Committee on the Strategic Competition Between the US and the Chinese Communist Party, on the launch of forcedlabor.ai. “Corporate actors must be open-eyed and take action to avoid complicity in this abuse and billions of dollars in global supply chains that rely on the CCP’s persecution of the Uyghurs.”

“When our global non-profit, which helps organisations build their resilience to modern slavery and labour exploitation, was looking for a technology to provide supply chain visibility, we reviewed over 400 platforms, and Exiger was heads and shoulders above all of the others,” said Slave-Free Alliance CEO Tim Nelson. “They’ve built the world’s largest forced labour risk database with some 20 billion records, and now they’re making incredibly valuable data available to everyone, creating a level of baseline transparency never before possible.”

The tool was developed with input from human rights and supply chain specialists including Kit Conklin, Exiger SVP of Risk & Compliance, Atlantic Council Nonresident Senior Fellow and former US House Select Committee on China Senior Advisor, as well as Dr. Laura Murphy, one of the world’s foremost experts on forced labour, Professor of Human Rights and Contemporary Slavery at the Helena Kennedy Centre for International Justice at Sheffield Hallam University, Senior Associate in the Human Rights Initiative at CSIS, and former Department of Homeland Security (DHS) Senior Policy Advisor who led the UFLPA Entity List team.

“This is a revolutionary, first-of-its-kind platform that makes regulator-grade forced labor risk intelligence accessible to everyone,” said Conklin. “The scale and universal availability of this data, powered by AI, represents a new era in forced labor transparency.”

Exiger is launching forcedlabor.ai at WEF’s 2026 Annual Meeting at Davos. Exiger CEO and WEF Governor Brandon Daniels will discuss how AI and supply chain intelligence, including forced labour data, are reshaping the industrial, economic and defence landscape alongside private sector CEOs and government officials at the USA House. The first session, Boardroom to Battlefield: Winning the AI Tempo War for Economic and National Security, is at 12:15PM CET on Wednesday, January 21, and the second, From Enforcement to Advantage: The Integrated Trade Strategy Powering America’s Industrial Revival is at 2:15PM CET on Thursday, January 22. Sessions will be livestreamed. For details on all of Exiger appearances and activations at Davos, visit https://www.exiger.com/davos2026.

  • AI in Supply Chain

Caroline Grey, Co-Founder and CRO, Treefera, explores how better visibility is fixing blind spots

The world is getting noisier. Climate volatility, environmental degradation and political instability are increasing both the number and the severity of disturbances that ripple through supply chains. With each disturbance, new complexities arise from new variables, like soil health and rainfall shifts, regulatory changes and geopolitical friction. These variables compound into an opaque risk ecosystem.

The unfortunate reality is that traditional data collection methods, aimed at managing supply chains and reducing risks across the all-important first mile, now can’t keep up in this challenging environment. Manual data collection or static surveys can’t process this rising tide of complexity fast enough to inform decisions, meaning businesses don’t have access to critical information. The result? Without this primary data, businesses are “flying blind,” which means they don’t have control over their supply chain operational performance, thus impacting revenue.

Technology plays a crucial role in quietening the noise, restoring clarity and providing leaders with the insights needed to improve supply chain resilience. We’re already seeing that satellite imagery, drone information and ground truth data can all be elevated using AI agents, allowing businesses to make better decisions.

The first-mile challenge

Today, 60% of business costs and risks occur within the first mile of logistical supply chains, meaning poor management of risk in these sourcing regions can directly impact business success. At the same time, regulatory pressure and requirements are growing, with the impending EUDR and EU omnibus legislation. Businesses need to have access to the right processes and technology solutions to ensure compliance.

For the EUDR, this means that any business that operates within, or sells to, Europe will need to ensure no deforestation occurs within their supply chain. They will also need to backdate evidence from as far back 2020. While timelines for this regulation remain uncertain, acting now to prepare for compliance should be a business priority today.

Given the scale of first-mile risk, visibility is essential to build resilience. This can only be done by leaning into the right mix of technologies, including the smart use of AI to generate insights that allow for greater, better-informed decision-making. AI allows us to abstract complexity – leveraging the massive acceleration in the capabilities of satellites over the past 10 years and turning disparate and disconnected data into actionable insights at global scale and near-instant speed.

AI-nativity needs to be the first step

While the entire supply chain can be opaque, the first mile has historically been hardest to manage, with information about sourcing regions and commodity origins often fragmented, remote and expensive. Businesses need access to insightful data that uncovers what’s really happening on the ground.

Data governs the flow of capital, and the quality of this data can equip enterprises with the ability to scope out and invest in appropriate sourcing options. Satellites, drones and ground truth data help with this, but only to a point – they provide surface level information without the depth of insight necessary for action.

AI-enabled data systems make it possible to track first-mile activity in real time. These tools translate raw, real-world data into scalable insights that decision makers can act on. They can also be tailored to specific business needs – from monitoring particular geographies to aligning with the compliance frameworks that matter most.

How does this work in practice? Take a large brand sourcing cocoa in Madagascar, for example, which needs to assess the risks posed by deforestation in order to meet EUDR standards. By utilising AI and satellite technology, they can map their entire supply chain to assess deforestation, tenure and labour risks, while producing automated DDS (Due Diligence Statement) reports ready to be submitted to the EU.

Agentic AI is the enabler here, synthesising complex and vast real-world datasets into expert-grade insights that are accessible at speed and scale. AI agents build on traditional AI models through autonomy and comprehensive self-learning mechanisms. Ultimately, this technology supports businesses in understanding the risk landscape within the first mile. And when incorporated into models that include regulatory and compliance frameworks, businesses can manage accountability and maintain their governance commitments.

Building deep insights from historic blind spots

The factors that affect global supply chains show no sign of slowing down – it’s time for businesses to take a different approach to risk identification and management, especially within the first mile. By ensuring access to accurate, scalable data and utilising real-time monitoring, businesses are laying the foundation for unwavering supply chain resilience.

For the C-Suite, the stakes are clear: revenue security and enterprise value now hinge on visibility at the first mile. In a world of climate shocks, political instability and regulatory pressure, legible supply chain data is no longer a technical nice-to-have; it is the foundation for protecting continuity, defending margins and sustaining growth over the long term.

  • Digital Supply Chain

Issue 10 of SupplyChain Strategy is here!

In this issue, we’re shining a spotlight on the rapidly-growing sportswear brand, On. Craig Jones, Chief Supply Chain Officer at On, has a long history of transformational excellence. We sat down with him to discuss the expertise he brought to On, and how the business has evolved. 

On is a young company, founded in 2010, and has grown exponentially ever since. It has gained international attention and renown during the last 16 years, but swift growth can have unforeseen consequences. To make sure vital elements of the supply chain didn’t get overlooked with all the extra work and pressure upon it, Jones made sure to start by getting back to basics.

“After 30 years in the game, I would say I can walk around a warehouse and kind of smell where the problems and bottlenecks are,” Jones says. “A lot of it is just the basics of running a distribution centre with planning. If you think about planning, there are not many companies I know that have accurate forecasting, especially with the volatility of our environment today. So it’s important to be clear on who owns what and what needs to be done by whom. A lot of it is just about discipline without being over-the-top.”

Read the full story here!

And that’s not all…

Alongside the On profile, we have some expert insights about supply chain circularity from Kimberley Duarte, Strategic Programs and Operations at the Circular Supply Chain Network. Caroline Grey, Co-Founder and CRO at Treefera, also lends us her wisdom on the topic of building supply chain resilience through first-mile visibility. Plus, procurement and technology leader, Nedra Dickson, talks us through the value of small business.

Additionally, we’ve got fascinating round-ups from DPW Amsterdam and Exiger’s Executive Forum from the tail-end of 2025, and we’ll also be looking ahead to Manifest 2026 and other upcoming events.

Enjoy!

Read the latest issue of SupplyChain Strategy.

Simon Bowes, CVP Manufacturing Industry Strategy EMEA at Blue Yonder, discusses AI’s role in resilience

For some time, global supply chains have been under considerable pressure. Media coverage continues to reflect the uncertainties faced across industries as diverse as construction, chemicals, semiconductors and food, among many others. News reports point to both positive developments and persistent challenges, with stories about disruption, weak demand and slow recovery appearing alongside more encouraging signals.

On the ground, these issues are causing significant problems. Research reveals that 84% of executives have experienced supply chain disruptions, ranging from route changes and extreme weather to geopolitical unrest. These disruptions complicate planning, impacting everything from production capacity to transportation costs. 

On the other hand, supply chains have also proved themselves to be incredibly resilient, with organisations everywhere adapting to unprecedented levels of disruption to keep the wheels of commerce in motion. Looking ahead, however, how can organisations strike a balance between maintaining operational continuity and adapting quickly to new risks and changing market conditions?

AI-powered digital transformation

Key to long-term success is an ongoing commitment to digital transformation, particularly the deeper integration of smart supply-chain platforms and AI-driven tools that strengthen visibility and support faster, more confident decision-making.

In this context, “smart” supply chain platforms are modern, cloud-based systems designed to connect data, processes and stakeholders across the end-to-end supply chain. They replace fragmented legacy tools and spreadsheets with a unified operating environment, integrating data from internal functions (planning, procurement, manufacturing, logistics, etc) and external partners (customers, suppliers, carriers, retailers). In doing so, they provide a single, consistent source of truth across the supply chain network.

AI can play a central role in generating insights that organisations use to radically improve planning and decision-making. By processing large data sets to detect patterns, anomalies or emerging risks more quickly than manual analysis, machine-learning models can anticipate fluctuations in demand and inventory positions, using that information to inform forward planning.

AI can also recommend actions, such as re-routing shipments or adjusting production plans, to minimise disruption while automation reduces reliance on manual decision-making and speeds up response times. Together, these capabilities help organisations adapt more quickly when conditions change, as they inevitably will.

Effective integration

Despite strong potential, integrating AI into incredibly complex supply chains is not without its challenges. For instance, many networks remain extremely fragmented, with data often trapped in multiple systems that don’t communicate well. This reduces the quality and completeness of information available to AI models, meaning organisations struggle to operationalise tools consistently across relevant functions. According to Blue Yonder’s research, 82% of leaders agree that outdated technology will hinder their supply chain’s potential, and 51% state that implementing new tech is a top strategic priority. 

In the rush to deliver performance improvements, some organisations have implemented AI on a piecemeal basis, deploying point solutions that address only one area (such as warehouse optimisation or forecasting) without supporting broader end-to-end decisioning. The problem with this approach is that it can easily create new barriers by reinforcing data and process silos, making it harder to share insight across functions and limiting the ability to coordinate responses when conditions change.

So, what do AI-powered supply chain processes look like in practice? Imagine a manufacturer sourcing key components from multiple suppliers across different regions. Without prior warning, a disruption, such as a severe weather event that closes a port or a supplier’s production delay, occurs. Using traditional processes, teams would need to manually piece together information from procurement, logistics and production systems to understand the scale of the problem, a task that can take hours or even days.

Armed with the appropriate data platform and AI tools, because data from procurement, production, logistics and inventory is unified, the organisation receives an early alert. AI models quickly analyse the likely impact of the problem, such as which orders will be affected, expected delays, and how production capacity will be influenced, among other factors.

The platform then evaluates scenarios around options such as alternative suppliers, rerouting via different ports, adjusting production schedules or reallocating inventory across distribution centres. It then recommends the most effective option based on lead time, cost and service commitments.

Planners can review and approve the recommended response, supported by a clear rationale. After this point, execution steps are automatically triggered across procurement, transportation partners and warehouse operations. As conditions evolve, AI continues to monitor performance and adjust recommendations, ensuring customer commitments are met and cost impacts are minimised.

In many ways, the argument in favour of using AI to improve supply chain performance and resilience has already been won. Research has shown that 80% of industry leaders say AI is already changing how they operate. Delivering on the technology’s true potential requires a shift from experimentation to scaled deployment. That means unifying data, connecting processes and equipping teams to act on AI-driven insight with confidence.

  • AI in Supply Chain

The CRO of Kallikor discusses how supply chain professionals can become more proactive and less reactive

Poor alignment of strategy to execution plans across supply chain operations coupled to a continuous mix of internal and external disruptions are leading to a culture of constant firefighting. Last-minute fixes and costly reactive changes to address even small bottlenecks are eroding margins and confidence at the top. And, for CEOs and CFOs, this short-term mindset in the operation leaves them incapable of making confident growth bets for the future.

Instead, decision-makers need a way to shift from firefighting to foresight, with access to a safe virtual environment that enables testing of long-term strategies, quantifying the impact of even the smallest changes and aligning decisions across finance, commercial, logistics and supply chain operations.

Starting anywhere

No more reactive, day-to-day problem solving to deal with demand changes or external factors. Instead, leaders can use composable simulation to target the real pressure points that constrain growth – whether that’s in-store operations, warehouse flows, transport strategy or outdated inventory policies. By tackling the bottlenecks that matter most, businesses gain the agility to act decisively.


With a joined-up model spanning areas of operation, changes in one domain which impact adjacent processes can be modelled together – avoiding greedy optimisation which favours one function, landing additional costs elsewhere in the business. Those might include warehouse design, store operations or network flow, with the power to move seamlessly between but balance the needs of different areas as needed. That flexibility gives executives the foresight to direct resources where they’ll unlock future growth, not just satisfy immediate local operational challenges.

From composability to adaptability

Composability is crucial for adaptability. With composable simulation, businesses can quickly adapt to changing requirements or conditions across the operation. New use cases or models can be added if needed, supporting targeted improvements on-the-fly, but critically balancing each of the elements of the end-to-end flow.

Firefighting mindsets have been exacerbated by rigid rules and policies, or guardrails, in supply chains, especially when they no longer fit today’s market dynamics. Composable simulation enables businesses to simulate different scenarios that challenge those guardrails.

The short and long-term impact of changing or removing certain policies or rules can be fully tested in a risk-free environment, enabling true foresight. It’s even possible to identify new effective ways of operating across the supply chain which may have been previously overlooked due to the established, siloed structures in place.

Accessibility that drives alignment

But even with the flexibility, impact and foresight offered by composable simulation, it only creates value if the insights are accessible to decision-makers at every level, so that impact is lessened if the platform is too complex for staff to leverage and C-suite leaders can’t gain the relevant insight.

Many old-school tools demanded near perfect data and data scientist level tech talent to deliver value. That’s no longer the case. Innovations in AI and no-code models mean composable simulation no longer requires spotless data or deep technical expertise. A happy by-product is that composable simulation avoids the downsides of data aggregation necessary to feed the traditional tools.

Even if substantial gaps are present in the available data, AI can synthesise the missing elements based on the available information. Through intelligent preparation of extensive simulation experiments it is possible to describe and fully explore complex scenarios which extend beyond the bounds of what could be achieved with ‘real’ data alone.  

The result is a safe environment for testing operational decisions and modelling real-world impact, accessible to all, from technical specialists to the C-Suite.

Targeted change, strategic impact

In short, composability allows businesses to leave firefighting in the past, challenge the rigid guardrails that have held them back and achieve much-needed foresight. By building modular simulation digital twins, leaders can test new strategies, expose outdated rules and see the ripple effects of every decision before committing capital. Instead of reactively addressing bottlenecks, the supply chain becomes the cockpit for growth foresight, where the C-suite can align investors, operations and strategy – and act boldly with confidence.

  • AI in Supply Chain

As pressure mounts to deliver faster and more reliably, the ability to adjust in motion becomes a vital competitive edge

Supply chain disruption is no longer an anomaly; it’s a constant. From geopolitical tension and rising fuel costs to climate-related events and shifting regulations, logistics leaders are navigating an environment defined by volatility.

But that’s only part of the story. Rising accident rates and escalating costs are adding further strain: large truck crashes have increased since 2024, despite widespread safety efforts. At the same time, fleets are grappling with tightening regulatory and compliance pressures, from evolving emissions rules, such as the EPA’s proposed heavy-duty vehicle standards, to more stringent Compliance, Safety, Accountability (CSA) scoring.

As a result, the concept of supply chain “resilience” has evolved from a buzzword into an operational necessity. At the centre of that resilience is real-time visibility, not only across shipments and inventories, but across fleet safety and compliance too.

While many organisations have made significant strides in digitising warehouse operations, improving demand forecasting, and modernising port logistics, one area remains critically under-addressed: road transport. Despite being one of the chain’s most vulnerable and variable links, the road remains a blind spot for many. Recent research reflects this gap – more than 70% of respondents admitted their fleets lack real-time visibility into road conditions.

Supply chain leaders are grappling with an acute driver shortage that threatens the backbone of road transport. Across the EU, Norway, and the UK, there is already a shortfall of over 233,000 truck drivers, a gap projected to swell to more than 745,000 by 2028 as older drivers retire without enough new entrants to replace them. In the UK alone, an alarming 55% of HGV drivers are aged between 50 and 65, with an average age of 51, signalling that a significant portion of the workforce may leave within the next decade.

Against this backdrop, supply chain leaders must embrace real-time road intelligence, powered by artificial intelligence and edge-computing vision systems, as a key strategic tool for visibility, adaptability, and risk management.

Road transport: A dynamic environment with limited visibility

These mounting challenges highlight the urgent need for stronger oversight and proactive risk management across fleets. Unlike static warehouse environments or planned shipping schedules, roads are dynamic and unpredictable. They’re impacted by human behaviour, weather conditions, infrastructure quality, and spontaneous events, any of which can delay deliveries or damage goods. Yet visibility into these disruptions often remains alarmingly limited.

A recent survey revealed that while 84% of safety leaders identified fleet safety as a high priority, 60% admitted they have no formal fleet safety technology in place, frequently relying on nothing more than basic GPS tracking. Moreover, 46% of surveyed professionals are still unclear about the full financial impact of accidents on their businesses, underscoring how visibility gaps continue to be a serious liability. Without accurate, real-time data on driver behaviour, vehicle conditions, and external risks, companies are left reactive rather than proactive, a critical threat to supply chain resilience.

Edge-computing vision systems powered by artificial intelligence (AI) address this challenge by collecting and processing road-level data directly at the source in real-time. These systems provide immediate insight into traffic conditions, driver behaviour, and environmental hazards, turning the road from a risk point into a source of actionable intelligence. They also play a crucial role in optimising operational costs, a large fleet of delivery trucks means high expenses, and keeping these under control is a constant challenge, especially for companies managing hundreds of vehicles making multiple deliveries each day.

For instance, when weather patterns shift quickly or congestion builds on a critical route, teams can reallocate resources, reroute vehicles, or update delivery schedules in real-time. This shift from reactive management to proactive planning is one of the key advantages of road intelligence.

Systems capable of analysing 100% of drive time add another layer of value, capturing full journey context to support decision-making, coaching and incident resolution.

AI and risk mitigation

AI is a core enabler of dynamic risk mitigation. Rather than relying on historical averages or static route plans, modern AI-driven systems identify emerging patterns and adapt recommendations based on current conditions.

This includes spotting subtle indicators of risk, such as shifts in driver behaviour that suggest fatigue, or clusters of hard braking in a specific area that might point to a developing road hazard. As foundational models evolve, AI is even being trained to predict the likely movements of drivers and vehicles, enabling earlier intervention to prevent incidents before they occur. With this level of intelligence, logistics teams can anticipate disruptions before they escalate and respond proactively to keep operations on track.

Crucially, advanced driver safety platforms today do far more than just warn of lane departures or potential forward collisions. They continuously analyse driving performance in real time, issuing immediate voice alerts to correct risky actions, turning each potential hazard into a safer outcome on the spot. For example, a driver about to tailgate or showing early signs of drowsiness can receive a prompt to adjust, helping avert accidents before they happen. Many systems also incorporate positive reinforcement, recognising and rewarding safe driving habits to strengthen safety cultures across fleets.

This kind of dynamic responsiveness is essential during peak demand periods, extreme weather events, or disruptions to global trade routes. As pressure mounts to deliver faster and more reliably, the ability to adjust in motion becomes a vital competitive edge.

Building resilience into the last mile

The last mile has become one of the most scrutinised segments of the supply chain, where delays and miscommunication are most visible to customers. It’s also where efficiency and traceability are most challenging to maintain, particularly during external disruptions.

Real-time road intelligence provides the operational agility to protect this final delivery stage. By integrating road-level data into dispatch and routing systems, teams can make micro-adjustments that reduce delays, improve customer communication, and avoid costly rework.

This agility can also help prevent compliance breaches, protect product quality, and reinforce customer trust in temperature-sensitive or high-value logistics. Fleet managers using AI-driven road intelligence platforms have already seen measurable improvements, such as a 50% reduction in road accidents, by combining real-time alerts with proactive coaching sessions.

Closing the gaps: From compliance to ESG

Beyond operational continuity, road intelligence also plays a critical role in helping organisations meet growing regulatory and ESG requirements. Visibility into emissions, idling time, route efficiency, and driver behaviour helps teams identify areas for improvement and demonstrate measurable progress against sustainability goals.

It also supports ethical business practices, ensuring safety is prioritised, risky behaviours are addressed constructively, and drivers are given the tools to perform at their best. This reinforces a safety-first culture contributing to long-term resilience, driver retention, and public trust.

Real-time road data provides the insight and accountability needed to align transport operations with broader environmental and governance commitments.

Looking forward: A strategic asset, not a tactical add-on

Real-time road intelligence isn’t a tactical bolt-on; it’s becoming foundational to building resilient supply chains. By embedding AI-powered insights into core logistics processes, organisations gain the flexibility to respond faster, the foresight to avoid costly disruptions, and the intelligence to meet evolving expectations.

In a world where supply chains must operate precisely in dynamic environments, the ability to see and respond at the edge is crucial.

The road has long been treated as the most unpredictable link in the supply chain. However, with the right intelligence in place, it can become one of the most strategic. AI, when fuelled by scale, speed and visibility, becomes a force for good, reducing accidents, empowering drivers and creating a safer ecosystem for everyone on the road.

  • Digital Supply Chain

At the most recent Exiger Executive Forum, we had the opportunity to listen to the experts discuss how supply chains can shore up in chaotic times

Most often than not, the control you have over your value chain is an illusion.

That’s the bold statement November’s Exiger Executive Forum picked to examine and dissect. The event, entitled False Security: The Illusion of Control in Modern Day Value Chains, was chosen carefully to reflect what procurement and supply and value chain leaders are concerned about today.

On the 18th of November, we joined Exiger and its distinguished guests at the beautiful Great Scotland Yard Hotel in London to dig into this topic and hear directly from the best of the best in an expert panel. The guest list reached from defence leadership, supply chain experts, world-leading analysts and senior politicians. 

The aim? To challenge that illusion of control, and frame the conversation as a tough love wake-up call. Without open dialogue like this, risks can quietly accumulate in the background, leading to systemic failures.

That’s why the Exiger Executive Forum is so important. By giving the most pressing matters – especially the uncomfortable ones – a platform, issues are demystified and disempowered and real solutions to be put into place – both with deep values and credible pragmatism. This allows leaders in procurement and supply chain to  resolve modern day challenges with confidence, regain lost control and determine their future and not merely react.

Tim Fowler, Client Engagement  Director at Exiger, acted as moderator for the evening’s discussions. He opened the discussion with a sobering reality: that organisations all over the world are facing systemic risks. “Global supply chains are more data-driven, more regulated, more digitised than ever,” he explained. “But, paradoxically, they’ve never been more fragile with the convergence of geopolitical fragmentation, resource scarcity, technology threats, and regulatory volatility.”

The risk caused, Fowler said, is one that “hides in plain sight”. Many enterprises operate under the assumption that they have full visibility of their suppliers, and that as a result, they’re in control. However, dig a little deeper and there are many unseen dependencies, regional concentrations, and of course, human risk. With a more hopeful lilt, Fowler then reminded attendees that the goal of the Executive Forum is to explore what real control and resilience means in a chaotic and ever-changing world, with the help of the expert panel:

• Koray Köse, CEO & Chief Analyst, Köse Advisory; Senior Fellow, GlobSEC GeoTech Centre; and Board Member, Slave-Free Alliance

• Scott LaFoy, Vice President, Nuclear and Technology Security Programs, Exiger
• Sven Markert, Head of Supply Chain & Logistics, Siemens Smart Infrastructure
• Angela Qu, Advisor, Strategist, and former Chief Supply Chain Officer
• Faysal Rahman, Director, Corporate Coverage – Global Defence Coordinator, Deutsche Bank

The illusion of control

In the first segment of the evening’s strategic expert exchange, Fowler dug into the concept of this illusion of control with the panel. For Köse, the illusion of control is one of the greatest blind spots in modern business. But why? “It’s all based on our systemic understanding or how we actually created value in the past,” he explained. “Not 50 years ago, but even just 10 or 15 years ago, the world looked very different from what we are facing today. Changing the rules of the game is something many companies still do not examine seriously. It requires a deep review of how their value chains are designed, the governance and compliance structures that guide them, and the intelligence embedded into their processes. Ultimately, it is about building resolve and the capability and capacity to not only survive the challenges of today, but to shape and compete in the markets of tomorrow.”

Following this, Qu was asked whether she has also witnessed a false sense of security within governance models in organisations she’s worked with. She pointed out that many companies now have risk mapping, risk monitoring, and risk mitigation as a top agenda since COVID-19, but shortages and disruptions continue. What’s key, for Qu, is “awareness, visibility, and overview. I think we’ve made big steps in the last 2-3 years,” she explained. “There are a lot of conflicts in the classical KPIs, which are still siloed even after the COVID crisis. That’s why you need good visibility of the whole value chain setup – not only tier one.”

For Markert, maintaining agility when managing various political, technological, and economic challenges has been a major undertaking. “The truth is, I don’t know if we really maintain the agility or just manage the chaos,” he admitted. “We’re focusing on adaptability over perfection, so we accept that full control is impossible. Then, we’re coming back to basics. This starts with processes, then technology. Lastly, people are the most important and most valuable assets you have. You have to build up cross-functional teams. We don’t want to predict the future; we want to be prepared for the future.”

From a financial standpoint, Rahman stated he believes it’s important to take a step back and contextualise the challenge we’re living in. The last few years have seen a pandemic, wars, and geopolitical tensions the likes of which have never been seen, impacting supply chains. With this in mind, Rahman believes that there “couldn’t be more of an emphasis” on supply chain resilience. “How do you make sure your operational resilience is robust so you can withstand black swan events that are becoming more and more common?” he asks. “Diversification of risk is really important.”

Sometimes, failure is simply not an option. For LaFoy, who works with national security-grade supply chains, having all of the information in front of you is great, but it means nothing if you don’t use it to take action. “Often people think they can see everything, and that’s only step one of the problem – it doesn’t fully address it,” he said. “You have to be willing to take action within the organisation, to mitigate the problem, fix it, and try to rebuild. People like to say that they’re going to fix their supply chain, but the supply chain is likely supporting a programme that has existed for so long it’s entrenched within the organisation. So it’s almost always too late.”

Vulnerabilities and systemic risk

Fowler: “Where do you see the biggest unseen vulnerabilities accumulating today?”

Köse: “It’s in the KPIs. Companies are measuring themselves against metrics that no longer drive sustainable or resilient value creation in today’s world. They still prioritise short term shareholder returns that evaporate with every risk event. KPIs shift from quarter to quarter, yet value chains take decades to build and mature, just as supplier partnerships and political relationships take decades to cultivate. Both can erode rapidly when interdependent opportunistic and negative actions and disruptions occur.”

Fowler: “How do you encourage best practice and good behaviour with your clients?”

Rahman: “The number one ingredient is confidence. Having transparency across the value chain, the supply chain, the governance procedures, is super important too. It can take 50 years to build trust and one second to lose it, so it’s important to take a very risk-averse approach while being very commercial and pragmatic.”

Fowler: “What have you seen work in terms of breaking down siloes to drive agility?”

Qu: “I usually go with strategy, organisation, technology. Technology encompasses risk mitigation, as well as ESG and compliance. We need dedicated projects, working with suppliers and engineers to reduce waste and create internal excellence. Personal resilience is also very important.”

Fowler: “How do you balance all the elements of regional concentration and supplier dependency?”

Markert: “Efficiency is still key if you want to stay competitive. We cannot optimise purely on costs anymore – that’s gone. We have to take into consideration, as Angela said, the transparency insights beyond tier one. For me, it’s all about continuity and compliance.”

Fowler: “What lessons can the private sector draw from defense-grade risk management?”

LaFoy: “The defence-grade supply chain has this draconian adherence to certain processes, and that inflexibility doesn’t always translate in a positive way. But in this case, it’s necessary to examine what key things you’re prioritising as a company. 

Technology, intelligence, and the myth of visibility 

It’s clear, in spite of the warnings about vulnerabilities and control, that the overall feelings for supply chain professionals are hope and determination. Fowler introduced the next segment of the conversation by mentioning that investors and PE companies are now focusing on supply chain risk and resilience as key measures. This bodes well for those in supply chain when they inevitably come to justifying proposed improvements. The fact that supply chain risk ties directly into financial risk proves once again that supply chain is a business-wide concern, if there was any remaining doubt.

For Rahman, from a financial perspective, there are a couple of areas clients are focusing on when it comes to their investments. “One is financial risk,” he told Fowler. “What we mean by that is leverage – how much debt and cash they’ve got on the balance sheet. The other is business risk, which is quite broad. It’s about how much the product is needed in the market, whether it’s a diversified product, and so on.”

When it comes to questions of compliance and ESG in supply chain, balancing those areas of focus with what investors want can be a challenge. Those investors may have a clear idea of their areas of interest when thinking about risk and resilience, and Qu’s solution for making sure those vital areas don’t get overlooked is to always see things from the customers’ perspective.

“That customer, if you want them to choose your product versus a product from competitors, they want to know you’re compliant to all regulations,” she explained. “That results in collaboration among different departments to focus on a common goal and how we achieve it. Also, you need an overview of potential risks and have solutions in place for those focus areas, supported by technology. Things can go wrong, but if that happens when you’re prepared, it’s not the end of the world. There are still activities where humans can take over.”

The conversation again turned to leadership, and how that affects organisations in a way that incentivises them to focus on protection and resilience, while not stifling innovation and agility. The key, for Köse, lies in communication and constant messaging, so vital areas don’t get forgotten. “The important factor is drawing the journey very clearly to everyone who is a stakeholder in this process, and make sure that every part of their contribution will become part of the overall value creation process. When we talk about resilience, you always need to think about the next step. We’re not necessarily predicting anything, but we’re preparing for everything.”

The conversation shifted to summarising comments, where the panellists highlighted resilience across all functions, with a heavy emphasis on supply chain, utilising AI to help navigate decisions, and simply showing up as being some of the most important aspects to getting the modern supply chain right. “We need to be able to understand, from A to Z, geopolitical interdependencies, financial impact, innovation impact, industrial history, and the most valuable assets – your people and your culture,” Köse concluded. “Showing up in that context, and driving that as leaders, is ultimately really critical.”

During the course of the evening, the expert panelists exposed the glaring issues and shattered illusions across the modern value chain, while leaving attendees hopeful that they can achieve operational resilience through a proactive commitment to preparedness. Thank you to Exiger for inviting us to join in this vital conversation; we look forward to the next one.

  • Events
  • Together in Events

These milestones reflect not just commercial progress, but market validation of Exiger’s platform

The US Army has licensed Exiger’s AI software in order to accelerate its defence acquisition, reduce lead times, and enhance operational readiness. It’s part of a multi-million collar contract that’s been awarded to Exiger to provide end-to-end supply chain risk illumiation.

“This is a revolutionary capability that will transform the way the U.S. Army approaches sustainment,” said Exiger CEO Brandon Daniels. “Our software will help identify at-risk NIINs that may be subject to undue constraints from a variety of factors. It will unlock the organic and additive capabilities that the government has invested in. And it will monitor for severe risk hiding in the supply chain, identifying where natural and manmade disasters, supplier operational and reputational risk, and foreign adversary sourcing could create disruptions in the weapons systems our warfighters depend on. Together, these capabilities deliver a more predictive industrial base, capable of responding to evolving mission needs at speed.”

Exiger has also joined forces with Palantir as part of this project, combining Palantir’s operating system with its own mission-built supply chain AI.

“This partnership combines Palantir’s and Exiger’s world-class technologies to integrate production decisions with battlefield demands, ensuring the US Army can deliver faster and more reliably to those on the front lines,” said Mike Gallagher, Head of Defense, Palantir.

“AI and automation across the supply chain enable deeper visibility, faster risk surfacing, active and proactive mitigation, and accelerated supply movement, giving commanders and portfolio acquisition executives a level of foresight and speed never before possible,” Daniels added.

  • AI in Supply Chain

Exiger has been awarded a huge contract to help modernise the detection of transshipment for the US government

Exiger, the market-leading supply chain AI company, announced today that it has been awarded an exclusive, multi-million dollar contract by US Customs and Border Protection (CBP) to modernise the detection of illicit transshipment across global supply chains. Designed to evade tariffs, trade restrictions and sanctions, illicit transshipment is the practice of manipulating supply chains to disguise a product’s true country of origin. Exiger’s Trade AI will be adopted and deployed across CBP, serving as an additional tool for the US government’s transshipment detection capability.

Transshipment identification and enforcement are critical priorities for the Department of Homeland Security (DHS) and CBP. Convergent Solutions, Inc., DBA Exiger Government Solutions, will equip CBP enforcement offices and personnel across the US with access to Exiger’s AI platform and data to identify illicit transshipment at-scale and in real-time.

“Billions of dollars worth of global trade move through illegal transshipment channels that seek to bypass US restrictions,” said Exiger CEO Brandon Daniels. “A core CBP mission is to enforce US trade and forced labor laws, thereby helping ensure that American manufacturers and workers are competing on a level playing field. Exiger is proud to support this mission, bringing to bear the world’s largest proprietary supply chain database and the market’s most sophisticated AI.”

Exiger’s AI will be an additional resource available to CBP personnel to:

  • Detect illegal transshipment across global supply chains
  • Monitor and enforce tariff and trade regulations
  • Leverage Exiger’s proprietary AI models and trade intelligence data to enrich data in CBP systems and enhance decision making
  • Deploy AI-enabled validations of tariff classification, value and country of origin
  • Create automated bills of material for products and sub-components
  • Map the flow of raw materials and sub-components through global supply chains
  • Risk-score shipments in-real time
  • Collect tariff revenues earlier
  • Trace global supply chains to enhance import visibility and risk segmentation

Exiger’s proven AI solutions have been deployed across 60+ US Government agencies, including the Department of War, Department of State, Department of Energy, DHS, the intelligence community, and armed forces.

Exiger’s technology continues to earn top recognition. In April, Exiger was named an awardee on the Government Services Administration’s Supply Chain Risk Illumination Professional Tools and Services (SCRIPTS) Blanket Purchase Agreement, and was the highest-ranked unrestricted vendor awardee of the 10-year, $919 million contract. This year, Exiger was named a Leader in the 2025 Gartner® Magic Quadrant™ for Supplier Risk Management Solutions, a Best-of-Breed Solution and three-time Value Leader in Spend Matters’ SolutionMap, and a Leader in Omdia’s Market Radar: Firmware and Software Supply Chain Security. Exiger also won a 2025 STEVIE® Award for AI Company of the Year.

  • AI in Supply Chain

The proof, as they say, is in the pudding – and the evidence of TealBook’s increasingly-successful evolution lies in its client relationships

We talked endlessly about data and AI at DPW New York 2025. A universal truth is that the successful implementation of AI requires clean data; it doesn’t have to be perfect, but businesses certainly need to have a decent handle on their data before adopting AI tools successfully. 

To help make this a reality, North American data and software company TealBook has recently announced a legal entity-based data model. It’s designed to resolve supplier records to the correct legal entities, map parent-child relationships, and enrich profiles with verifiable attributes, enabling accurate supplier data to flow seamlessly into procurement systems and AI applications. “This is part of a 12-year journey for TealBook,” says Stephany Lapierre, the company’s Founder and CEO. “Our vision has always been to build a way to enable procurement organisations to have high quality data with a lot of integrity, in order to give them the trust they need to put data directly into their systems. 

“Twelve years ago, we underestimated the complexity of getting large enterprises to trust a third-party data solution. As part of our journey, we started using AI early on to find information where it exists on supplier websites and databases, and start creating digital profiles in a structured way for procurement to access it, match it to their vendor master, and use it.”

TealBook’s evolution

But, again, at the beginning, TealBook couldn’t be sure whether the data was high enough quality. In 2017, the company was primarily known as a supplier discovery application, positioned as a pre-sourcing engine to help procurement teams identify alternative suppliers. At the time, TealBook’s data and models enabled it to determine which companies were similar to others, allowing users to search and find comparable suppliers to expand their sourcing options.

“But that was just a way for us to deliver something that was underserved in the market,” Lapierre continues. “Then our customers started asking for certificates, which are hard to collect and match. They needed cleaner data. They felt they were under-reporting. So in 2018, we started to see whether our technology could refine the data more, and focused on certificates and supplier diversity. We collected great use cases along this journey, and the vision never wavered.

“Just last year we released a new technology – completely different, really sophisticated – allowing us to pull from a lot more data sources, and we have provenance so our customers can actually verify where the data’s coming from. We can match it to vendor masters. And now, we also have this new model that includes 230 million verifiable global legal entities from across 145 countries’ registries. We marry this with global parent and child hierarchy, which is really hard for our customers to match themselves.”

Partnership with Kraft Heinz

Now, after 12 years of that vision, TealBook is deeply proud of what it’s achieved. Part of its ability to get to this point is due to early adoption from key customers. Kraft Heinz is a business which Lapierre describes as a “co-innovation partner”, and has been invaluable in helping TealBook achieve its recent goals.

From the perspective of Stefanie Fink, Head of Global Data and Digital Procurement at Kraft Heinz, the partnership has been an immediately valuable one. “It really started with having a visionary, like-minded relationship,” she says. “That’s an important piece of it, because my vision for procurement is that we are partners in our enterprise. 

“In order for us to do our jobs, we have to bring in the right data for use. This is where Stephany’s partnership and vision really resonated. We were really looking for diversity and we could make things easier for our partners, while making sure we had the right people in our ecosystem. We also had to lift up the hood and see what was underneath everything we’ve got. Stephany brought our vision to life. TealBook has evolved too, as we’ve seen; it’s more about orchestration and software-as-a-service. It has been a partnership of need and we cannot continue to do other things without this kind of partnership around data.”

When initially dabbling with this relationship, Fink was clear that Kraft Heinz had no desire to be taking care of more stuff. What she wanted from TealBook was a strong focus on good quality data. After last year’s product release from TealBook, Kraft Heinz already saw its data enriched by 25%. The recently-announced new data model gives the business and TealBook’s other customers the right structure tied to a legal entity, which is a highly credible anchor. “We’re able to do entity resolution – all automated – remove all the duplicates, and then you start with a clean, digitised vendor master,” says Lapierre. “That’s what brings further enrichment.”

The challenge of assessing data quality

Assessing its data before involving TealBook was important for Kraft Heinz, but challenging for such a large organisation. “We had to fail first and fail fast,” says Fink. “We tried some AI around fixing things early, but that didn’t work for us. It was a real eye-opener, realising where this next evolution could take us regarding focusing on AI and agents for the right things, not the meaningless things. Before, we were asking agents to tell us if things were duplicates, when we should have been asking: what do these suppliers offer? Where is the innovation? Where is the value?”

What surprised Fink most when looking under Kraft Heinz’s hood was the lack of attention that was being paid to what the business was doing. “It was amazing that nobody had questioned it sooner,” she says. “So I said, let’s take this as a crawl, walk, run approach, and I have a wonderful CPO who really understands where we want procurement to go as a function. She was excited about us just getting it done and getting people involved, and that’s what it takes: real pride in ownership of the data.”

Getting engrossed in GenAI

True partnership and an all-in approach has enabled Kraft Heinz to work successfully with AI – something some businesses are struggling with as the conversation around artificial intelligence grows louder. For Lapierre, as the CEO of a tech company, adopting AI successfully has meant trying and failing and being fully entrenched in AI as it has evolved.

“We’ve been using AI in our technology since 2016,” she states. “We’re an early adopter. We’d be talking about scraping data, and data in the cloud, and AI models, and our customers’ pupils would widen in surprise. We’ve come a long way and the market has come a long way. 

“The technology we deliver today wouldn’t be possible without the AI tools now at our disposal. We used to build models; we don’t do that anymore. We spend a lot of time investing in engineers to build and test models, and that’s made us so much more efficient. I use GenAI every day for so many things now, and I’m encouraging my team to be so involved in AI. That’s how you build expertise, and you need really strong expertise to use GenAI well. 

“Getting good with AI is about taking risks and having a leadership team that pushes for new things, and suddenly the successful use of AI becomes a habit.”

  • AI in Procurement

The march towards agentic AI can be a daunting thing, but it’s important to get over that fear in order to make strides

A common question when discussing AI is ‘where do humans fit in?’. The fear of technological advancements stealing our jobs is an old one, but the conclusion is always the same and always true: there will never be a time when human judgement and teamwork isn’t required.

At DPW New York 2025, we sat down with Rinus Strydom, Chief Revenue Officer at Pactum AI, and Steven Velte, Executive Director Procurement Transformation at Honeywell – a customer of Pactum AI – to discuss AI’s evolution and the human connection. As AI develops, for Strydom, Pactum’s focus is on agentic, rather than generative. There’s a key difference there, especially for initial adoption at large enterprises. 

“A lot of enterprises feel a little bit afraid, because generative AI can go a little off the rails,” he explains. “But when you put agents to work, they’re always within the rails that are defined by the customers. Once we get over that hurdle and can make clients see that they can take their procurement operating model and have it just run at scale with agents, rather than being afraid that their image will get tarnished, AI can be put to work much faster.”

Putting AI to work

When it comes to strategies procurement leaders can adopt to make AI work for them, it’s a major discussion point for Strydom and Velte. As a customer, it’s important for Honeywell to feel like its work with Pactum AI is a collaboration; it’s part of what makes its strides into AI work successfully. “This collaboration goes deeper than what we’ve typically had in the past,” says Velte. 

“When we go through organisational changes, we need a true partner, And when that partner gets into the elevator with you, they don’t just push the button with you – they go up to the next floor with you and sit at the table to talk about what’s happening. So a barrier to AI adoption is not having that deep collaboration and partnership.” 

“I think another thing leaders can do today is really help with that psychological change management to make it feel like a safe thing,” Strydom adds. Mindset shift is such a vital part of this change, especially when it comes to successful collaboration. “It’s important to embrace agentic AI, to encourage people to become managers of agents and not run away or become fearful.”

Identifying the opportunities

The true benefits of AI are now beginning to present themselves, as people increasingly embrace AI. For Velte, businesses have to get going with their AI plans in order to realise where the real opportunities lie. “I can make a business case with tons of ROI, potential productivity gains, revenue uplift, bottom line, profit line – all of that. But the real benefits that come from AI are those hidden benefits we don’t realise. When you start looking at it, there’s a common theme of saving time, and time becomes the real benefit. Unlocking better use of time gives you more potential to work on other creative aspects of the business.”

For Strydom, the true value lies in achieving things that used to be extremely difficult to achieve. Pactum AI’s customer base is broadly looking at 10X ROI, which, now, is easily done thanks to the use of AI agents. Agents also allow procurement teams to scale extremely fast, which is something that has, historically, been hard-won. 

“For example, if you need to change payment terms across your entire supply base, you can do that with thousands of agents in parallel. You could never do that before. It gives you the agility to react to global macro risk issues, like tariffs.”

Start now; perfection comes later

One of the loudest topics of conversation at DPW New York 2025 was data quality and the challenge of cleaning that data up. It’s a huge topic, and a daunting one. Many businesses fall into the trap of thinking their data has to be perfect before they can get fully involved with AI, but the conclusion many procurement leaders are coming to is that getting started is more important than perfection.

“Data quality is always the holy grail going forward,” says Velte. “Everyone’s going to look for it, and try to attain it. When you start implementing within an AI framework, you just need to go in there and know that you’re going to constantly evolve in a good way, thanks to the agents, AI programs, and initiatives. They’re going to uncover and unlock a lot of data and inconsistencies that you have. You won’t get there unless you start looking into them as an opportunity area. Data perfection is not the way to go; it’s about getting in there, starting to look at the opportunities, and being willing to be creative, disruptive, and innovating quickly.

“There’s never going to be a time when everything is 100% correct and accurate, because data is always evolving,” adds Strydom. “Start now. The data can be enriched over time with the agents’ help.” 

Maximum savings, maximum momentum

Pactum is using AI specifically to enable it to be a strategic advisor for customers like Honeywell. The use cases coming out are very new, and changing fast. What Strydom and his team want is to be able to guide customers on the right strategies for them, how to get maximum savings, and maximum momentum. As this landscape becomes more complex, human intervention and guidance is more important than ever, which links back to the topic of mindset and change management. 

There’s been a lot of debate within Pactum AI as to how the business embraces this. “From a marketing perspective, too, there’s the question of whether we should make our agents look human,” says Strydom. “Actually, what we’re seeing is that suppliers actually enjoy interfacing with a bot. Walmart, one of our customers, did a survey where they found that 85% of their suppliers actually prefer to negotiate with Pactum than with a human. It’s more efficient, fair, and unbiased.”

Speaking of humans, shortage of talent has been a talking point within procurement for some time. That was, until advanced tech became more widely adopted, and bringing in procurement experts became less important than bringing in technology experts who are willing to learn. With the advent of agentic AI, according to Strydom, procurement leaders are now acting as managers of agents.

“All the analyst surveys say that procurement organisations are being asked to do more with less every year,” he says. “So the type of talent is definitely transforming. What we see is that the procurement organisations of the future are much more strategic. They’re focusing on creating strategy and procurement policies and procedures, and then having the agents actually go out and do the menial day-to-day work – entering things into ERP, turning requisitions into purchase orders, onboarding suppliers, and so on. All of that can now be done very quickly and efficiently by agents. This really elevates the role, and allows procurement to become a partner to the business.”

Velte adds: “When you talk about talent shortage, it’s also that shift in the mindset we’re going through right now. The expertise is changing, and we want to be able to bring in talented people with that technology flare. When we look at the next generation of leaders coming out of university and college, they’re AI enabled already. They’re expecting AI to be available to them to accelerate their development, career goals, and ambitions.”

Making sense of the landscape

As DPW New York 2025 unfolded around us, the discussion inevitably turned to the ways in which DPW helps procurement make sense of the AI landscape. Pactum AI is actually a perfect example of how useful DPW is. Only four years ago, the business was a startup, and won a pitch contest at DPW Amsterdam. “That catapulted the business, and got us a lot of visibility,” says Strydom. “It’s a great place for visibility with practitioners, investors, and partners.”

Again, it comes back to people. Being able to meet them in real life, communicate face-to-face, and learn from one another. “It’s about reconnecting with a lot of our partners,” says Velte. “But it’s also about seeing what is out there on the forefront that’s becoming available. It’s an amazing opportunity for us to really benchmark ourselves, while also getting a glimpse of what’s coming around the corner.”

  • AI in Procurement

At Kinexions 2025, Jennifer Roberts, Supply Chain Leader, IBM who talked us through how the supply chain is transforming at the global giant

Jennifer Roberts, Supply Chain Leader at IBM, is visibly buzzing as she shares her favourite Kinexions moments so far. “Kinexions is really exciting,” she says, having flown in from Raleigh-Durham, North Carolina to be here. “The first thing for me is getting to see the people I work with at Kinaxis who help advance the solution within IBM,” she explains. “We have a great account management team that’s helping us look to the future. And the energy here is always exciting. They really are a motivating company when it comes to thinking about the future. I’m really thankful that IBM invested in the ability of our teams to join the event this year.”

Roberts and IBM’s C-level executive suite for supply chain are located at Raleigh-Durham’s Research Triangle Park where IBM has a large facility covering 600 acres. “It’s a good place to be,” she says. “But a large part of my team is broadly located throughout the US in Poughkeepsie, New York, Rochester and Minnesota. And then we also have a team down in Guadalajara, Mexico. The global supply chain is located everywhere, but the people I work with are primarily in those locations.” 

Roberts leads Demand Planning Operations for IBM’s hardware manufacturing division, supporting mainframe, power, and storage products across both internal and contract manufacturing. She supports transformation efforts within the Demand Supply Planning and Inventory organisations.

Supply chain transformation

Roberts specialises in configuring and modelling planning architecture in Kinaxis and SAP, translating, automating and transforming business processes, while identifying and collecting the relevant data from various large unstructured data sources. Her goal is to optimise supply chain processes and tools, reduce costs, improve efficiency and enhance customer satisfaction. 

The words “revolution” and “transformation” have embodied the discourse at Kinexions and these are two concepts that play out in a major way at IBM. “Our business is all about transformation,” she explains. “We are constantly looking to evolve to solve a variety of different areas of opportunity. There’s certainly never a day where we aren’t thinking about what the next disruption may be. And so within our organisation, we focus a lot on resiliency, protecting our supply chain and ensuring we can deliver quality to our clients.” Indeed, IBM onboarded Kinaxis around five years ago to help transform Demand Planning and Supply Planning. Kinaxis Maestro provides IBM with the transparency needed to see how changes in demand and supply affect each other, utilising the most current data to run multiple concurrent scenarios.

AI in supply chain

IBM’s supply chain transformation efforts are currently focused heavily on AI. Of course, IBM has been leaders in the AI space for quite some time with the Watsonx products, but supply chain is considered client zero within IBM for that platform. “We are focused on efficiencies in the organisation, digital transformation, developing digital twins and taking enterprise data and bringing it together so that we can orchestrate a plan that is visible to all through one source of truth,” she reveals. “And that’s something we can all execute against seamlessly.”

“Everyone wants data in real-time. Everyone is looking for accuracy of data. They’re looking for answers to problems faster than we’ve ever been able to perform before,” she explains. “When the next big diversion comes, the next big distraction, we need to be able to quickly align ourselves, not just within the supply chain, but upstream with our sales organisation, who are feeding us all the sales opportunities and giving us insight into where the business is going. And then our downstream suppliers need to be equally connected. So, we partner with those organisations to ensure it’s all very seamless and that our data flows in both directions so we can manage results. So, one of the advantages of our internal AI supply chain tool, which we call CSCA 360 (Cognitive Advisor), is to get a 360-degree view of the world considering all those products. And access is a big part of that because we run our S&OP and MRP (Material Requirements Planning) processes through that tool, along with our inventory management process as well.”

According to Roberts, the biggest opportunities for Supply Chain at IBM lay within ways to mitigate disruptions earlier, boosting resiliency and agility, while protecting the supply chain. “There are things that hit us between the eyes at the last minute, and we have to be as responsive as possible to solve those problems. Data insights and being able to assess them proactively, is so important. And that’s where I see our organisation heading more strategically, through taking the data, ingesting it faster, making decisions on it, using generative AI and focusing on allowing people to dig into the data more quickly and get answers on information they’re seeking. We’ve been using agentic AI for years, but we’re really starting to dig into what it can do for us now in terms of impacting productivity.”

The human touch

Although Kinexions has been showcasing transformation and technological revolution it has also stressed the importance of work culture, something vitally important to Roberts. “Our leadership drives the mindset of transformation being at the forefront of where we’re going, in order to keep up with the demands of the future,” she tells us. “We’re always being asked to look at where we can create opportunities within the business and not just taking the leadership’s advice on what we should be doing. We look to all our employees and get their ideas from the bottom up; deciding whether or not there’s business value that can be returned from things that aren’t always visible.

“I think the most important part of your business is your people. Without having the ability of your people to be transparent in where they see opportunities, you really are going to hold yourselves back. Keep an open mind, ask a lot of questions, listen closely. I’m always told you have two ears and one mouth. And I think as a leadership team, you should allow your employees to come forth with ideas, plus, we need to think about why they are suggesting them – well, it’s because they’re impacted every day by what’s going on around them. So, listen.”

  • Digital Supply Chain
  • Together in Events

From automating decisions to redefining procurement talent, AlixPartners lays out why risk-takers lead the way.

The use of artificial intelligence (AI) in procurement is gaining traction with many organisations already looking at how the technology can improve processes. However, there’s scope to go beyond efficiency and instead focus on transforming value delivery. 

At DPW New York, we spoke to Amit Mahajan and Aaron Addicoat from AlixPartners, a management consultancy firm doing things a little differently. The organisation is advising its clients on how to implement AI to drive value, but it’s also using AI internally, too. 

“AlixPartners has a unique business model,” explains Addicoat. “We have a very senior model, very few junior resources. So now you imagine taking people with 10 or 15 years experience and now you equip them with AI… For us, it’s a huge unlock.”

This is about more than just productivity gains. AlixPartners focuses on using AI to transform the way procurement teams work, while crucially, maintaining the human touch.

How procurement professionals are using AI

With the support of technology, it’s possible to shift procurement from a cost-saving exercise to a potential revenue driver. Procurement teams are already looking for these opportunities, as Mahajan explains. “They’re starting to think about new ways of doing things,” he says. “It’s not just automation, but asking how do I leapfrog and do something differently?”

There are plenty of use cases where AI is helping with automation. This is a great place to start as it frees up human workers to do more valuable jobs that need a personal touch. “I have a client who’s using AI every day,” says Addicoat. “This allows them to review documents and contracts rapidly, to find key clauses and termination dates. They’re also using it in spend control processes to identify which things need to be reviewed more thoroughly.”

Many organisations are also using AI agentically to create their own bots. This gives teams a more accessible way to review information. “One example is a client who’s using AI for their business to help with acronyms,” says Addicoat. “They built it as an acronym tool to help break down the language barrier between different functions using different terms. This led to better engagement.”

This empowers employees across an organisation to be more autonomous while still getting the full picture. Agentic AI, especially, allows them to interact with information in a way that previously would’ve required specialist technical knowledge. Now, it’s possible to query information within a contract directly. 

“It’s about using agents and AI to look at anomalies within your procurement contracts,” explains Mahajan, “and be able to help the category analysts, the category specialists, and others to get more of those insights.”

While generative AI might be a hot topic, it’s not the only way to use the technology. In combining several sources of data and using AI to spot trends, it’s possible to create workflows tailored to the current environment. Addicoat explains: “We take a series of data inputs, such as weather patterns, lead times, contractual terms, inventory, and forecast. Then the AI generates the purchase order, queues it for review, and upon approval, places the order.”

This can help an organisation to place orders with the right supplier in the most timely fashion to avoid delays, and optimise for cost, for example. This fully automates the end-to-end process, using AI to interpret those important data signals.

While this is useful for procurement teams, it’s only the start. “Using AI in this way is really cool,” says Addicoat, “but what I found most fascinating is that you’re building a data model, and with AI layered into it, that over time can tell you how to optimise itself.”

This has huge implications for procurement teams looking to save money and drive revenue. “For example, it could tell us the commodity price at a certain point in time was low,” says Addicoat, “but because inventory capacity to hold resin was maxed out the client could only buy so much at that low price. So now investing in a new storage unit at a cost of a few hundred thousand dollars could, under the same scenario in the future, save millions of dollars..Data quality challenges

A roadblock that can stop procurement teams from fully embracing AI is a lack of quality data. With so many sources of information, often including paper-based documents, some might think it’s difficult to get the data AI needs to be truly useful.

“Don’t wait for everything to be perfect before you get started,” says Addicoat. 

This is a sentiment echoed by Mahajan: “Use AI to solve your data problem before solving your business problems.”

This requires a mindset shift. While AI can help cleanse, enrich, and structure existing unstructured data, it’s important to take the right approach. Shift from asking ‘what can we do with our data?’ to ‘what value do we need to create?’ and work backwards from there.

With this approach, the questions are less about the data and more about the business problem. This then allows you to use AI to work with the information you have to help answer those questions.

“Start with the value proposition in mind and work backwards,” explains Addicoat. “You can get data from anywhere — it has to serve a purpose.”

Bringing back the human touch

AI can free up procurement teams to focus on tasks that need more nuance and expertise. Using technology to automate workflows and make information more accessible has a huge impact on employee productivity. “It’s fundamentally transforming the way they work, the amount of work they can do, and the type of work they’re able to do,” says Addicoat.

There’s always the worry that with any new technology, the human element will be forgotten. “With every new advancement that comes in,” says Mahajan, “whether that was a steam engine or when computers came along, everybody wondered what they were going to do. But as humans, we always find ways to start doing higher-level work.”

This means that many professionals will find new ways of doing things. “Imagine all the mundane tasks you have to do in your daily job now,” Addicoat continues. “With these new ways of working, imagine the speed with which you can turn an idea into something real. All that time you free up allows you to go talk to people and build relationships that mean something.”

On the other side of things, the sheer volume of AI-generated content out there is going to drive people towards those more meaningful interactions. “You don’t know what to trust and what to believe anymore,” Addicoat says. “That’s going to lead to a resurgence in face-to-face content, being at the office, and being at events.”

AI’s impact on procurement talent

The talent landscape is changing. With technology playing a larger part than ever before, organisations don’t just need procurement professionals, they need adaptable, tech-savvy people. The nature of the job means that those in procurement need a wide range of skills. 

“We do everything,” says Addicoat, “legal, operations, supply chain, negotiation, analytics. Procurement professionals are generalists.” 

Tech plays into every element of that skillset, which means tech skills are becoming even more important for candidates applying for procurement roles. “Nobody goes to college thinking they’ll be a procurement professional,” says Mahajan, “but with AI and tech, that’s changing.”

With procurement often seen as a proving ground for leadership, embedding these tech-minded generalists could have a huge impact on the future. “We have a shortage of talent,” explains Addicoat. “But with more and more CEOs and COOs coming from procurement, that speaks volumes to what procurement does and the value it brings, as well as what the future holds.”

At AlixPartners, the passion for procurement is very clear with Addicoat saying: “There are only two kinds of people in the world: those who love procurement and those who don’t know it yet.”

Change is coming

With AI of all forms steadily gaining traction, procurement could change dramatically in the coming years. It’s the organisations that are willing to take risks and embrace change that will come out on top.

“AI has the potential to disrupt the whole management consulting world,” says Mahajan. “Firms focused on transformation will thrive.” 

With AI’s capabilities increasing rapidly, it’s difficult to predict what comes next. However, adaptability is key. “Hold onto your hat. In a year and a half, the world’s going to look very different,” concludes Addicoat.

  • AI in Procurement

AI is already transforming procurement, but meaningful value depends on more than just tools. At Beroe, that starts with aligning AI to real business problems

As AI continues to dominate conference stages and boardroom discussions, the pressure to use it is everywhere. As this technology becomes further embedded in enterprise strategy, many organisations are still grappling with how to apply it in a way that delivers real, measurable value.

Rather than focusing on AI for the sake of innovation, the question now is how to align new tools with real business problems. That means looking beyond dashboards and pilots to deploy AI where it can simplify decision-making and improve processes.

At Beroe, this principle is central to how AI solutions are developed, deployed, and scaled. As the company behind the world’s leading procurement intelligence platform, Beroe provides real-time market data, cost analysis, and supplier risk assessments, empowering thousands of organisations globally to streamline operations and mitigate risks. Its latest advances in autonomous negotiation, supplier discovery, and predictive analytics show what it means to align AI with business objectives.

Speaking with Prerna Dhawan, Chief Product Officer at Beroe, during this year’s DPW New York conference, the discussion explored how procurement leaders can move beyond hype and start unlocking the full potential of AI.

Misalignment with business needs

There are plenty of real-world examples of how AI can improve efficiency within a business, from automating manual tasks like invoice processing to identifying new suppliers based on complex sourcing criteria. Accessing this technology is easier than ever with a wide range of tools available to procurement professionals. It can be tempting to jump on the bandwagon and integrate AI across every area of an organisation, but success requires a more nuanced approach.

The key is to ask the right questions, Dhawan explains: “We talk about all the latest and greatest technology out there, but what does it mean in practical terms? We need to ask, ‘How can I apply it today in the work I am doing as a head of product or as a procurement professional?’”

The allure of generative AI is especially strong, but business leaders should ask whether that’s the right solution for their needs. As with any decision, it’s important to consider the business problem. “It starts with a little bit of knowledge about what you’re looking for,” says Dhawan. “What are some of your biggest challenges, and which of those challenges could AI technology solve?”

Matching the right tool to the job

Once an organisation has identified a specific problem, it’s possible to find the AI solution that fits. While generative AI gets a lot of attention, other AI technologies and machine learning based systems might be more appropriate. 

In some cases, prescriptive, rule-based, or predictive AI could be a better choice to solve a problem without the need for a large language model. For example, forecasting commodity prices doesn’t require generative AI, just strong, contextual machine learning. 

“We are looking at AI across two dimensions,” says Dhawan. “Firstly, what is our offering to customers, in terms of procurement intelligence and autonomous negotiation technology. Second, we are looking at AI internally. Let’s say in product development, how do we use the latest AI solutions to accelerate our product development cycles so we can release new modules and capabilities more quickly.”

Regardless of the type of tool chosen, it should cover a high-impact use case. Integrating AI to solve a problem that only surfaces for a small group of people a couple of times a year won’t have a great return on investment. Instead, look for regularly occurring problems that, if fixed, could have a huge impact on productivity or quality. 

Reducing the cognitive load

We’re already bombarded by information, and the use of AI to add to this doesn’t make sense. “I don’t need another dashboard in my life,” says Dhawan. 

When implemented correctly, AI can make data more accessible while reducing cognitive load for users. The result is increased productivity and faster decision-making. 

“I think the power of AI is to simplify access to data. This is why ChatGPT has been a success: it democratises access to information. That’s what our B2B technology world is waiting for. It gives me something simple that allows me to talk to my data. Then I can focus on what insights I need to make a decision or take action.”

For most B2B users, the key is intelligent simplification. Look for ways to simplify access to data through agent AI tools and conversational interfaces. This brings the focus back to action rather than dashboards.

Inside Beroe

While many procurement teams are still exploring AI’s potential, Beroe has already embedded it across both its platform and internal operations. The company, founded in 2006, provides procurement intelligence to thousands of organisations worldwide. Its platform delivers the critical data that professionals need to make informed sourcing decisions, from commodity prices and risk indicators to ESG scores and supplier intelligence.

“We provide all data that procurement needs for decision making, whether it’s cost data, risk data, ESG data or price data,” says Dhawan. “Our reimagination of the future is not just giving access to more data but creating that layer of recommendations that help you make decisions at speed and scale.”

One of the clearest examples of this in action is Beroe’s new ‘autonomous negotiations’ platform resulting from its recent acquisition of negotiation technology business, nnamu.  Delivering a significant evolution in the procurement technology landscape the platform enhances the foundational elements of AI and game theory with Beroe’s industry-leading market intelligence and, according to Dhawan, it’s being deployed successfully in live sourcing scenarios.

“This is a technology that is being used for multilateral negotiations,” Dhawan explained. “It’s no longer just a POC or prototype, it’s live and being used at scale.” These new tools reflect Beroe’s core mission: to help procurement professionals minimise surprises and maximise margins. 

Crucially, Beroe isn’t waiting for perfect data to apply these technologies. Instead, the company is using AI to work with what’s available — cleansing, interpreting, and extracting value from both structured and unstructured sources.

“You can use AI for cleansing data – even paper contracts,” Dhawan says. “Historically, we thought data had to be structured. But now, with vision models and image analytics, that’s no longer the case.”

Rather than striving for 100% accuracy before taking action, Beroe embraces a more agile mindset that balances speed and precision. 

Is mindset holding procurement back?

The technology is ready. The use cases are proven. So why do so many procurement teams still hesitate to embrace AI? “There’s this subconscious fear that I think is a barrier to adoption,” she said. “And to some extent, it’s to do with our friends in Hollywood.”

There’s the myth that AI is a job-threatening black box, especially in industries where trust and experience are the backbone of good decision-making. For procurement, where professional judgement and business context are critical, the idea of handing over tasks to AI can feel risky.

But Dhawan believes this fear is misplaced. At Beroe, AI isn’t replacing procurement professionals, it’s augmenting them. Whether it’s surfacing new suppliers, automating elements of negotiation, or flagging risks earlier in the sourcing cycle, the aim is to enhance human decision-making. She says: “I think with the new kinds of AI technology that’s available to us, it is an opportunity for us in B2B tech to embrace more human-centred design with higher focus on UX.”

Looking ahead

Looking ahead to 2026 and beyond, Dhawan sees procurement evolving into a more personalised and responsive function – one where AI plays a critical role in both strategy and execution.

“We see hyper-personalisation coming, both in supplier relationships and internal stakeholder engagement,” she explains. “AI will be at the centre of that.”

Rather than one-size-fits-all sourcing strategies, AI will enable procurement teams to tailor their approaches to specific business units, categories, or even individual suppliers. This means smarter segmentation, more relevant insights, and stronger commercial outcomes.

Another key shift is the growing ability to connect macro events, such as geopolitical shocks or regulatory changes, with micro actions inside the business. AI can help procurement teams identify these signals earlier, respond faster, and still align with long-term goals such as cost efficiency or sustainability.

“It’s about balancing your fire-fighting reactions to market events with your long term goals and strategy,” says Dhawan. “Procurement needs visibility and flexibility at the same time.”

Beroe is already moving in this direction. Alongside its growing AI capabilities, the company is refining how it delivers intelligence, building agents and recommendation layers that not only inform decisions, but also help teams take action on them. Whether that means automating routine negotiations or proactively flagging supply risks, Beroe is evolving to meet the needs of a procurement function that’s more dynamic than ever.

As Dhawan points out, the goal isn’t to overwhelm teams with more tools, it’s to make their lives easier. “It’s about reducing complexity and giving procurement professionals confidence in what to do next,” she concludes.

For many procurement leaders, AI still feels like a long-term ambition. But the solutions are already here, and through companies like Beroe, they’re already in use. The challenge now is not whether AI can deliver value. It’s whether teams are ready to adopt the mindset and cultural shift that will allow them to unlock that value.

  • AI in Procurement

Jonathan Jackman, Regional VP at Kinaxis, dives into how AI is reshaping supply chain planning.

Artificial intelligence (AI) is often seen as a threat to jobs, with a recent TUC poll showing half of UK adults worry that AI will take their job. When it comes to the supply chain sector, AI is shaping up to be a powerful tool that empowers planners to take on more creative, fulfilling roles. 

The prospect of AI-enabled supply chain planning is an exciting one for both professionals and businesses. Scaling operations without the need to massively increase headcount is a major selling point for any enterprise, while for professionals, the prospect of removing the repetitive, mundane and manual processes that restrict and slow effective planning is surely a promising one.  

Far from job elimination, AI is a major upgrade for supply chain workers in a number of different ways. We’re entering a new era of increasingly autonomous AI systems, which will elevate supply chain planning to new heights. So, how exactly will the day-to-day role of the planner evolve as we go further into the AI era? 

Humans still in control 

First, it’s important to dispel a myth: the supply chains of the future will not be “driverless”. Many believe that AI, and particularly agentic AI, has the potential to run supply chains on autopilot. This is far from reality: while AI can surface insights, automate tasks and even take action in a crisis, it will always need to be augmented by a human to fully interpret the nuances of the real-world. 

This human oversight is a crucial failsafe. There will be many times where AI flags potential shortages and proposes the best way to respond, but it will only ever be as good as the insights it is fed and the guidance given by human. For example, what if it is missing a crucial bit of real-time information about an upcoming election which could lead to disruptive trade challenges? While the algorithms. may be great at crunching the numbers and making recommendations, only a human planner can assess the full context surrounding a decision before deciding action. 

The future of supply chain planning isn’t AI instead of humans, it will be AI and humans. In the AI era, supply chain professionals will be the orchestrators, steering AI systems and validating recommendations with important human insights and context.  

Each planner is likely to have fleets of AI agents beneath them, acting as demand forecasters, inventory optimisers and scenario simulators – feeding information back to the supply chain professionals to empower them to make the best decisions based on the maximum amount of data analysis, all done in real time. 

Planners unleashed 

With AI handling the mundane and routine supply chain tasks, planners will be unleashed to focus on the creative, strategic elements of the job that machines simply cannot do: building relationships, working with partners, building and selling strategy, and, of course, managing AI agents. 

Consider negotiations with partners, for example, AI won’t be able to compete with a human. It will, though, supply planners with the data they need to enter those discussions armed with deeper insights than ever before, empowering them to work more effectively. 

Planners will also play a critical role in shaping the very AI tools they use – training models, curating data, and ensuring outputs reflect reality. Over time, this human feedback loop will make the technology even more valuable.     

One key evolutionary step we are starting to see is the emergence of Autonomous Concurrent Orchestration. Currently, many vendors focus on agents automating existing siloed processes, but in the future, we will see more agents that synchronise planning decisions across functions – procurement, logistics, manufacturing – in real time. Agent-to-agent communication will break down silos and speed up problem solving and decision making, easing the burden on supply chain professionals. 

Augmenting, not replacing 

Perhaps artificial intelligence is the wrong phrase when it comes to supply chains Instead, the industry should be discussing augmented intelligence, where machines unlock insights and real-time decision making that simply wasn’t possible when tasks relied on manual processes.   

For planners, the AI era promises exciting change: embracing new tools and evolving alongside this technology is not only good for business, but good for the careers of supply chain professionals. 

  • AI in Supply Chain

We sat down with Abe Eshkenazi, CEO of ASCM, to dig into the organisation’s focus points, and how CHAINge is addressing supply chain’s needs

Tell me a bit about your background, and how you got into supply chain.

Early in my career, I spent quite a bit of time in operations and materials management. We didn’t call it supply chain back in the day – it went by a number of different terms. Not surprisingly, given my role within ASCM, I worked closely with supply chain professionals, not only to elevate the role of the supply chain professional, but to understand the impact that supply chain has on business and society. 

At ASCM, we’re focused on not only supporting that competent, capable individual, but ensuring that organisations are responsible in terms of using supply chain to really enable consumers and patients to get what they need at a reasonable price and reasonable time. This is what supply chain is about. My background combines that business management education and deep engagement with supply chain professionals. This gives me a strong appreciation for not only their challenges, but the opportunities the field faces today.

Tell me about the planning for CHAINge NA this year. What were you looking to achieve when putting ideas together?

Today, supply chain professionals are trying to balance efficiency with geographic diversity and political resilience. They’re trying to put those things together and identify what would make an individual do their job better and exchange that information with others. So our planning is centered around a key theme, which is: how do we equip supply chain professionals for what’s next? 

The systems that we built for speed and cost optimisation are under stress right now. They’re struggling under the weight of complexity, volatility, consumer demands, and all the disruptions that we’re facing today. We’re being called today to rethink not only how quickly and cheaply we can move things and get them to the consumer, but how responsibly, transparently, and resiliently we can operate today. Our hope is that the engagement part of the event enables individuals to exchange information and walk away with insights and actionable strategies that can be taken back to their organisations and implemented. We’re truly looking for that engagement from the attendees. This is an event for the attendees, by the attendees.

It’s also about making the contact and relationships that we all depend on. We’re all seeking opportunities and examples of organisations that have done it better or have responded easier to the challenges that we’re facing today. This provides individuals with an opportunity to engage. We had an opportunity to do this at our European event, after which attendees overwhelmingly indicated that the engagement part – the opportunity to exchange information learned from each other – was a key element of the event itself. We’re trying to replicate that, but with the amount of issues that the US is facing versus the rest of the world, the topics are going to be a little bit different here.

What are the core topics covered at CHAINge NA that you think are most helpful for supply chain professionals?

We need to take a temperature of the current environment, and not surprisingly, we structure the event around several core themes that we’re all facing today. First, resilient and agile supply chains. The adaptability that’s required today is unlike any time that we’ve ever faced. We’ve had disruptions before, and we’ve responded as an industry. Today, we’re continuing to respond, but the pressures on these individuals due to day-to-day uncertainty has created a very different environment.

The second core topic is emerging technologies. As the focus on resiliency and agility becomes much more critical, there are only a few ways to gather the data necessary to enable organisations to make informed decisions. Not surprisingly, AI, digital twins, and a whole host of scenario planning technology tools are a focus for a lot of organisations today. Digital transformation is happening in almost every organisation to shore up their visibility, their transparency, and their traceability.

Also, advancing sustainability practices. We can’t forget that at the end of the day, we still need to be sustainable as an industry. This has been a huge focus within supply chain. It’s taken a little bit of a backseat in the current environment, but organisations are still focused on ensuring that they are sustainable and ethical in their business practices. Lastly, no discussion can be had without understanding what the talent availability is, what their capabilities are, and whether we are ensuring that we do have the right talent.

How important is collaboration (accelerated by things like CHAINge) in supply chain, especially as the landscape becomes more complex?

In today’s environment, as we focus on visibility and on connecting all parts of our supply chain end-to-end, we understand the demand signals clearly so that we can address them appropriately. Collaboration is no longer optional – it’s essential. No single individual organisation can solve today’s challenges on their own, whether it’s navigating geopolitical tensions, managing risk in a global network, or even driving sustainability. The solutions demand cross-functional and industry collaboration. It used to be that the Chief Supply Chain Officer in the back room was only called upon when there was a crisis. Well, I think we’ve got enough crises today that we need to push that individual into the front office.

First, we need to enable them to use their voice at the table to advocate for appropriate supply chain practices, but also in combination with a wide range of other roles. These are the teams that are now addressing these issues. It’s no longer just a supply chain issue; it’s an organisational issue. It’s a societal issue that we now need to address, and there’s only one way to address that; that’s through collaboration within the organisation, as well as with your partners, your vendors, and your vendor’s vendor. This is a very dynamic environment today, and enabling organisations to have that complete visibility and connectivity is critical.

There’s been a lot of talk about a shortage of talent across supply chain; how big an issue is this, from your perspective? And how can it be overcome?

From our perspective, it’s one of the defining issues of our time. As supply chain has moved from the back office to the boardroom, so has the demand for skilled professionals. More often than not, supply chain people come out of finance or engineering. In today’s environment – a very diverse workforce – digital natives are coming into the workforce. They’re not only adaptable, but very comfortable with modern technology. It’s a little bit of a reverse from the leadership that we have in supply chain today, that may still be using that Excel spreadsheet on their systems. Supply chain has the demand for those skilled individuals.

To address this, we’re focused on a number of things. First, expanding the awareness of supply chain as a rewarding career path, which our salary and satisfaction surveys confirm. Secondly, talking openly about investing in ongoing professional development. We’ve been to a lot of conferences and whether we’re talking about AI, sustainability, or disruptions, at the end of the discussion, it always comes down to people. We should be talking about the people at the beginning of the discussion as opposed to the end of it. We need to create that opportunity for individuals to see that they can not only make a difference, but that their voice is heard and followed on within their organisation. That’s what we’re preparing supply chain professionals for. 

We need to provide an inclusive workplace that attracts and retains that diverse talent. As I indicated before, individuals coming into the workforce are digital natives. They’re very adept at AI and they’re more than willing to jump in with the technology. We need to enable them with problem solving, critical thinking, and experience on the job. I couldn’t be more excited about the individuals coming into the workforce today and the focus, and they’re able to change the world through supply chain.

How can supply chain professionals approach the challenge of ever-changing regulatory requirements?

Financial markets and supply chains do not like uncertainty. We like certain demand signals so we can ensure that our supplies are appropriately managed. Supply chain professionals need to have robust systems to monitor changes and provide that data, or the regulatory information and policy individuals reporting become significant. Among the concerns that we have is that more often than not, it’s become regulatory or policy and it becomes a checklist. Part of that concern is whether we’re really focused on really making a change, or focused just on those compliance checklists that often drive down to minimum effect.

Today, technology helps, but so does developing a culture of compliance and resiliency. Once again, collaboration matters, sharing best practices across industries, and enabling individuals to understand that there are ways to respond to the regulatory and the policy changes. 

What are some of the most exciting innovations happening in supply chain today?

I think the combination of the people and technology is what’s going to make an exponential difference. On the technology side, tools like advanced analytics, AI, and digital twins are transforming how we forecast, manage risk, and build resiliency. The real innovation is combining cutting edge technology with a highly skilled, adaptable workforce. I heard a fantastic quote the other day: ‘AI is not going to take your job; an individual using AI is going to take your job’. That’s where the focus is right now – enabling individuals to use technology to really leverage that and enable organisations to be much more responsive and agile, as they address demands.

  • Digital Supply Chain
  • Events
  • Host Perspectives

The two-day event (9th-10th September) offers attendees all the tools they need to improve their resilience and adaptability.

Be the CHAINge you want to see in supply chain, and join fellow supply chain professionals at CHAINge North America. Located at the Greater Columbus Convention Center, in the heart of Columbus, Ohio, the two-day event (9th-10th September) offers attendees all the tools they need to improve their resilience and adaptability.

SupplyChain Strategy readers receive an exclusive $200 discount when registering for CHAINge North America, by using code SCS200

The event gives attendees access to a rich agenda of learning opportunities, covering topics such as:

  • Supply chain digitalisation
  • Data visibility
  • Risk and resilience 
  • Future-proofing supply chains
  • Woman in supply chain
  • Harnessing AI

And much more. Those attending CHAINge North America join their peers for two days of interactive learning, lively discussion, and novel ideas to drive change in their own supply chain. 

All supply chain professionals and executives are welcome to become part of the movement and discover the latest in supply chain innovation.

Register today and use our exclusive discount code: SCS200

As well as eye-opening talks, CHAINge North America attendees gain access to:

  • 10-minute innovation tech showcases
  • Educational breakout sessions
  • Use case theatres
  • Industry Q&A

Join your fellow professionals on the 9th and 10th of September for this industry-leading event. Register now and use code SCS200 for $200 off the cost.

  • Event Newsroom

SupplyChain Strategy attended July’s Exiger Executive Forum to hear from the best and the brightest in the industry.

Supply chain resilience is one of the most pressing concerns of modern business, whether executives are aware of it or not. That was the central theme of the Exiger Executive Forum held on July 23rd 2025. Titled Supply Chain Sovereignty in a Fractured World: Winning the AI and Geopolitical Race for Resilience, the event brought together business analysts, CEOs, supply chain and procurement executives, academics, and politicians for an open discussion around supply chain sovereignty and the urgent need to secure supply chains across myriad industries and territories.

As geopolitical events, trade wars, and threats to globalised networks threaten to destabilise global and local supply chains, the case for supply chain sovereignty, which is an organisation’s ability to control its supply chain and minimise dependence on external suppliers, becomes increasingly stark. However, a myriad of stakeholders must come together to enable organisations and nations to gain independent control of supply chains, and collaboration between industry, government, and academia is essential.

Three guest speakers joined Maria Villablanca, CEO and Co-Founder of Future Insights Network, each representing voices from within politics, business, and academia: Tobias Ellwood, former UK Minister and Chair of the Defence Select Committee; Koray Köse, CEO and Chief Analyst of Köse Advisory, Senior Fellow at GlobSEC Geotech Centre, and Board Member of Slave-Free Alliance; and Karsten Machholz, Professor for Supply Chain Management and Strategic Procurement at University of Applied Sciences, Wuerzburg-Schweinfurt. 

The discussion exemplified the discordancy of priorities and perspectives among senior voices from all angles regarding security, economics, policies all impacting value chains, albeit with a shared willingness to engage in secure, competitive, ethical and innovative supply chains, fuelling businesses and economies through heightened volatility in a fractured world that is recalibrating through the era of reglobalisation.

Supply chain sovereignty: Bridging political understanding, and urgency

“It is a dangerous world that we’re entering,” Ellwood warned. “If I ask you ‘Do you think the world will be safer or more dangerous in five years from now?’, I think we’d all agree in which direction it’s going. We have to then ask ourselves how we prepare for that.” To that end, Ellwood believes an increased focus on supply chain sovereignty is both an economic and military imperative.

For Ellwood, the central issue is limited understanding, both public and private, around the urgency presented by the current risk and threat environments. Through the combination of limited knowledge around supply chain complexity and an election cycle-focused impetus to enact vote-winning policies, he believes the political class lacks both the nous and urgency to prioritise supply chain sovereignty.

“After 20 years in politics, I can safely say that many politicians are simply unaware of what’s coming over the hill,” said Ellwood. “The tide took me out to the last general election, and so I went from helping to craft and nudge policy and encourage Britain to move forward to then scrutinising what we were doing, not just at home but internationally. Now that I’m outside of politics, I continue doing those same things.”

The necessity for political engagement is not lost on Köse, who through his own experiences of researching, advising and leading supply chain organisations, has been advocating for supply chain resilience as a top line driver for economies and companies, has equally encountered the depth of that disconnect.

“At an early point I realised that geopolitics is the key denominator for all value chains and all of us in this context,” he said, adding that work is overdue but starting to be underway to bridge this gap. “The London Defence Conference, as one critical congregation, is key for you all folks to be aware of. Not only because of what they do in terms of bringing the politicians into one room to debate some of the most fierce topics of the day, but it’s all about convergence. Bringing in supply chain leaders, policy makers and technology folks with a direct approach to debate.”

Villablanca noted that Ellwood’s presence was indicative of a gradually shifting tide, however. “It’s not lost on me that here we are in this panel, talking about supply chain, and we have a former politician with us,” she said. “That is very different to some of my earliest supply chain conferences where we didn’t see that, so it’s a sign of the times. Set the scene for us around why you’re here and why it’s important to discuss the geopolitical situation vis-a-vis supply chain today.”

“I spent most of my time in politics trying to strategise, trying to go four or five chess moves ahead, and I found I was on my own,” Ellwood replied. “Politicians operate for the day, for the here and now, the election cycle; the news cycle is what keeps them busy. They’re not thinking about these things and yet the world we’re now seeing in everything… everything is being weaponised because that is the change in the character of conflict.

“But today, from my perspective, I see the world splintering into two spheres of hugely competing influences. If you look at the number of countries that have signed up to China’s One Belt One Road initiative, you’ll see that many of them are either opting or hedging their bets as to where things go. 

“To make matters worse, our exemplifiers of what democracy looks like aren’t in a good place. We see what’s going on in America, British politics and so on, and Europe and America are not on the same page. We aren’t promoting global law in the sense that we had a sense of determination that we had when organisations were set up in 1945. Other nations are getting together and realising that there’s an opportunity to exploit the wobbliness of our world order and do things their own way.

“That’s where the mechanisation of just about anything comes in to cause us economic harm, to sow political discord from afar. It’s very easy to do and becoming easier simply because of the openness of our society. It means, from a rudimentary perspective, anything you do can be weaponised against you.”

“It’s very easy, from afar, to then limit your supply chains and thereby limit your capabilities. There are countries that specialise in sowing economic discord from afar. They understand and learn and know supply chains better than we do, and they can work out which missing pieces will cause our assembly lines to grind to a halt.”

That lack of preparedness, he says, is an impediment to putting the nation on a footing that could support a war effort on the scale of the World Wars.

He continued: “There’s also the prospect of preparing for war, which means that we are suddenly spending more money on defence. Our ability to switch on the supply chain levers to support military capability is not there. This is why companies that have no connection with the defence world need to think about the services they provide that might have a military bearing. In five years time, you may be called upon to do exactly that.

“That is the mindset we now need to get into. Security and economy are one and the same now, and that’s what we need to learn.”

AI, foresight, and risk strategy

The conversation then shifted to the business side, where securing critical supply chains powering key technologies such as AI, defence and security, biotech, energy and quantum computing has become a more pressing concern in the wake of a range of global disruptions through the early 2020s. 

Along with broad supply chain breakdown during the COVID-19 pandemic, the geopolitical environment has become more fraught. Escalating trade wars, the imposition of sweeping import tariffs in the US and heightening tensions between America and China have thrown globalised networks into question. Alongside those challenges, Environmental, Social and Governance (ESG) directives have placed an increased onus on supply chain leaders to sanitise their supply networks against modern slavery, conflict minerals, and indirectly sourcing materials from rogue nations. The case for establishing redundancies in supply, as well as heightening visibility on an end-to-end supply basis, was thus clear amongst the panel.

“Koray, you work with a lot of different companies,” began Villablanca. “Do you think there’s a mindset issue where politics and commerciality need to come together to realise the common goal and create resilient supply chains?”

Directly, there probably is a mindset issue,” Köse replied. “I think there is a lack of clarity about the importance of geopolitics’ impact upon supply chains, and there is certainly the capability issue of understanding the context of geopolitics.” He then elaborated on the challenge by highlighting shortfalls in companies’ predictive capabilities.

“Companies operate with risk dashboards,” he continued. “Sometimes it’s just red, yellow, green, and that’s all you have. They have a few key risk indicators like financial compliance issues, quality issues, performance issues, but you never see strategic foresight. It’s retroactive, based on historical numbers. If you look at a production line it might say, ‘We didn’t have an incident for 80 days’. What if somebody were to say, ‘We won’t have an incident in the next 100 or 80 days’? You don’t see that in production; it always looks backwards because it is built on the past.

“A big problem in a lot of the military complex, and in politics, is thinking that the next war will be like the last one. They cannot necessarily understand that asymmetric, hybrid and proxy warfare is really where things are going, and the same goes for technology. Supply chains are often built on yesterday’s technology.”

To then end, he believes supply chain leaders should be more forthright in leveraging their profound influence upon business operations: “In supply chain, we see the conversation about having a ‘seat at the table’ for decades now and I always say, ‘Just bring your own freaking table’, and invite everybody to it. Everything, every cent in an organisation, goes through you. Own that leverage and don’t run after them, invite them to come to you. Your table is where value is generated, secured and innovation and competitiveness are established. You hold the fate of the future.”

As to politics’ place within meeting this challenge, Villablanca asked Ellwood whether the political sphere could be doing more to shape the corporate agenda.

Yes, and that last point you said is the most critical; recognising that there is a massive risk, that this is a very different world that we’re now facing, and I expect the point that’s really being made is the absence of politicians,” he said. “The politicians themselves need to be told what we need because their expertise in understanding this arena is poor.

“China now owns the periodic table. If you are into silicon wafers, where’s your serum going to come from? If you’re into magnets, where’s your Europium going to come from? You need to know this sort of detail, and it’s not just you yourself. It’s your suppliers and the suppliers of your suppliers, too.”

While supply chain transparency has undoubtedly increased in recent years, he stressed that considerable work remains to realise total visibility.

“At a recent procurement event I was astonished at how many household names were unaware of what their second and third-tier partners were doing during the procurement cycle,” Ellwood continued. “They didn’t understand the vulnerabilities, down to the SMEs, of what’s going on. If the assembly line stops then that’s quite serious, but what’s going to happen because of that stress? 

“There are people who don’t understand it over here, not recognising that our competitors are deliberately looking at our supply chains and working out where that vulnerability lies. It is so that Ford stops making trucks, so that pharmaceuticals stop making medicines. Ministers are ignorant about this and we need to become better at it. This is the frontline of the next war that we’ll fight, and that war is coming.”

“I would add that some can’t fathom the complexity of certain supply chains and the vulnerability and risk associated with multiple tiers within them,” Villablanca posited. “There’s probably a translation issue with regards to business and politics around supply chain.”

To this, Ellwood stressed that international government groups hold the keys to unlocking a broader understanding within members’ respective political spheres.

“The G7, the Five Eyes Alliance, this is where these conversations need to go,” said Ellwood. “To recognise this must be a priority within the western world, we now need to have an alternative source to make sure that we can build our aircraft, we can build our factories, we can build our products. It isn’t so much the rare earth minerals themselves, but it’s the processing. Setting up a processing factory for rare earth minerals takes almost a decade.”

Here, a guest interjected with a point that hearkened back to Ellwood’s own admission that politicians have an innate directive to focus on local, vote-winning issues: “Politicians recognise there are no votes in this. The average MP will say their inbox is full of ‘fix the NHS’, ‘get the roads fixed’.”

Resolving political challenges such as those, Ellwood replied, is predicated upon strengthening economies to open fiscal headroom for public investment.

“If our economy is affected by problems with our supply chains, there’ll be no money in the treasury,” he explained. “Not for health, transport, potholes, policing, defence. It’s imperative that if you want to fill the coffers, then we need to protect ourselves. You can only do that with supply chain resilience. As a politician, you’ve got to take the people with you if you want to make the case.”

Villablanca then repositioned the conversation with regards to pressing issues around sustainability.

“There’s a lot of risk associated with our supply chains that goes beyond geopolitics,” she said. “We also have climate issues, economic issues. How do we maintain sovereignty in our supply chains while still trying to pursue goals around sustainability?”

“Supply chain transparency is something that I advocated for when I was a young consultant in the early 2000s when my hair was not so grey,” said Machholz, highlighting the gradual shift in supply chain priorities around identifying the finer details across those networks. “It isn’t a new topic and in the EU we now have the Critical Raw Materials Act.

Machholz drew the conversation towards sustainability in the context of integrity and continuity. “I’m German, and what we have is engineering power. We are good at car and machine manufacturing, but we have no natural resources. We have a little bit of coal, but all other things need to be imported. There have to be some sources to get those things.

“There’s Trump and tariffs going up and down, and we have some other geopolitical tensions affecting supply. You might say, ‘Where do I source this particular thing from? We don’t really have a second source of supply, because both of these sources are located in the same geographical spot.’ Maybe both of them are coming out of China.”

For Machholz, lessons to be gleaned around forecasting with technology’s latest predictive capabilities were presented en masse by the pandemic. “If we look at COVID, almost all supply chains were disrupted and you were running out of materials,” he continued. “You needed to be much more risk alert, and this is the problem we have already touched on: not looking in the back mirror, but using your data and turning insights into foresights to see what could happen, and then being agile and adapting.

“Sustainability could be one thing, having several sources, having alternatives, but of course, especially if we’re talking about critical raw materials, critical parts or maybe patent-protected or monopolistic suppliers, we are in an ambitious situation, put it that way, to find some alternatives.”

Machholz stressed: “This is something that each supply chain manager, CPO, and CFO, needs to understand to set boards’ scenarios. I’m pretty sure with the help of artificial intelligence we can elaborate much more on our data and predict different scenarios so we can be more prepared rather than just reactive.”

Shifting from cost-cutting to resilience

Of course, supply chain executives are under siege from an enormous breadth of challenges, whether it’s geopolitics, technological evolution as both a benefit and a threat, and shifts in consumer behaviours precipitated by those same factors. Rising to meet those challenges on all fronts, especially in a business landscape that often adheres to cost optimisation and efficiency over investing in resilience, can give rise to decision paralysis or financially-stymied strategies.

Turning to Köse, Villablanca asked: “There’s a mountain of black swan events lurking around us, ready to attack at any minute. What are the things that a supply chain leader should be focusing on today to try to build resilience?”

“To be honest, I don’t think they’re looking at building resilience,” said Köse. “What they’re doing right now is cost optimisation, looking at inflation and making sure that the profit margins are going to be protected through the bottom line, not considering top line revenue maximisation. 

“I think agility and economics always need to come back to top line, which basically means in the context of normal business 101 you are producing something, that there is a want and a need and a willingness to pay, and not necessarily hyper-focusing on the cost line or saying, ‘I’m not going to produce a bunch of bullshit that nobody’s going to pay for, just because I got to claim savings to my CFO’.”

I’m going to challenge you there,” Villablanca interjected. “I think, theoretically, that’s great, but everybody in this room is running a business. We have our own boards, people above us, board directors and so on saying, at the end of the day, you are remunerated and we are all remunerated for our quotas. How do you deal with the day-to-day management of your business as well as building that kind of resilience, agility and visibility?”

To this, Köse stressed that the difference can be made by reframing how businesses examine and counteract risk. “We’re thinking about turning the tide by really embedding foresight in risk indicators. Those risk indicators need to incorporate geotechnical, geostrategic issues with foresight,” he continued before highlighting what he implied to be a tendency for organisations to bury their heads in the sand when faced with developing geopolitical challenges.

“I published an article before Russia invaded Ukraine, about Russia getting ready to invade Ukraine, that went through loads of red tape and debate internally that calling Russia an aggressor was cancelled out from the research note,” said Köse. “They said, ‘You can’t say that’ while it was pretty obvious that Russia were clearly the aggressors. 

“The supply chain-focused function needs to spread out and have these geopolitical indicators, geotech-related risk indicators, and not just the last financial report from your supplier A to Z or tier one or tier two.

“We must then tie it back to the value and revenue you’re generating. Get away from this hyper focus and obsession with savings. In that context, make your analytics smarter with a bold analysis of things that you feel uncomfortable about. Think about ‘what now?’ and think about politics. I know we eradicated politics out of business as much as we eradicated many other beliefs from the conversation, but it has to come back.”

With this in mind, he proposed that cost optimisation is to an organisation’s detriment where resilience is concerned, not to its security. “Your indicators for success are not just on the cost line item or bottom line. Your priority must be on the top line. If I sell more, I can grow. With cost optimisation you can shrink yourself to death. That’s what some countries have done with political reviews where you shrink this, you shrink that, let’s shrink here, let’s shrink there. Potholes, collapsing bridges and rail systems, come because of the shrinkage of your investment budget for public infrastructure, for example. What I have found in the last decade of the sustainability high is that it actually impeded resilience, while the narrative said it was supposed to increase resilience.”

To this, Machholz highlighted the data behind Köse’s comments that resilience offers heightened growth potential than cost-cutting measures.

There were some studies from McKinsey which showed that companies who are investing in risk management are 4.7 times more profitable than those who don’t,” Machholz shared, stressing that businesses engaged in this mindset are missing growth opportunities. 

“People just fall back and say, ‘Okay, now the risk is over, COVID is over, whatever event is over,” he continued. “‘We can just go back to business as usual’. Resilience is just extra cost, extra inventory, maybe a second supply chain that needs attention, money, and people to take care of it, and they just simply don’t do it. This is, I think, one of the big threats that we are all facing.”

Exiger Executive Forum: A closer look 

The Exiger Executive Forum (EEF) in London is a global think tank that brings together elite independent voices from strategy, policy, technology and business to equip leaders with the frameworks and foresight needed to navigate the multipolar era. The EEF is exclusively curated for industry experts, analysts, policy makers, and senior procurement and supply chain decision-makers through Exiger, a market-leading supply chain AI company. The next Exiger Executive Forum ‘War-time Economics: How Europe’s €800BN Defence Spend Will Reshape Supply Chains’ will take place in London on Thursday, September 18th, 2025.

Ellwood concurred that this lack of foresight and willingness to invest in protective supply chain measures leaves businesses undefended against interruptions both foreseen and not. “We need to prepare ourselves for unexpected events to happen as the norm,” he said. “What would happen to any business if it didn’t have power for 72 hours? How would you look after your personnel? How do you make sure you salvage the business so that, after 72 hours, you can get back up and running. These aren’t questions that we naturally posed at the moment because again, we tend to park these things.

“The mentality may be, ‘The world certainly feels like it’s getting dangerous, but my life actually looks okay.’ That isn’t the right attitude. If you go to Sweden or Finland, who are much closer to the war with Russia, they are preparing in a way that we are not for a major event or incident. It may well be that when something happens and it’s the moment where governments wake up, but you shouldn’t be waiting for that moment.”

Villablanca then highlighted the recent, universal example of poor supply chain resilience bringing business, both domestic and international, to a grinding halt. “Did we learn nothing from COVID?” she asked. “Did we not take the opportunity to stress test our supply chains and look for the vulnerabilities within multiple layers?”

In response, Ellwood invited guests to consider whether the muscle developed in response to COVID’s interruptions had been allowed to atrophy. “I think that’s a question for everybody; how much of that was retained?” he asked before blending the conversation of supply chain agility with the potential for organisations to support national security should their respective nations go to war. 

“During COVID, supply opportunities came about,” he said. “Everyone here today represents diverse businesses. What services do you provide that you could tweak or add value to where something else has fallen short? 

“That’s where life really becomes interesting because that’s what happened in the First and Second World Wars. We called on organisations that previously had no interest in helping out with the war effort to add support and value to the wider machine and protect ourselves from a resilience perspective.”

Challenges faced by supply chains, he explained, have analogues to business that clearly marry the political and business spheres: “When we say ‘war effort’ today, it isn’t just Army, Air Force, Navy, air, land and sea. It’s now cyber, it’s space, it’s coastguard, it’s AI. This greater warfare is where a lot of the real pain will happen. As happened in COVID, it’s going to be the clever people in the industry that step forward to say, ‘I’ve already thought about this’. They’re in the patent-esque mode, they’ve done the work to say, with a few tweaks here and there, give us some extra money, and I can alter what I’m producing to provide a solution.”

The roles of government and industry

While there are clear precedents for, and incoming needs to, prioritise supply chain resilience in both the political and business spheres, the conversation made it clear that a unified front stands to offer the most impact.

The challenge, particularly in a political environment preoccupied with economic stabilisation, increased productivity, and soothed international relations, is identifying a shared north star or galvanising body to lead the shared project.

Striking at the heart of the conversation, one guest posited:If we want to align supply chain and geopolitics moving forward with a mutually-reinforcing relationship and shared goals, joint risk assessment, a focus on resilience over efficiency, and heightened cross-disciplinary talent and data,  what are the forward steps? 

“What can we within industry do in partnership with governments to move this forward?”

Representing the political voice, Ellwood replied: “There are certainly supply chain improvements that you can do on a national, sovereign basis. But from where I sit, there is a wide political threat that we face and are losing right now. One of them is to do with the energy supply, and another is the threat of AI. The quantum race will be won or lost in the next five years’ time, and that will be game-changing. It simply means that if the winner can harness the power of computing on that scale, everything’s over.”

Ellwood then invoked the technological advancements made in modern wartime, stressing that political figures must wield the mindset of those times to accelerate progress.

“I would like to see some two or three Manhattan Project equivalents, if you like, to ask, ‘How do we harness modular nuclear power?’,” he said. “That’s a very easy way to keep our lights on locally. Then, how do you harness AI? Let’s make sure it is this side of the world that wins that. 

“Again, there isn’t that coordination, that sense of urgency, because it’s too far down the road,” he concluded, then highlighting that opposing forces on the world stage already have the unified capabilities that many Western nations lack. “State, industry, and academia in China, for example, are all morphed into one and that gives them huge benefits in the race for these key arenas.”

Köse elaborated on this point by highlighting Turkey’s effective coalescence of business and government.

“If you think about the private-public national defence sector in Turkey, it came from being totally dependent on the US armoury to a leading innovator of drone wars,” Köse explained. “When you think about asymmetric warfare, innovative, impactful and economic weaponry, from drones to secure soldier transportation and all of that, think about what Turkey is producing right now in technology compared to others. The headway Turkey experienced in the last decade in the defence sector is unprecedented.

“That private-public sector coalition and symbiosis has covered such a need for them in a decade that many are surprised. I think that is something that Europe has to relearn, because Europe thinks a lot about public sector dominance in an area where the private sector should actually take charge. In the US, it’s the opposite. They say, ‘keep the public sector out’. The solution lies in collaboration and bringing each sectors strength to the table while leaving out their weaknesses and flaws.

While of course not advocating for adopting the political model, he agreed with Ellwood that nations like China have an innate advantage in this race. “When you think about the way that the autocratic countries are going about it, it’s the public sector dominating the private sector environment,” he said. “That’s why they’re so hyperfocused on things and they can scale but not necessarily innovate in this sector.

“I love the government when it’s in the right place to actually do something positive and impactful. But when I’m exposed to it, I usually get anxiety issues due to the lack of pragmatism, innovation and agility. But hopefully there’s this convergence of politics, business and academia driving intelligence into critical sectors and industry, and we’re trying to drive it through this think tank here.”

The unified case for supply chain sovereignty

Exiger’s Supply Chain Sovereignty in a Fractured World event was an enlightening review of the supply chain landscape and the myriad challenges and stakeholders it encompasses. 

While the panellists’ conversation in many ways highlighted the disconnect between government, business, and academia, the resonating message was one of shared pressures and goals. Where governments have pulled back on the reins of public spending, many organisations have in kind adopted a cost-optimisation mindset that may protect the bottom line but opens the door to heightened vulnerability. 

Where governments must consider challenges around energy sovereignty and insulating populations against the breakdown of globalised networks – as was demonstrated upon Russia’s invasion of Ukraine in 2022 – supply chain executives must create redundancies to cover lapses and minimise potential disruptions to production and wider organisational integrity.

The guests’ final comment, that states which can marry both the public and private spheres towards shared interests, neatly encapsulates the urgency with which those worlds must reunite. While much work remains to enmesh those spheres, it is clear that the conversation is progressing at pace.

  • AI in Supply Chain
  • Digital Supply Chain
  • Events
  • Host Perspectives

James Watson and Rachel Noll, Argon & Co, explore how smarter use of data, automation, and robotics can help manufacturers unlock productivity.

The UK government’s newly launched industrial strategy was long in the making, but has arrived with bold ambitions. Its 10-year roadmap for economic growth has a firm bet on advanced manufacturing as one of the eight high-potential industries in the UK, along with sectors like financial services, clean energy, and life sciences.

For many operating in this sector, this support couldn’t have arrived soon enough. Manufacturing has been pushed from disruption to disruption, hampered by inflation, persistent labour shortages, and global supply chain crises. Businesses have been urgently calling for tools to help them do more with less, and, against this backdrop, the government’s commitment to invest in digital transformation and skills has been widely welcomed.

The industrial strategy features investment in specialist advisory services and organisations to increase technology and robotics adoption across advanced manufacturing. But the big question is now whether it will deliver the change that manufacturers are hankering for, especially in relation to smart manufacturing.

How manufacturers can get smart: in five stages

Central to the Advanced Manufacturing Sector Plan is a push to scale the adoption of robotics, data, and advanced digital technologies. While cutting-edge automation and predictive AI are becoming more accessible, many manufacturers – particularly SMEs – still lack the maturity or infrastructure to implement them.

The industrial strategy aims to bridge this gap, announcing a new Robotics and Autonomous Systems (RAS) programme, backed by an initial investment of £40 million. This will establish a new network of Robotics Adoption Hubs – physical centres with the expertise, equipment, and connections to accelerate firms’ adoption of robotics. These will be designed as a ‘one-stop shop’ to help end-users invest in RAS technologies in a safe, low-risk environment.

However, smarter manufacturing also needs to be backed by operational visibility and a strong data foundation. Here’s how manufacturers can embark on this journey successfully:

Stage one: Increase operational visibility

Manufacturers first need sight of their core operational metrics to define and monitor performance. After all, you cannot improve what you don’t measure.

Many manufacturers still rely on paper-based reports and inconsistent metrics, making it hard to compare shifts or pinpoint problems. Without operational visibility, actions tend to be reactive and retrospective. Perhaps a shift has underperformed, but without reliable data, it’s impossible to identify the cause.

The first step is defining consistent metrics across all shifts – such as operatives per line, output per line, downtime reasons, or quality defects. Even simple tools like whiteboards or spreadsheets can instil the habit of consistent data capture and begin building a mindset of continuous improvement. The input might be manual and prone to human error, but it provides a common point of reference and highlights areas needing further insight. 

Stage two: Build deeper operational insight

Capturing data in an automated format is inherently more reliable, as it doesn’t require human interpretation. Data such as scan times, equipment health and performance, and employee clock-in and out times can feed into visualisation tools like Power BI or Grafana, helping to spot trends and anomalies over time.

Data is ideally stored in a data warehouse to allow for secure deposit and retrieval in a structured format. Layering information from different sources can reveal patterns. For example, does the mechanical equipment perform consistently at all hours? Are reworks linked to break times?

Organisations may spend longer in this phase retrieving, cleansing, and analysing data, but it’s a vital foundation for future analytics.

Stage three: Apply predictive analytics

One of the defining features of smarter manufacturing is being able to predict what’s happening next and act on it – and predictive analytics can bring this to the factory floor. With knowledge of trends, organisations can begin to form corrective courses of action, strategies of intervention, and avoid downtime. For instance, if the data shows that breakdowns spike after 100 hours of runtime, repairs and servicing can be scheduled in advance. Or, if absenteeism spikes after bank holidays, extra staff can be rostered.

Stage four: Use prescriptive analytics

At this stage, it is assumed the organisation has a strong data foundation. Prescriptive analytics recommends specific actions based on historical feedback loops: detecting a trend, initiating a response, and measuring its effectiveness.

By combining data sources, like weather, complaints, and inbound profiles, organisations can run probability-based models to suggest specific checks or actions. However, human judgment is still required to execute or validate these suggestions. To build trust, models should offer tracing to help users understand why a decision has been made.

Stage five: Become self-optimising

At this final stage, responses are automated, based on high confidence in the data and models. Trust in data is key to achieving full insights maturity. Getting here has likely taken time, learning, and refinement, and as a result, can be relied upon with little human intervention. Like Google Maps rerouting you in real-time around traffic, self-optimising systems react instantly to disruptions – the user only needs to accept or decline the suggestion.

A “human-in-the-loop” retains a level of control, but decisions can be made in seconds. While full automation across the value chain is ambitious, it can be prioritised in high-value areas.

The human factor

While the industrial strategy is welcomed with open arms by most in the industry, success still depends on people as much as policy. While the journey is data-driven, people are the linchpin to progress – or the lack of.

Resistance to change is common. Humans simply cannot process large volumes of data as effectively as a machine can, but their insight is vital for interpreting results and providing context. Ultimately, the most effective smart manufacturing journeys have a perfect blend of human intuition with machine intelligence. 

  • Digital Supply Chain

John Santagate, Global Senior Vice President of Robotics at Infios, delves into the challenges tariffs pose.

Successful supply chains have always been measured by how well they deal with complexity. Getting deliveries and returns right requires multiple levels of collaboration, information sharing and strategic decision making to reduce the risks of confusion or delays. In tandem, customer expectations have changed. Expedited deliveries and a smooth returns process are now intrinsically linked to a positive customer experience. Amongst US consumers, cost, transparency of shipping and flexibility and ease of returns, including real-time tracking, are now the leading delivery preferences.  

With seamless buying experiences now standard, pauses in supply chain execution have major consequences for customer loyalty and brand reputation. This is particularly damaging at a time when every pound is crucial. Beyond driving cost efficiencies, enhanced speed and resilience are now equal parts of the supply chain challenge, and retailers must get this process right to succeed.

Even if brands understand that resilience is key, achieving this is another matter entirely. The volume and regularity of significant supply chain disruptions have tested the resilience of even the strongest supply chains. Organisations continually reevaluate the processes they have in place to ensure goods continue to reach customers. 

Global impact of tariffs

Political upheaval, global conflicts and the introduction of trade tariffs have driven six months of unprecedented global supply chain uncertainty. It’s estimated that the economic impact of the tariff disruption alone could reach as high as $1.4 trillion globally. Ongoing tensions have destabilised established supplier relationships and created uncertainty in the cost of products and materials. Beyond costs, businesses face increased uncertainty in product availability and financial planning, adding further obstacles to already complex operations.

2025 was a fundamental milestone in supply chain strategy. Single region sourcing and rigid inventory management are rapidly fading. In its place, diversification in sourcing and real-time adaptability have become more important than ever.

At its base, for retailers, navigating the evolving tariff environment is about maintaining customer satisfaction. Organisations have opted to move manufacturing of products to new markets. Others have used previous pauses in tariff implementations, and regular legal challenges, to try and ‘time’ tariff implementations and activate previously budgeted activity at the optimum period.

Among these changes, a question has emerged – in a world that is now defined by constant tariff uncertainty, where can technology help to establish a new, more resilient approach to supply chain execution?

Does forward buying help?

Forward buying of inventory has become the most common response to tariff-inspired uncertainty, as organisations aim to maintain product levels and meet customer demand. In the short term, some stability has been achieved. Organisations have been able to maintain existing purchasing and pricing strategies and the flow of goods. Over the long term, however, this strategy carries risks. In fast moving industries, like consumer goods, demand can be linked to virality. Trends can die as quickly as they begin, increasing the risk of product redundancy. Falling demand already costs even the smallest retailers as much as £10K per year. Over the long term, tariff uncertainty will continue to disturb the balance between purchasing and investor management and could cause costs to spiral. 

Staying future-ready requires businesses to enhance preparedness. Streamlining operations and building real-time visibility are an important step. As peak season planning picks up, many organisations face uncertainty around how to manage procurement and ordering in a way that minimises waste and inefficiency.

Integration of supply chain technologies, like order management (OMS) and warehouse management (WMS), provide real-time visibility across customer demand, supplier delays, and order status. Live, up-to-date information empowers teams to proactively manage and optimise supply chain operations, reducing bottlenecks and maintaining overall efficiency.

Making technology-powered decisions

The current tariff environment has also reduced the decision-making window. Taking a painstaking approach to sourcing goods and materials was once common practise. The current environment, however, necessitates companies to pivot on short notice. The announcement of any new policy or tariff could inflate costs to an unsustainable level. The ability to effectively source alternative suppliers, in markets with smaller tariff restrictions, or being able to re-route products and amend production timelines, has become a focal point of success.  

This level of decision making requires the practical application of data. Predictive analytics are a powerful tool that organisations can use to understand when costs might rise, or delivery delays could happen. Real-time dashboards mitigate supply chain disruption and provide informed and expedited decision making. Businesses can monitor changing global developments; assess potential risks to their own supply chain processes and act in a greatly reduced timeframe. Traditionally, these planning cycles may have taken place on a quarterly basis. Today, data analytics tools mean pivots can be made in days or hours. The impact of this cannot be overstated, building resilience against disruption alongside a wider competitive advantage. 

It is safe to say that disruption isn’t going away. Whilst tariffs undoubtably pose challenges, the opportunity for organisations to use this period for fundamental business change is clear.  Technology can build stronger supply chain processes and speed up real-time decision making. Not only will this improve responses to tariff-based disruption, but ultimately it will improve the ability for businesses to meet customer expectations, which remains the end goal. 

  • Risk & Resilience

Simon Bowes, CVP Manufacturing Industry Strategy EMEA at Blue Yonder, on how to navigate challenging situations in supply chain.

Organisations worldwide continue to face severe supply chain disruptions, creating immense operational challenges. Compounding these difficulties is a bleak economic outlook that shows few signs of improving, keeping consumer confidence stubbornly low.

Meanwhile, experts are claiming that President Trump may stand firm on his plans for sweeping global tariffs. This is despite a US trade court ruling that the President had exceeded his authority in imposing the duties and ordered an immediate block on them – only for a federal appeals court to temporarily reinstate the most sweeping of the President’s tariffs. This means tariffs remain an ongoing problem and, the UK market will likely face further disruption.

When you factor in increased costs, labour shortages, escalating geopolitical tensions, cybersecurity attacks, and weather-related disasters (like the $27 billion in damages seen in the US alone), it’s evident that constant instability has become the new normal for supply chains.

Senior executives agree, with 84% stating in a recent survey, that they have encountered disruptions within their supply chain over the past year. Therefore, organisations must be prepared for the unexpected, understand the potential consequences, and have a plan in place to mitigate such risks. 

How can organisations create a strategy for the unpredictable? The answer is by building a comprehensive plan that integrates the capabilities, processes, and technologies needed to operate efficiently, no matter what happens.

End-to-end supply chain planning

The first step is to create an overarching strategy that encompasses the entire supply chain. Having visibility across all areas will support synchronised planning and communication across disparate functions. 

When organisations bring together teams and processes, they can start to overcome the traditionally fragmented approach to supply chain management. Uncoordinated procedures inevitably create an inefficient and weaker supply chain, which makes it particularly vulnerable to disruptions. 

Whereas, resilience is strengthened by collaboration between functions, if backed with integrated data systems and communication methods to enable sharing of real-time information. Keeping all parties in the loop, with relevant data and meaningful insights, encourages better and faster responses to problems, as well as increases awareness of potential forthcoming issues.

Ideally, what’s needed is an end-to-end connected platform where all departments, offices and sites are working from the same consistent, up-to-date data. And, are not required to change systems to find or cross-check relevant information and iron out anomalies.

Smart decision making with AI and automation

Next, it’s vital to incorporate intelligent automation to improve and speed up decision making. Companies are already using data tools to forecast supply and demand planning, but they now can incorporate AI’s ‘always-on’ capabilities to dynamically evaluate and adapt to changes in supply and demand.  

AI-powered solutions can assess how work is progressing by automating data gathering for analysis and optimisation. Automation can handle routine issues, leaving supply chain professionals free to focus on more strategic tasks. Furthermore, AI can facilitate transparent, trackable decision-making to accommodate predicted supply chain disruptions or react to unexpected ones. This level of auditing provides vital insights that will help refine future decisions and actions for the next time similar circumstances materialise, improving outcomes in the long-term.

Additionally, organisations can leverage AI to predict the likelihood of disruptive events happening. Knowing how often they occur and how they have unfolded in the past can inform decision-making and planning. Whether that’s examining competitor behaviour or economic trends, AI tools can process millions of pieces of real-world data to model likely what-if and worst-case scenarios that could impact the supply chain. While these instances may seldom occur, proactive scenario pre-planning provides the foundation for an effective response in the event of real-world disruptions or disasters.

Organisations should identify the specific issues which present the highest risk to their business and ensure appropriate mitigation measures are ready to be activated immediately they are needed.

Investment in flexible, agile solutions

Restrictive working practices coupled with outdated technology can make it harder to react effectively when disruptions occur. Building long-term supply chain resilience means finding a best-in-class solution and partner with deep domain expertise to guide deployment of appropriate modern technologies.

When considering options, businesses should keep in mind fundamental requirements for flexible, agile technologies. These include checking how a software or platform supports data integration and cross-organisational collaboration, whether it can simulate market conditions in near real-time, if the technology architecture is compatible with AI, and how easily does it scale.

It’s critical to have a technology platform that’s designed for scalability and extensibility to manage changing workloads and requirements. Therefore, organisations should look for products with a cloud-native architecture for scalability and resilience, a microservices-based approach for flexibility, and solutions that are easy to configure and maintain without specialised IT expertise.

Building a resilient supply chain

In today’s volatile business landscape, organisations must embed resilience into their end-to-end supply chains, supported by the right technical infrastructure. Investing in modern technologies and platforms offers additional advantages. Advanced solutions that adapt easily to changing conditions, automate manual processes, and harness the power of AI can also provide a competitive edge. For instance, AI’s ability to crunch and analyse vast amounts of data can reveal hidden opportunities stemming from unexpected events—opportunities that might have been overlooked previously.

By making smart technology decisions, organisations can build more resilient supply chains, enabling them not only to survive in current unstable conditions but also to optimise performance and operate more profitably.

  • AI in Supply Chain
  • Procurement Strategy

By Mohammad Mesgarpour, Head of Data Sciences at Microlise, discusses why we need to think beyond data when it comes to logistics.

Data is everywhere — often invisible, but constantly at work behind the scenes. As we move through our day, it quietly powers much of what we experience. A simple card payment in a shop sets off a chain reaction: your bank processes the transaction, the store updates its stock levels, capturing vehicle location and driving behaviour location data by telematics box, and the company’s central system records the sale.

It’s data that informs the display board on a train platform, letting you know your train is just two minutes away. From our morning routines to our evening commutes, data is woven into how we live in 2025.

And the scale of it is immense.

Today, it’s estimated that there are around 181 zettabytes of data globally. That’s equivalent to one trillion gigabytes or one billion terabytes. In just a few years, this figure is expected to soar to 394 zettabytes — a rapid expansion that highlights just how central data has become to everyday life.

We may not always see it, but at every digital touchpoint, data is shaping the world around us.

Data in logistics

The logistics industry has long recognised the value of data and has been quick to adopt technologies that help improve performance and efficiency. As new tools and systems have emerged, the sector has consistently found ways to use them to its advantage.

It started with the basics. Early telemetry services, such as GPS tracking, gave operators a clear view of  their vehicles’ location on a map – a simple yet powerful tool. From there, the industry moved into deeper insights, analysing fuel consumption patterns and driving behaviours to improve overall fuel efficiency and road safety.

Since then, the capabilities have expanded significantly.

Today, vehicles can generate ten times more data than they did just ten years ago. Thanks to advances in both hardware and software, operators now have access to a wealth of information that can transform decision-making and drive smarter logistics operations.

But this volume of data doesn’t come without challenges. More data doesn’t always mean better outcomes or deeper insights. Businesses are beginning to recognise that without the right systems; high-quality and relevant data; and effective analysis, they can become overwhelmed rather than empowered.

The real opportunity lies not just in capturing data, but in turning it into meaningful, manageable and actionable insight. It can drive operational efficiency, informed decision-making and measurable business outcome.

The appliance of data science

It’s easy to assume that simply collecting data is enough to transform logistics and haulage operations. But in reality, raw data alone won’t deliver results. To drive real value, that data needs to be refined, analysed in context of strategic business objectives. This is where the real analytical challenge begins.

There’s a well-known saying in data science: garbage in, garbage out. And it’s more relevant than ever in an era where artificial intelligence tools – like ChatGPT – are increasingly part of the conversation where the quality of data directly determines the accuracy and effectiveness of the AI model’s output.

Anyone with deep subject matter expertise will quickly spot the flaws when these models are asked about highly specific topics. They may generate convincing answers based on flawed or outdated sources, and while experts can see through the inaccuracies, others may accept them at face value. When that misinformation is reused and reinforced, the cycle continues, leading to skewed conclusions and poor decisions.

The bottom line? Better data leads to better outcomes.

This principle becomes even more important in real-world applications, such as complying with the government’s updated requirement to inspect trailer braking systems at least four times a year instead of once. With accurate, well-managed data, operators can confidently predict when inspections should take place, helping to reduce downtime, avoid unnecessary checks and keep fleets moving efficiently.

Turn around, go back

Geofencing is another area where accurate data is critical to the success of logistics operations. When systems misreport how long a delivery takes after entering a geofence (delivery site), the ripple effects can disrupt far more than just one delivery.

Inaccuracies here can throw off turnaround times, leading to incorrect arrival and departure times, delayed subsequent jobs, inaccurate performance metrics and ultimately frustrated customers. What begins as a small data issue can quickly escalate, leading to missed expectations, strained relationships and inefficiencies across the board. Moreover, if this inaccurate turnaround time is fed into a machine learning model to improve future logistics planning, it can lead to a systematic degradation in the model’s reliability and usefulness, and consequently, in the effectiveness of the plan itself.

High-quality data helps avoid these pitfalls entirely. When the source information is precise, the systems built around it work as intended. And importantly, solving data issues upstream before they feed into larger workflows is far simpler than trying to fix the consequences later on.

In logistics, precision isn’t a luxury. It’s essential.

Open source informs much more

Modern technology plays a key role in identifying the behaviours that impact operational efficiency. Actions like harsh braking, rapid acceleration or excessive cornering speed all contribute to increased fuel consumption. And today’s systems don’t just monitor them, they help correct them. Moreover, onboard sensors and telematics devices track and monitor vehicle health in real time, flagging issues before they become costly problems. Whether it’s the driver, the transport manager or fleet manager, having this information early enables proactive maintenance rather than reactive fixes.

The story doesn’t stop at the vehicle.

Open-source and crowd-sourced data brings another layer of intelligence, offering a broader context that goes beyond what’s happening inside the cab. By combining internal data with external sources, hauliers can gain insight into accident-prone areas, localised weather patterns or planned road closures; all of which influence route planning and delivery performance.

This level of enrichment adds real value. Rather than simply receiving updates every mile or minute, operators benefit from a fuller picture of the journey, making location data smarter, not just more frequent.

Reporting for duty

Accurate data – whether it’s tracking punctuality, fuel consumption or driver performance – underpins a wide range of operational reports. These insights can be tailored to suit each customer’s needs, helping them streamline operations, drive efficiencies and stay competitive in a fast-moving industry.

As we move toward an expected 394 zettabytes of global data by 2028, the value of this information lies not just in volume, but in context and quality. Future data won’t simply indicate what happened, it will increasingly help explain why it happened, too.

Take driver behaviour as an example. Instead of just recording that a driver braked harshly, new systems will identify the circumstances behind the action. This shift means drivers will be recognised for making safe, responsive decisions rather than penalised by isolated statistics.

It’s a powerful step forward. But unlocking the full potential of this data-driven future depends on how well the information is used. Data must be processed, applied and interpreted thoughtfully. 

When done right, it not only enhances internal operations, but it also delivers measurable value to customers as well.

  • AI in Supply Chain
  • Digital Supply Chain

Charles Crossland, Managing Director at Goodman UK, discusses the unique challenges the food supply chain is facing.

The food supply chain operates under unique pressures. With short product life cycles and a complex journey from source to shelf, it must navigate strict regulatory demands, price volatility, and increasing consumer expectations – all while maintaining speed, freshness, and traceability.

In recent years, global disruptions have exposed vulnerabilities. From reduced access to imported goods to increased transport costs, the sector has had to rapidly adapt. In response, many businesses are turning to technology and data-driven strategies to build resilience and agility into their supply chain operations.

Building resilience in a volatile market

Stock shortages are no longer unusual, and customers are increasingly aware of the fragility of food supply systems. There’s now greater scrutiny on how food moves through the supply chain and growing pressure on businesses to deliver consistency and transparency.

Businesses are adopting new technologies such as artificial intelligence (AI), predictive analytics, and automation to improve supply chain visibility and performance. AI-powered forecasting tools, for example, can help businesses respond faster to demand fluctuations, minimising waste and reducing risk.

At the same time, many have moved away from “just-in-time” approaches for non-perishable goods and are reassessing their sourcing strategies. Dual sourcing, diversified supplier bases, and increased inventory holding are helping to minimise risk and prevent single points of failure.

Smart logistics and strategic warehousing

The transport and distribution stages of the supply chain are also evolving. Soaring fuel prices, labour shortages, and carbon targets are forcing businesses to review delivery routes and optimise their warehouse networks. Proximity to customers is now more important than ever.

By investing in strategically located distribution hubs — close to major infrastructure and consumer populations — businesses can reduce lead times, optimise last-mile logistics, and cut transport-related emissions. 

All logistics operations, from warehousing to transport, are increasingly equipped with smart systems for real-time tracking, allowing for greater control over stock movement and condition. For temperature-sensitive goods in particular, the use of tracking sensors helps monitor freshness, reduce spoilage, and maintain product quality throughout transit.

Extending freshness through technology

Warehousing is undergoing a quiet revolution. Robotics and automated systems are now performing tasks such as picking, sorting, and packing with improved accuracy and speed. This is especially valuable in the food sector, where shelf life and freshness are key.

Technologies being deployed include:

  • Grading visibility systems which assess produce quality and reduce manual handling
  • Advanced freshness testing which pinpoints stages of ripeness with precision
  • Specialised climate control systems, including zoned heating and cooling, to maintain product quality

By reducing errors, extending shelf life, and improving product flow, these innovations contribute directly to reduced food waste.

Sustainability as a supply chain driver

Sustainability is no longer a nice to have — it’s becoming central to how supply chains are designed and operated. The environmental impact of food production and distribution is under growing scrutiny from regulators, retailers, and consumers alike.

Businesses are now expected to track and report on carbon outputs across their operations. Efficient route planning, electrified fleets, and eco-friendly packaging are just some of the areas seeing rapid investment.

Data is critical here too. By using detailed analytics, organisations can identify hotspots for energy use or waste and adjust operations accordingly. Many are now measuring not only emissions but also transport efficiency in a bid to reduce their environmental footprint.

Looking ahead: A tech-enabled, resilient future

Incorporating smart technologies into warehouse workflows and logistics strategies is already delivering benefits — from productivity gains to improved safety and fewer errors. But this is just the beginning.

As food supply chains grow more connected and responsive, businesses will need to continually adapt. The future will be shaped by those able to combine agility with long-term planning — embracing innovation, forming deeper supplier relationships, and keeping sustainability at the core.

  • AI in Supply Chain
  • Sustainability
  • Sustainable Procurement

Mario van den Broek, Partner, RSM Netherlands, dives into regulatory fragmentation and how it’s affecting shipping.

The global shipping industry has reached a critical turning point.

The International Maritime Organization’s (IMO) recently agreed emissions deal has been hailed as a milestone in maritime decarbonisation – signalling long-overdue progress in regulating one of the world’s most polluting industries. But this breakthrough has been overshadowed by a stark omission: the United States’ decision to walk away from negotiations.

The US’s withdrawal raises serious questions about the enforceability and cohesion of the agreement. The IMO’s regulatory model relies on flag states to enforce compliance. If more nations opt out or water down their commitments, enforcement becomes inconsistent, and a two-tier shipping system could emerge: one made up of operators bearing the cost of compliance, and another of those operating under weaker or unenforced regimes.

More worryingly, it risks triggering a wider trend of regulatory fragmentation – with significant consequences for manufacturers, logistics providers and supply chains around the world.

Why is this a setback for companies?

For global businesses, consistency and predictability in regulation are critical. Fragmentation in maritime decarbonisation policy disrupts both. Without a unified global standard, companies must navigate a patchwork of national or regional rules – each with different timelines, thresholds and enforcement regimes. This not only creates legal and operational uncertainty but also increases the cost and complexity of compliance.

Companies that rely on international shipping, especially manufacturers, exporters and retailers, may be forced to choose between higher-cost compliant carriers or risk reputational and regulatory exposure by engaging non-compliant operators. Those costs will not be evenly distributed.

Firms operating across multiple markets may find themselves juggling multiple emissions reporting systems, carbon pricing mechanisms and verification requirements. For small and mid-sized businesses in particular, these added burdens could squeeze margins and dampen competitiveness.

There are also strategic risks. A lack of coherence in shipping policy makes long-term supply chain planning more difficult. For example, businesses that have invested heavily in decarbonisation may now hesitate to go further if they perceive competitors, especially in markets with looser regulation, are gaining an unfair advantage. This could stall progress not just in shipping, but across adjacent sectors that depend on it, from automotive to consumer goods.

The US’s decision to walk away from the IMO negotiations weakens the political legitimacy of the agreement and signals to others that opting out is a viable path. In doing so, it undermines the collective action needed to decarbonise global trade routes. The result is a business environment marked by growing divergence – where resilience is replaced by reactivity and climate ambition is undercut by regulatory uncertainty.

How can companies turn this into a strategic advantage?

While the policy landscape remains uncertain, companies can still take practical steps to prepare for change. Carbon pricing is beginning to influence shipping costs in some markets, and businesses that assess the potential impact early may be better placed to respond. This includes reviewing freight strategies, factoring potential carbon levies into budgeting and setting clearer sustainability expectations for suppliers.

Some organisations are already exploring options to reduce emissions within their supply chains, such as selecting carriers that use alternative fuels like LNG, biofuels or methanol. Manufacturers are responding too, choosing greener carriers, shortening transport routes and investing in digital tools to track and report emissions.

Moreover, embedding sustainability into core decision-making – rather than treating it as a separate or reactive issue – will help companies manage regulatory risk, meet stakeholder expectations, and identify areas for operational improvement. This not only helps them build more resilient supply chains but also aligns with rising customer expectations and investor pressure for greater environmental accountability.

Businesses must not only adapt to regulation but engage constructively in the development of future standards. By contributing insights and maintaining dialogue with industry groups and policymakers, businesses can play a role in shaping a more coordinated, transparent framework for decarbonising global shipping.

Looking ahead

The carbon divide is set to disrupt global trade. As nations diverge in their approach to maritime decarbonisation, companies will increasingly find themselves navigating a fragmented landscape that distorts competition and complicates compliance. But fragmentation doesn’t have to mean paralysis.

By preparing now, engaging constructively, and embedding sustainability into supply chain strategy, businesses can not only mitigate risk but also help shape more stable and predictable conditions for global trade.

  • Sustainable Procurement

Without trust, AI cannot deliver on its full potential, leaving manufacturers hesitant to go beyond pilot projects, says Darren Falconer.

It’s no secret that trust is the foundation for successful AI adoption. By addressing scepticism, prioritising data quality, and ensuring algorithms are explainable and auditable, AI can become a powerful force-multiplier in manufacturing operations. 

Manufacturers are increasingly looking to AI to boost efficiency, streamline operations and automate routine tasks. 75% are planning to step up their AI spending in 2025. However, much of this attention is focused on Generative AI – something that we believe is poorly suited to factory settings.

Part of this misalignment stems from a lack of understanding of AI’s practical applications in industry. With only 7% of manufacturing leaders feeling “very knowledgeable” about AI applications, scepticism and trust issues loom large.

Feedback from vendors and end-users consistently points to trust as a leading barrier to adoption. Without trust, AI cannot deliver on its full potential. This leaves many manufacturers hesitant to go beyond pilot projects, XpertRule’s Technical Director, Darren Falconer explores this further.

Overcoming the AI ‘fear factor’

The portrayal of AI in the media has long been dominated by dystopian headlines and Hollywood blockbusters, with fears of mass unemployment and doomsday narratives. For manufacturers, this continuous, subliminal bombardment creates a trust deficit before any AI project even begins.

Business leaders are having to overcome not only technical hurdles but also the deep-seated scepticism that AI solutions are uncontrollable or inherently risky. To counter this, companies must approach AI with transparency and explainability at every stage, showing that AI is a tool to amplify human capability not replace it. 

For a simple comparison, think about cruise control in a car. [within cars today,] Traditional cruise control maintains a set speed but that’s all. Compare that to adaptive cruise control, which considers real-time conditions, adapts to your driving preferences and responds intelligently. Similarly, AI in manufacturing must adapt to the unique needs and complexities of each operation.

For those implementing these systems, understanding the ‘mechanics’ – how algorithms interact with data inputs and external influences – is a vital part of building trust. Explainable AI bridges the gap between automation and operator oversight, providing a clear view of how the system reacts and adapts. This clarity increases confidence among users, fostering trust in AI’s outputs.

But of course, building trust also requires a mindset shift – from a data-centric focus to a decision-centric approach.

Trust starts with decisions, not data

A common misstep in AI adoption is starting with the data instead of focusing on the desired outcomes. Many manufacturers think, We have all this data – what can we do with it? However, this approach often leads to complex systems that lack focus, transparency, fail to deliver meaningful outcomes and reinforce doubt over AI’s value.

A decision-centric approach begins by asking, What do we want to achieve, and what decisions need to be made to deliver those outcomes? Only then should businesses ask, What data supports those decisions and what are the models linking these decisions to this data?

From there, manufacturers must focus on ensuring data quality – calibrating sensors, cleaning data streams, validating inputs and standardising formats. Remember, the vast majority of AI success lies in data preparation and only a small percentage in the modelling itself.

Imagine a manufacturer aiming to improve quality control. They might gather extensive data from every step of the production process to find possible defects, leading to an overwhelming volume of disjointed data with no clear path to action.

Using a decision-centric approach, they would:

  • Define the goal: Improve product quality and aim to reduce defects by 10% over the next quarter.
  • Identify key decisions: What factors directly impact product quality? What parameters should trigger quality checks? How can inspection processes be optimised to catch defects earlier? What actions should be taken when deviations are detected?
  • Use AI to model the outcomes: Build AI models that analyse historical production data , to discover explainable patterns relating outcomes to metrics like machine settings, material consistency or environmental conditions. The system can then use these models in real time to flag anomalies that indicate potential defects and recommend adjustments to maintain product quality.

This clarity in purpose makes AI implementations transparent, explainable and, ultimately, more trustworthy. It also provides a clear framework for measuring success, helping to build greater confidence from engineers, users and management alike.

A key factor in building trust is recognising that AI doesn’t replace human insights and experience – quite the opposite. Human operators and engineers bring a level of expertise, contextual knowledge and intuition that machines cannot replicate. Having a ‘human in the loop’ is therefore critical to an AI system’s effectiveness.

Decision Intelligence connects Explainable AI principles with operational trustworthiness by embedding human oversight at its core. For example, experienced technicians possess knowledge built up over years of practice. While they can’t be everywhere at once, their expertise can be integrated into AI systems to automate routine decisions while reserving complex or ambiguous scenarios for human intervention.

This balance between human and machine intelligence ensures AI systems remain transparent, reliable and dynamic. It also enables manufacturers to scale the knowledge of their experts, reducing variability across shifts and locations while maintaining trust and accountability.

From pilots to trusted partner

For AI adoption to move from pilot projects to the heart of manufacturing operations, trust must come first. A decision-centric approach offers a practical pathway to achieve this, ensuring AI systems are transparent, aligned with business goals and designed to augment human expertise.

When manufacturers trust their AI systems, they can harness the technology’s full potential, creating new opportunities for efficiency, resilience and competitive advantage. Decision Intelligence becomes the connector between Explainable AI and operational trust, moving AI from being perceived as a risk to becoming a trusted partner.

  • AI in Supply Chain

Maria Torrent March, Managing Director, Warehousing & Logistics, Europe at Iron Mountain, digs into the F&B supply chain landscape.

What are the characteristics and pain points specific to the food and beverage logistics and warehousing sector that set it aside from other sectors? Does it demand more speed? Environmental control? 

The food and beverages (F&B) sector is large, dynamic, and continuously growing due to high consumer demand for everyday products. The warehousing and logistics (W&L) sector must remain flexible and scalable. This is in order to meet deliverables and ensure products are dispatched on time, especially when dealing with perishable items.

    The F&B sector requires greater environmental control to maintain quality and safety. This can be achieved by partnering with W&L providers who are accredited with the British Retail Consortium (BRC). BRC accredited providers are required to meet strict protocols and are certified to hold food and consumer goods. Additionally, BRC warehouses offer several benefits, such as protected company reputation, implementation of industry best practices, and reduction in risks and potential liabilities. These are critical when handling sensitive items when it comes to food storage.  

    How is the process of managing logistics and warehousing in the F&B sector changing? What are the forces driving that change? 

    The management of logistics and warehousing in the F&B sector is undergoing significant transformation. This is driven by evolving consumer demands, regulatory pressures, and technological advancements. Consumers now prioritise products that are delivered quickly and sustainably. It’s pushing companies to adopt faster distribution networks, and eco-friendly practices like solar power, EV charging stations, and rainwater harvesting.

    Technological innovation is also a key factor impacting the evolution of warehousing and logistics in the F&B sector. Automation and AI are optimising warehousing operations, reducing labour costs and errors while improving efficiency in handling perishable goods. The F&B sector is looking to improve efficiency and reduce transportation costs by leveraging strategic locations like the golden logistics triangle. This is a key hub for W&L because of its high number of distribution facilities and proximity to transportation networks such as rail and air. While the railway supply chain is relatively new, it can be ideal for F&B, where goods are heavy and where there are  weight limitations in trucks or shipping. 

    Many high-street retailers stock multiple brands that each have individual supply chains. As a result, they are exploring how they can implement streamlined supply chain strategies across their businesses. They want to partner with 3PLs who can provide consultancy for managing these complex networks of supply chains, and not just a standard solution. 

    How do you make warehouse spaces more flexible and scalable to provide the necessary adaptability to manage fluctuating demand and seasonal peaks?

    The F&B sector often faces challenges with space allocation to meet unpredictable demands. Robotics can be used to perform wall-to-wall scans of warehouses, creating a digital twin. This enables quick decision making and improves warehouse control and reliability in response to changing seasonal peaks. 

    Furthermore, with the use of AI, organisations can predict increases in demand due to holidays, sales, and seasonal trends. Iron Mountain has employed the use of AI across its warehouses. That allows us to predict stock locations and replenishment and improve productivity from the high-quality data received from Dexory. Dexory is a UK-based company that specialises in AI driven warehouse automation. This not only allows warehouses to make fast, real-time decisions on pricing and inventory levels but also helps to predict future demand spikes with greater accuracy.

    Where do technologies like automation, digital twins, IoT, etc. fit into this picture? 

    AI and automation play a crucial role in inventory management. Iron Mountain considered adopting a more traditional setup with stock controllers but was concerned about potential labour shortages In 2024, it was reported that 37% of European warehousing organisations, including those in the UK, were experiencing significant labour shortages. 76% noted a noticeable shortfall. These shortages have impacted the logistics sector, making a notable difference to warehouse and logistical efficiency.

    As a result, Iron Mountain partnered with Dexory to deploy an autonomous robot that provides live data insights by scanning the warehouse daily. This technology delivers full visibility of inventory, which is highly valuable for the F&B sector, where understanding how to quickly move stock based on demand is essential. Additionally, AutoStore is used to provide an automated storage and retrieval system, enabling rapid responses to customer requests. Utilising this technology makes warehouse and logistics operations more efficient, faster, and reliable.

    We’re in an age where disruption is starting to feel like the norm rather than the exception. How can warehousing and logistics help supply chains be more reactive, agile, and resilient? 

    Disruption is common in the W&L sector, so organisations must be both flexible and reliable when it comes to supply disruptions, which can take many forms, including geopolitical conflicts, climate events, or sudden demand spikes.

    Many organisations have had to think about these challenges over the last few years, starting with the pandemic. Sudden world events can force F&B companies to reorganise their supply chains. It’s important to consider these issues from their perspective. For instance, they may be seeking different suppliers in different markets. Ultimately, it’s about offering flexible solutions and tailoring them to the sector you are working with.

    Over time, warehouses have adapted to become more dynamic, technology-driven, and strategically integrated into the broader supply chain. The W&L sector is always looking for scalable solutions that can be implemented when issues or disruptions arise, making it easier for supply chains to adapt and evolve in the face of challenges while maintaining operational efficiency and customer satisfaction.

    • Digital Supply Chain

    Eelco van der Zande, Managing Director of ReBound Returns, helps navigate the issues caused by tariffs.

    Rapid changes in global trade policy are creating serious challenges for businesses operating across borders. With tariffs soaring one day and easing the next, retailers are being forced to rethink how they handle international returns in real time.

    Fluctuating import duties imposed by the US have at times exceeded 145%, and retaliatory measures from key trade partners have thrown global supply chains off balance. Even with the most recent truce reducing US tariffs on China to 30%, there’s no guarantee these figures will hold. As of  June, 2025, US trade policy remains fluid, with ongoing negotiations reshaping tariff structures across multiple regions, including Europe and Asia. President Trump has noted that some levies have been suspended- not cancelled – and may rise again within months.

    Adding to the uncertainty, twelve US states have filed a lawsuit in the Court of International Trade, seeking to halt to the “Liberation Day” tariffs. A US appeals court has allowed the tariffs to remain in effect while it reviews their legality.

    The new risks of cross-border returns

    Amongst the ambiguity, international returns are now under intense scrutiny. With each item crossing a border potentially attracting new tariffs, returning products for restocking has become costly. When an item crosses a border twice- first for sale, then for return- and possibly a third time for resale, retailers face multiple layers of duties and fees. A t-shirt sold internationally could now incur fees exceeding its original retail value. This makes it more important than ever to evaluate every return for cost-efficiency and logistical feasibility.

    Volatility also makes forward planning difficult. Retailers can’t afford to be reactive; returns systems must be agile, localised, and data-driven to navigate the shifting conditions. Strategic returns management is key to future-proofing reverse logistics against unpredictable tariffs.

    Localising and consolidating returns to minimise costs

    One of the most effective ways to reduce tariffs exposure is to localise returns processing. Keeping returns in the country where they were purchased allows retailers to avoid costly re-importation. Processing and storing products at local returns centres and re-fulfilling them to new customers in the same region can save on shipping and duties. Repurposing items through alternative channels can also reduce costs.

    Consolidating returns into fewer, larger shipments rather than handling them individually can significantly  cut logistics expenses. Using regional return hubs to group items before further processing or redistribution reduces transportation spend and carbon footprint. This local-first approach not only limits fuel consumption and emissions, but also supports a circular economy by keeping goods in-region. As ESG expectations rise, aligning reverse logistics with sustainability goals becomes a competitive differentiator. This optimised, local approach enhances efficiency and makes cross-border returns more sustainable and financially viable at scale.

    Faster returns to reduce inventory lag

    With tariffs driving up inventory costs, time has become a critical cost factor in returns management. Every day a returned item sits idle or in transit is a day of lost revenue and tied-up capital. Slow processing delays resale and undermines profitability in an already margin-sensitive environment.

    Retailers must accelerate returns processing to reduce inventory lag. That means quickly assessing, sorting, and restocking products. Fast triaging, localised warehousing and agile reverse logistics can shave days or even weeks off the cycle, improving inventory turnover and unlocking working capital. In practice, faster processing can significantly increase recovered revenue from returned goods.

    Smarter and fewer returns through better data

    As tariffs raise the cost of goods, each return, especially the avoidable ones, become more expensive. Retailers that harness return data across their operations can turn unpredictability into strategic insight. This requires integrating data from multiple sources into a unified view, enabling more accurate demand forecasting, better inventory planning, and identification of products that are driving unnecessary returns.

    Leading retailers are also using AI-powered platforms to anticipate which items are most likely to be returned and to automatically route them to the most efficient return locations. These systems integrate seamlessly with order and warehouse management tools, reducing cycle time and cost.

    Data insights can also reveal deeper patterns, such as size discrepancies, product quality issues, or customer behaviour trends, that are contributing to high return rates. Addressing these issues through refined product descriptions, size guidance, and customer education expectations better can lead to measurable reductions in returns.

    Even modest drops in return rates can yield significant savings when margins are tight. Smarter use of data enables faster, more informed decisions, and stronger profitability.  

    Seamless returns to build customer loyalty

    The increasing complexity of cross-border returns hasn’t slowed rising customer expectations. Shoppers are less forgiving of a clunky or slow returns process, especially when tariffs mean they have paid more or waited longer for their purchase. A seamless experience with fast, easy, and transparent return options is crucial.

    Retailers that offer convenient local drop-off points, clear communication, and flexible refund or exchange options are far more likely to retain customers and drive repeat purchases. Quick refunds help preserve brand loyalty, even amid pricing pressures and economic uncertainty.

    Retailers that prioritise returns optimisation have seen measurable improvements in customer retention and the frequency of repeat purchases. A great returns experience doesn’t just mitigate risk, it builds trust, strengthens brand reputation, and turns a potential point of friction into a loyalty driver. 

    Adapting returns strategies for a shifting tariff landscape

    When tariffs can rise or fall overnight, international returns must be treated as a strategic function, not just a back-end process. They directly impact margins, sustainability, and customer loyalty.

    Retailers that embrace smarter returns management with localised, streamlined processing, better data insight, and seamless customer experiences will be best positioned to weather ongoing volatility.  To get ahead, retailers should consider conducting a full audit of their current returns operations, identifying gaps in localisation, speed, and tech adoption. Investing in smart logistics infrastructure today can unlock major savings and build long-term resilience.

    • Risk & Resilience

    Sylvain Rottier, General Manager at Tennant Company, explores how supply chain professionals are shoring up against labour shortages.

    Europe is facing an ongoing workforce crisis that demands major solutions, meaning business leaders can’t really afford to wait.  The numbers are disconcerting: labour shortages across the European Union have grown from 1.7% in 2014 to 2.6% in the first quarter of 2024—a 53% increase that shows no signs of slowing.

    Indeed, Europe’s demographic crisis seems to be accelerating, with projections indicating the continent will lose 95 million working-age people by 2050 compared to 2015 levels. For supply chain executives, this threatens operational continuity and competitive positioning.

    The impact may vary dramatically across sectors, but few industries will feel the pressure more acutely than essential services like cleaning and facilities management. Annual turnover rates in janitorial services have reached 200-400%, creating a revolving door that diminishes institutional knowledge and operational effectiveness.

    The impact beyond empty positions

    Twenty-five percent of EU businesses now report production problems directly attributable to labour shortages, transforming what was once a staffing inconvenience into an operational constraint.

    The financial implications are potentially severe. Companies experiencing 200% annual turnovers —unfortunately common in labour-intensive sectors—spend six-figure sums annually just on replacement hiring. This figure encompasses recruitment costs, training expenses, and the hidden price of reduced productivity during onboarding periods. However, these costs represent a small part of the problem.

    Quality degradation becomes inevitable when organisations rely heavily on inexperienced workers. Higher error rates, missed cleaning protocols, equipment damage, and inconsistent service delivery damage customer satisfaction and brand reputation. In supply chain environments where precision and reliability are paramount, these quality issues can trigger costly disruptions throughout the entire network.

    Perhaps most concerning is the competitive disadvantage that emerges when labour shortages force companies to reject new business opportunities. Constrained order books and inflated production costs create a vicious cycle where struggling organisations become less attractive employers, further exacerbating their staffing challenges.

    From automation to intelligence

    Traditional automation offered limited relief because it required extensive programming for specific tasks and was often an awkward-at-best fit for changing conditions. Today’s AI-enabled robotic systems represent a huge leap forward, delivering true operational intelligence that can learn and adapt, and also optimise performance in real-time.

    Modern robotic platforms (such as BrainOS, which power Tennant AMR Machines) leverage machine learning algorithms to improve their performance based on environmental feedback and operational data. Unlike their predecessors, these systems can navigate complex, dynamic environments while avoiding obstacles, adjusting cleaning patterns based on usage data, and even predicting maintenance needs before equipment failures occur.

    Integration capabilities have also come a long way. Contemporary AI-powered robots connect with existing warehouse management systems, inventory tracking platforms, and facility management software. This connectivity enables centralised monitoring, performance optimisation, and data-driven decision-making that extends far beyond the robots’ immediate task purpose.

    The technology’s greatest advantage lies in its ability to maintain consistent performance standards. While human workers may struggle with fatigue, illness, or high turnover, AI-enabled robots deliver consistent results that enable accurate capacity planning and service level guarantees.

    Implementation strategy

    Successful AI-robotics deployment requires a shift in thinking from replacement to augmentation. The most effective implementations complement human capabilities rather than eliminate human roles entirely. This approach not only addresses practical concerns about workforce displacement but also maximises return on investment by leveraging the unique strengths of both human intelligence and artificial intelligence.

    Smart organisations begin with pilot programmes that target specific, well-defined tasks within controlled environments. This approach allows teams to understand integration challenges, optimise workflows, and build internal expertise before scaling to full deployment. Critical success factors include ensuring compatibility with existing systems, establishing clear performance metrics, and maintaining open communication with affected workers throughout the transition.

    The skills landscape is evolving rapidly, creating new job categories in real time. Rather than eliminating careers, thoughtful implementation transforms traditional roles into technology-empowered positions that offer greater career advancement potential and higher compensation. For sectors like cleaning services, which have long struggled with “dead-end job” perceptions, this transformation can meet turnover rates with higher-calibre talent.

    Training programmes should prepare workers for collaborative environments where human judgment combines with robotic precision. These hybrid roles often prove more engaging and rewarding than traditional positions, creating career pathways that retain institutional knowledge while embracing technological advancement.

    Building tomorrow’s competitive advantage

    The demographic trends driving current labour shortages will intensify over the coming decades. Organisations that delay AI-robotics adoption risk falling behind competitors who embrace these technologies early and develop operational expertise while the market is still developing.

    However, successful transformation requires more than technology acquisition. Companies must strike a balance between technological capabilities and the human touches that drive innovation, customer relationships, and adaptive problem-solving. The goal isn’t to create fully automated facilities but to build resilient, flexible operations that can weather demographic headwinds.

    Leadership teams must think beyond immediate cost savings to consider long-term strategic positioning. AI-enabled robotics offers the foundation for sustained growth in an environment where traditional staffing models look  increasingly untenable. Early adopters will develop competitive advantages that compound over time, while late movers may find themselves perpetually disadvantaged in both talent acquisition and operational efficiency.

    The question isn’t whether AI-enabled robots will reshape supply chain operations—that transformation is already underway. The critical decision facing business leaders is whether they’ll proactively shape this evolution or reactively respond to competitive pressures once their options become more limited and expensive.

    Europe’s demographic winter demands timely action. For forward-thinking supply chain executives, AI-enabled robotics represents not just a solution to current staffing challenges, but a strategic foundation for long-term competitive success in a potentially shaky marketplace.

    • AI in Supply Chain

    Nigel Pekenc, Partner at Kearney, gives us insights provide insights on current key trends in supply chain, as well as his thoughts on nearshoring and reshoring.

    How are global supply chains evolving to become more resilient in the face of ongoing disruption, such as geopolitical shifts, raw material shortages, and logistics volatility?

    “Supply chains are undergoing a fundamental shift from static, efficiency-led structures to adaptive, digitally managed ecosystems. Companies have moved beyond simply adding redundancy or diversifying suppliers. Instead, they are building globally distributed and closely connected networks, using real-time visibility and predictive analytics to spot vulnerabilities early and respond flexibly. Strong supplier partnerships in key locations and centralised digital control towers that compile multi-tier insights are now essential to manage disruptions ranging from geopolitical unrest to material shortages and transport breakdowns. The aim is no longer just resilience but adaptive responsiveness, enabling businesses to adjust their supply chains dynamically and in real time.”

      Nearshoring continues to gain attention but rarely replaces full-scale global operations. How do you see companies striking the right balance between proximity, efficiency, and cost?

      “Nearshoring has gained prominence, especially amid recent trade disruptions, but companies increasingly see it as part of a strategic mix rather than a full replacement. They strike the right balance by regionalising the most critical parts of the supply chain, particularly those sensitive to lead times, geopolitical risks, or local market demands, while continuing to source globally to maintain flexibility, secure essential inputs, and benefit from specialised production. This hybrid approach often takes the form of multi-node regional hubs connected by digitally coordinated networks. The key is segmenting the supply chain by disruption sensitivity, customer proximity and value-added stages, ensuring nearshoring delivers strategic value without adding unnecessary cost. This balance enhances responsiveness, optimises costs and mitigates risks.”

        What role are technologies such as AI, automation, and digital twins playing in enabling smarter, more adaptive supply chain networks?

        “AI, automation and digital twins have moved from buzzwords to essential pillars of responsive supply chains. AI-driven analytics process vast, complex data to provide predictive insights, enabling proactive action amid market shifts. Digital twins offer virtual replicas of supply networks for scenario testing and stress simulation before disruptions occur. Automation enables the rapid execution of these strategies through intelligent robotics, dynamic inventory control and agile manufacturing. Together, these technologies let supply chains anticipate and adapt to disruptions, turning agility from aspiration into reality.”

          With supply chains becoming increasingly multi-tiered and complex, what strategies are proving most effective in maintaining control, visibility, and risk mitigation across networks?

          “Complex, multi-tier supply chains demand more than standard digitisation; they require fully orchestrated digital ecosystems. Effective companies are establishing integrated digital control towers that deliver real-time transparency and decision-making clarity across all supply chain tiers, from raw materials to end-consumer distribution. Advanced data governance protocols ensure quality information flows seamlessly through well-defined channels. Moreover, clearly established risk categories aligned to decision-making tiers within organisations empower rapid, informed decision-making. In short, the combination of robust digital infrastructure, clear governance and aligned organisational structures is proving indispensable to maintain visibility, manage risk and achieve operational responsiveness at scale.”

            “The future of supply chain strategy will be defined by the interplay of continuous geopolitical fragmentation, accelerated regionalisation and persistent economic volatility. Companies must architect globally distributed, digitally empowered supply ecosystems that embed flexibility and optionality by design. AI-driven predictive tools and digitally enabled scenario planning will move to the centre of strategic supply chain management, allowing businesses to anticipate disruptions and shift resources dynamically and swiftly. Preparing for this future requires immediate investment in digital capabilities, organisational readiness for decentralised decision-making and development of flexible supplier ecosystems. Companies that proactively build these capabilities today will emerge with significant competitive advantages, able to thrive and seize market share in volatile global conditions while competitors falter.”

              • Digital Supply Chain

              Mark Wilkinson, Senior Vice President for OpenText’s Global Business Network, discusses AI-driven success in supply chains.

              AI in industry

              AI might be transforming industries, but its ability to drive accurate workflows relies on a foundation of reliable data. For those working with supply chains, this data can generate assessments of global circumstances and highlight upcoming disruption to operations before it’s felt by the consumer. 

              In the past year, extreme weather, trade disputes, and geopolitics have tested the limits of business preparedness. For example, in October 2024, it was estimated that the storms that hit Valencia caused damage to its farming industry worth almost £1bn. That includes the produce lost and the rendering of underlying infrastructure as unusable. As the impact of the climate crisis drives an increase in natural disasters, supply chains must prepare for widespread disruption.

              Looking to 2026 and beyond, this trend is unlikely to change for the better. To best future-proof business processes, AI will be fundamental. But where should organisations start? 

              Which data is good enough?

              High-quality, accurate data is important for driving AI success in supply chains and providing users with accurate predictions. This enthusiasm is reflected in the expectation that the big data market will be worth over £300 billion by 2028. Despite this significant investment, most organisations, surveyed across industries, still face data-quality issues.

              At present, only 12% of data and analytics professionals believe that their company’s data is ready for AI adoption despite 76% recognising data-driven decision-making as a priority. To drive success in supply chains, this lack of readiness needs to change.

              Data preparation 

              Though action must be taken to remedy these concerns, companies shouldn’t view the quality of their own data as a blocker to innovation. Instead, they can ‘test’ the data before using it to drive insights.

              As a first step, it’s essential to identify the format and quality of existing data assets. With complete knowledge of all the information available, corporations can integrate AI tools that work with their data, instead of trying to fit it into incompatible solutions.

              Next, team leaders must be certain that their employees are trained on noticing hallucinations and changing processes to ensure accurate AI forecasting. Creation of the right procedures will feed into a successful long-term data governance strategy, ensuring full value is extracted by AI tools.

              For ongoing insights, directly reflecting global circumstances, data must be continually fed into AI systems. By setting up the extraction of data from a reliable platform, companies can ensure that the insights they receive directly correspond with the most pressing logistical concerns.

              Incompatible sources

              Strategic partnerships can bring essential expertise for agile transformation, helping companies to scale at speed and improve their assessment of risks. For instance, by integrating data from a partner organisation, visibility across the global logistics landscape will be increased. Concerns arise, however, when data is formatted differently at each company. To mitigate the chance of hallucinations, data-trained workers should be proactively advised to scan insights for duplicates, misspellings, and inaccurate information.

              Visibility

              For operational success amid an ever-changing global landscape, the importance of preparing and ‘cleaning’, data should not be understated. To ensure accurate insights are produced by AI tools, integrated solutions should be compatible with current data-formatting, proactively mitigating the chance of hallucinations. To derive full value, the same ‘cleaning’ procedure should be used for partner data. By taking the right steps at the beginning of the adoption journey, business leaders can drive effective insights, consistently being updated, to support future growth.

              • AI in Supply Chain

              We caught some precious time at Kinexions with Jennifer Dorsch, who outlines the transformation programme underway there.

              If ever there was a company that embodied the transformational spirit of Kinexions, it’s Syensqo, the Belgian multinational materials company. Established in December 2023, through the spin-off from Solvay, Syensqo is both emerging from its legacy company, whilst simultaneously transforming its operations during an era of unprecedented disruption. A challenging situation to say the least.

              Jennifer Dorsch is the Global Head of Supply Chain Center of Excellence at Syensqo; a woman who by her own admission is “transformation driven” and skilled in operational leadership, process optimisation and leveraging technology to achieve best-in-class performance. She is seeking to spearhead global transformation initiatives, enhancing efficiency and growth through streamlined processes, systems and strategic simplification.

              An inspirational leader

              A results-oriented senior executive, and a former Supply Chain Excellence Director at Solvay, Dorsch has a proven record of leading high-performing teams, driving impactful change and delivering measurable results spanning the industrial, supply chain, and finance functions. “As Head of the Global Supply Chain Center of Excellence at Syensqo, I spearhead transformation of the E2E supply chain,” she explains, backstage at the Fairmont Hotel, Austin. 

              The core values of the CoE are based on creating an efficient and resilient supply chain through simplification, standardisation and harmonisation with efforts prioritised in support of company objectives. “We measure the benefits of transformation through supply chain improvements and cost savings and deploy effective change management strategies to ensure adoption of new systems and processes aimed at improving KPIs in support of company objectives,” she reveals. “We also created accountability in support of change management.”

              Jennifer Dorsch, Global Head of Supply Chain Center of Excellence at Syensqo

              Emerging from a legacy

              Syensqo recently split from Solvay representing specialty chemicals while the commodity side remains Solvay. “The split of the company put us right into a transformation and the first challenge to be tackled was planning. And so we’re now using Kinaxis Maestro as a foundation for that. We’re taking it as an opportunity to bring all of our business units into a harmonised way of working through one platform. These are five business units that did things entirely differently. They didn’t even know who each other were and yet now they’re working together. This is quite transformational,” she enthuses.

              Of course, there are challenges to implementing any kind of transformative program and change management nearly always tops the poll as the most demanding. “The hardest part is the change management. There were folks that couldn’t understand, couldn’t envision what it was going to be like. Everyone naturally feels that their way is unique and often don’t understand the other parts of the business. But change takes time. We had to create platforms for the teams to get together across the businesses to view the details because supply chain is very detail oriented. Supply chain professionals like to see the facts and to see how each other works in order to understand how valuable it would be for each of them to change the way they work to come together.”

              According to Dorsch it’s vital to bring the people along with you on the journey. “It can’t be top down. They need to understand why and they need to feel it. However now there are more and more asking for it. Now they’re asking for Maestro and Kinaxis, which is great.”

              Agility is key

              So, how has Maestro enhanced agility and resilience and efficiency at Syensqo? “Well, it’s going to help us with the transparency, primarily. We will now have the information at our fingertips to make decisions in real time. We’ll be able to pull more of our planning upstream. Constraints realised further upstream in the planning relieves the pressure of the plant floor where it’s quite busy. The plant floor will be much, much calmer I would say.”

              Maestro is also able to enhance the customer side too. “Our customers will certainly see a difference,” she reveals. “Our service levels will see a real improvement too. We’ll be making the right inventory and have it in the right place at the right time, ultimately improving business outcomes. Working capital and customer service will also improve.”

              The people

              A lot of what’s been happening at Kinexions is technologically rooted, but the power of people is also being stressed as vital in these major transformation projects. “Oh they are,” she affirms. “People are stressed. They need to feel protected. And the Kinaxis teams have done a very nice job of helping the teams feel supported by giving them examples of other companies that they’ve done this for. This lets them know it’s normal to feel stressed and to not be sure until you go live. However, you need to let them know that you’re there for them. The more examples they go through, the more comfortable the users feel. But it does take time.”

              Disruptive and volatile as these times are, at least a platform such as Maestro gives users the ability to meet some of these daily challenges. “Yeah, it certainly does. I mean, the way we’re able to handle resiliency currently is that people have to work a lot harder. But the way we’re going to be able to handle resiliency going forward, when we have challenges, is going to be completely different because we’ll have such better transparency in our ability to react and respond. We will definitely adjust our focus onto using AI to make the decisions. All the routine decisions will be automated through AI and AI agents.” 

              So, what would Dorsch say to those supply chain leaders who have yet to make the leap into harnessing emerging technologies? “I would say think about the people that are working in the supply chain and improve their quality of life. The more you give them to make their jobs easier, the less stress there is on them. Let the system take the stress, not the people. It’s a way to retain your top talent. I would turn it more in that direction. Not to mention the fact that you get to improve outcomes for customers, financial statements, all of that, but crucially for your employees too.”

              • Digital Supply Chain
              • Events
              • Together in Events

              Kinaxis, the supply chain orchestration platform developer, is leveraging agentic AI in both its world-renowned Maestro platform and beyond. SupplyChain Strategy sat down with Andrew Bell, Chief Product Officer at Kinaxis, to learn more…

              Kinaxis’ Maestro is billed as an AI orchestration platform that revolutionises how supply chain leaders handle and use their data. Built upon three fundamental principles – supply chain data fabric, an intelligence engine, and the user experience – it serves to ease the challenge of gleaning actionable insights from broad data sets, as well as automating processes that are reliant on understanding shifts in that data.

              Through AI, it’s a system that users can speak with: ask Maestro a question about your data, and it will give you an answer in real-time. The AI-powered system can also simulate an endless array of scenarios, massively enhancing supply chain leaders’ capacity to prepare for the future against a backdrop of regular and often-decisive volatility around the world. Keen to learn more about the ways in which the firm is leveraging agentic AI in both Maestro and beyond, SupplyChain Strategy sat down with Kinaxis’ Chief Product Officer, Andrew Bell, backstage at Kinexions 2025, to learn more.

              The three AI disciplines

              Before we get into the finer details, it’s important to understand what agentic AI is and where it sits in the growing family of AI-powered technologies poised to reshape the world. “For supply chain, our view is that there are three AI disciplines that are highly relevant to what we do,” explains Bell, fresh from delivering a fascinating keynote speech to the assembled global supply chain leaders gathered in Austin, on agentic AI. “The first was predictive AI with machine learning, the second, more recently, was generative AI. Continuing on from there would be agentic and autonomous AI.

              “It’s not about any one of those on their own,” Bell continues, “but rather how they come together to deliver. When I think about agentic AI, it comes down to what we demonstrated in conference: the ability to chat with your data, to ask questions about your data, to get it presented to you however you want, all based on simple prompts. It’s actually a fusion of generative and agentic AI. There’s the agent that we built that works autonomously based on prompts from users; prompts that are then interpreted by the generative side.”

              According to Bell, when it comes to agentic AI, the real differentiator is the notion that it operates on its own, that it operates autonomously as a result of a user prompt or data change conditions. “The idea is that it’s able to make its own decisions as it progresses through a problem; that’s what I find so powerful about it,” he enthuses. “That’s how it differentiates from other forms of automation.”

              The democratisation of data

              While concerns abound regarding the disruption AI could bring to workforces, namely in headcounts and the nature of their work, Bell stresses that this form of AI, as with the others, is at its best as an enabler rather than replacer. “The first thing to say is that AI on its own, especially in the supply chain space, is not going to solve our problems,” he explains. “It’s not going to deliver the value. Its real value is its democratisation of data access through the combination of the data with tools that have the ability to access and use that data, with AI sitting on top. Then I can get to my data more easily and more quickly, and so can anyone else approved to use the system.

              “Users don’t need to learn a system, they don’t need to know how to navigate complex worksheets, set up filters and all the things you do in a traditional context. It means anybody, whether that’s an entry-level planner or a C-level executive can ask data-based questions, run a scenario or a simulation or execute something with less friction. I see it as a democratisation of the power of data and as an accelerant.”

              That sense of democratisation extends beyond Kinaxis’ internal use and development of its agentic AI systems, with customers and partners joining the fold to inspire new and iterative action. “We’ve approached it by building an agentic framework first, and that allows for the creation of agents and the running and execution of agents,” Bell elaborates. “That’s step one. Now we’re building our own out-of-the-box agents on that framework, as well as opening that framework up to our customers so they can build their own agents.  Customers know their business best, and there might be use cases that they want to apply an agent to that we haven’t thought of yet. They’ll now have the ability to do that.

              “From there, we’re using our customers and the challenges they share with us to figure out what we can build or iterate upon next. We’ve started with the ‘chat with data’ agent. Because that was the number one thing: get me access to my data. The next thing is the ability to evaluate two options and execute a change. Merck, who we’re working with, shared an agent that essentially detects late supply and takes corrective action.”

              Bell is evangelical regarding the adaptability of its AI framework, allowing agents to be used in isolation, or strung together. “It’s purely going to be based on the natural language prompt from the customer,” he reveals. “The framework will know all the different agents I have access to and so it can either do what the user is asking with those agents or suggest a combination of those agents.”

              Data is the key

              Data is the crux that all AI roads lead to and stem from. Without high-quality data, AI isn’t capable of delivering on its potential. Creating robust frameworks, exercising high levels of data hygiene, and structuring data stores in an AI-ready fashion are paramount in both the development of agentic AI and the application of those tools. For both developers and users, Bell stresses the fundamental importance of getting that data piece right. He notes, too, that its applicable advice no matter where individuals and organisations are in their AI journey. “There is the ability to start from any position on that journey,” says Bell. “It doesn’t have to be a big bang or a one-size-fits-all. No matter what, though, it is about the data. The agents, the automation, whatever it might be, is only going to be as good as the data that it can access. 

              “Step one is to understand the problems you’re looking to solve and figure out which data that system would need. We have capabilities that simply do exception reporting where you can implement predefined automations where your team has said ‘these are some processes that we execute on a regular basis, and we have the data, so automate it’. You can then move up the journey and say, ‘No, we’re ready to implement agents and we’re going to start using some proven native ones before going all the way to making our own.’’

              “The good news is that some of the foundational requirements apply no matter where you start in the journey. Getting the data and having the right tools in place are going to benefit you across the whole journey. From Covid to more recent impediments to worldwide networks via trade war escalation, significant global interruptions and bottlenecks over the past several years have put enormous pressure on supply chains to adapt at pace. As far as disruptive influences go, agentic AI represents a welcome boon for those who can effectively wield its potential.”

              “At Kinexions 2025, we had a presentation from ExxonMobil that noted how people typically think about disruptions as a negative thing, but our job is to build a supply chain that excels at managing those disruptions,” says Bell. “When we do, we have a competitive advantage. Our job at Kinaxis is to provide the tools, systems and capabilities to deliver that competitive advantage to our customers. Disruptions are going to occur. That’s a given. We don’t know what they might be, but they’re going to happen. If we’ve given you the ability to manage them effectively, that’s going to give you a strong competitive advantage.”

              • Digital Supply Chain
              • Events
              • Together in Events

              SupplyChain Strategy descended upon Austin, Texas, to join the supply chain leaders keeping the world moving at Kinexions 2025.

              From agentic AI to a unified data foundation accelerated through its collaboration with Databricks, Kinaxis showed how it’s turning orchestration from aspiration to execution – with the speed and certainty today’s businesses demand. 

              Early morning and the sun was blazing outside the palatial Fairmont Hotel, in downtown Austin. Inside, there was a palpable excitement as a thousand attendees of Kinexions congregated for breakfast. We certainly felt honoured to be representing SupplyChain Strategy courtesy of Kinaxis. Kinaxis are the software gurus who have both transformed supply chain through their Maestro platform. They have also attracted the leading lights of the function from many of the world’s biggest companies. ExxonMobil, Eaton, Volvo Cars, Colgate-Palmolive, Merck & Co., General Motors, National Instruments, and Schneider Electric have all come to Texas.  

              Kinexions started as it meant to go on. The headline ‘A Revolution’ dominating the screens behind the huge, purple-tinted stage as the keynote speakers walked on to huge applause. Bob Courteau, Interim CEO, Kinaxis, Mark Morgan, President, Commercial Operations, Kinaxis and Andrew Bell, Chief Product Officer, Kinaxis kicked proceedings off with a blistering and inspirational set of presentations. The message was clear: true orchestration, meaning a fully connected, always aware, and-able-to act-instantly supply chain – is finally within reach. This places supply chains firmly at the table as strategic value creators and, crucially, as protectors of business. 

              It was a morning session that truly set the tone of this three-day event. Concerns raised by Kinaxis’ 45,000 global users – including tariffs, labour shortages, cyber-attacks and the effect of disruption on investment – were front and centre of this event with myriad symposiums, workshops and presentations that showcased how Kinaxis​​ Maestro can orchestrate and empower fully-connected supply chains globally. Indeed, the tariffs on imported goods into the US dropped during Kinexions and so the timing of this conference, entirely devoted to the bolstering of supply chain operations during highly uncertain times, seemed somewhat inspired. In short, those who are transforming are surviving and outperforming.  

              Unified data

              Kinaxis is transforming too, we were informed, as the new partnership with Databricks was unveiled. Kinaxis Maestro and Databricks’ Data Intelligence Platform have combined to power faster insights, unified data and scalable AI across global supply chains, enabling organisations to unify their data, accelerate AI adoption, and respond to change with speed and confidence. This collaboration meets growing demand for more agile, data-driven supply chains and strengthens Maestro’s supply chain data fabric. In short, this move is helping companies coalesce data from core systems like inventory and procurement, alongside external inputs such as meteorological patterns and market movement, all within one single source of governed truth, ripe for innovation. As supply chains continue to evolve, this collaboration positions both companies to lead the next era of AI-powered transformation, where decisions are faster, disruptions are less disruptive, and performance is driven by unified data. 

              Linked to the foundational collaboration between Kinaxis and Databricks was the second huge unveiling at Kinexions: agentic AI. Guests were shown just how easily they could create and deploy intelligent agents using an intuitive GenAI interface to enhance decision-making, respond to disruptions faster and optimise workflows, through a powerful, in-development feature of Maestro. These are agents that go beyond surfacing data to deliver real-time insights and perform actions ​like ​addressing exceptions, managing supply allocation, or adjusting safety stock. There were numerous workshops taking place over the three days where clients could get their hands on the new tools and see just how easily they could transform their supply chain operations through AI. As was stressed throughout Kinexions, this is something that is happening right now.  

              A community of innovation 

              Kinaxis places real value on keeping the dialogue open with its clients and that’s the core motivation behind Kinexions, North America and its APAC and EMEA sister events set to take place in Tokyo and Amsterdam later this year. Indeed, during our time in Austin, we were lucky enough to sit down with supply chain leaders from Sanofi, IBM, Qualcomm and Syensqo as well as leading lights from Kinaxis. You can read the interviews from those discussions, and more from Kinexions, in next month’s SCS

              The quality of the guest speakers during the three days was incredible. Staale Gjervik, President, Supply Chain, ExxonMobil discussed how the giant is bringing orchestration to its multinational supply chain, solidifying ExxonMobil’s position as ​a ​global leader by establishing an enterprise-wide global supply chain organisation. Elsewhere, Global Director of Strategy and Planning for GM, Vijay Bharadwaj and Director of Supply Chain, Alexander Heavin shared how they are now able to run a global S&OP process to better serve customers and “stay on the road to success”. 

              Diego Pantoja-Navajas, Managing Director, Enterprise AI Value Strategy at Accenture and Chris Reynolds, Senior Director, Digital Supply Chain Planning & Intelligence at Pfizer provided a thought-provoking discussion on how multi-agentic AI is transforming the pharmaceutical supply chain. Abhijit Pattewar, Senior Manager, Global Modelling & Network Design at Schneider Electric – the leader in sustainable energy management and digital automation – delivered an engaging talk on emerging techniques for reducing CO2 emissions without sacrificing efficiency or growth.  

              Paying it forward 

              One of the standout discussions at this year’s Kinexions was an inspiring lunch session hosted by Lizet Tymon, VP Supply Chain, Rehlko and Rozena Dendy, Global Sales & Operations Planning Leader, ExxonMobil designed to celebrate, empower, and connect women who are making a difference in their workplaces and communities. Candid stories of the moments when mentorship, support, and solidarity helped them break barriers and build bridges to success will resonate with the audience for years. Each participant wrote down one action they committed to taking to support another woman, as part of the Pay-It-Forward Commitment. “Let’s build a legacy of women helping women, together!” 

              One woman who has long been an inspiration is real estate mogul and business expert Barbara Corcoran who presented ‘How to build your business through troubled times and prosper’. Corcoran, currently a Shark on ABC’s hit reality show, Shark Tank, knows that bad times are the best times to move ahead. Indeed, she survived and prospered amid 18% interest rates, the bankruptcy of New York, the subprime mortgage crisis, and the tragedy of 9/11. In this session, Barbara shared “lessons from the trenches” to demonstrate her leadership methodology on how to adapt quickly, pivot, and turn every obstacle into the new opportunity it really wants to be. It’s an ethos she has certainly embodied through her career, evident in the establishment and success of The Corcoran Group, started with a mere $1,000 loan. 

              And the winner is… 

              The winners of the 2025 Kinaxis Customer Awards were also announced in Austin, further cementing links between Kinaxis and its community. “These awards honour companies and individuals pushing the boundaries of supply chain innovation, efficiency and sustainability.” 

              ExxonMobil, Sanofi, Schneider Electric, and British American Tobacco (BAT) were recognised for their excellence in supply chain transformation. Additionally, Hanu Gadila (Merck & Co.) received the Champion Award, and Jeffrey Jones (Qualcomm) was honoured with the Lifetime Achievement Award for their industry contributions. 

              2025 Kinaxis Customer Award Winners 

              • Pioneer Award: ExxonMobil 
                Recognising companies that have implemented Kinaxis within the past three years. 
                ExxonMobil is changing how the industry applies sales and operations planning. They’re leading the way in fuels, setting a new standard for Advance Planning Solution capabilities for the industry. 
              • Champion Award: Hanu Gadila, Merck & Co.  
                Honoring individuals demonstrating leadership, vision, and perseverance in supply chain transformation.  
                Hanu Gadila has enhanced Merck’s use of Kinaxis Maestro™, optimising planning capabilities and efficiency through collaboration and advocacy. 
              • Lifetime Achievement Award: Jeffrey Jones, Qualcomm  
                Recognising long-term contributions to the supply chain industry.  
                A steadfast Kinaxis advocate for nearly 20 years, Jeffrey Jones has championed Maestro, supporting industry-wide transformation. Jones stated, “It has been a privilege to work alongside such talented professionals and to contribute to the evolution of our industry. I look forward to continuing our journey of innovation.” 
              • Excellence Award: Sanofi  
                Awarded for measurable business impact through supply chain strategy.  
                Sanofi is modernising its supply chain to reach best-in-class performance for unleashing its ambition to become the world’s leading immunology company. By leveraging digitalisation and tailored Kinaxis Maestro implementations, Sanofi has enhanced agility, resilience, and efficiency, enabling faster decisions, better risk mitigation, and seamless end-to-end operations. 
              • Impact Award: Schneider Electric  
                Recognising positive environmental and social contributions.  
                Schneider Electric, the leader in sustainable energy management and digital automation, successfully conceptualised incorporating emerging CO2tools & techniques of Maestro for achieving growth and profitability with planet-friendly practices. 
              • Innovation Award: British American Tobacco (BAT)  
                Highlighting innovative applications of Kinaxis technology.  
                BAT co-developed the first-ever production wheel and interchangeability functionalities, enhancing constraint management, SKU transitions, and automation. 

              Parting thoughts 

              As a veteran to many events such as Kinexions, it was refreshing to feel a jolt of genuine excitement at an event that was showing how things can actually change today, rather than in the future. This wasn’t an exercise in hypothesis, it was a call to action. If you want to harness what AI can do in orchestrating your supply chains in these unpredictable times, then act. Now. 

              As the four floors of symposiums, workshops and speeches were wrapping up, there was no time for rest for the guests, as it was left to none-other than the three-time Grammy-award-winning and Austin-born, Nelly to finish things off to a rapturous reception from the crowd. Hot In Herre boomed around the room, Nelly spraying the crowd with water, as another highly successful Kinexions drew to a close. It was an event that will live long in the memory. And as we departed the hospitable Austin and the incredible team behind Kinexions, it was clear that we would have to return. 

              Kinexions 2025 is made possible by its platinum sponsors Accenture, Capgemini and Scott Sheldon; and gold sponsors 4flow, Genpact, Microsoft, Google Cloud and Spinnaker SCA. For more information about Kinexions, including Kinexions EMEA 2025 and Kinexions APAC 2025, please visit www.kinexions.com. 

              • Events
              • Host Perspectives

              N-SIDE VPs Amaury Jeandrain and Charlotte Tannier discuss their organisation’s partnership with Sanofi and look ahead to a brighter future.

              Transparency. Good partnerships need it to survive.

              For N-SIDE and Sanofi, it has been a key ingredient to what has made the partnership successful for the past eight years.

              Since late 2015, N-SIDE has established and built on a strategic partnership with France-based pharmaceutical company Sanofi, aimed at optimising the firm’s clinical trial supply chain. The partnership helped digitalise Sanofi’s clinical supply chain while driving greater performance and waste reduction.

              Harnessing efficiency

              N-SIDE is a global leader in increasing the efficiency of life sciences and energy industries by providing software and services that optimise the use of natural resources, facilitating the transition to a more sustainable world. Founded in 2000, N-SIDE has built deep industry knowledge and technical expertise to help global pharmaceutical and energy companies anticipate, adapt, and optimise their decisions. In the life sciences industry, N-SIDE reduces waste in clinical trials, leading to more efficient, faster, and more sustainable clinical trials.

              Amaury Jeandrain, Vice President Strategy of Life Sciences at N-SIDE, has witnessed first-hand the development of the partnership since he joined the company in January 2016. “Very quickly, the value of risk management and waste reduction was perceived internally and this partnership ended up growing to become one of our largest. Today, Sanofi is the company at the forefront of a lot of the innovation co-created with N-SIDE.”

              Amaury Jeandrain, Vice President Strategy of Life Sciences at N-SIDE

              Pharmaceutical companies of varying sizes use N-SIDE solutions to avoid supply chain bottlenecks in their clinical trials, decrease risks and waste, control costs, reduce time-to-market and speed up the launch of new trials. N-SIDE’s focus is on four key pillars to bring high levels of efficiency into Sanofi’s clinical supply chain: best-in-class supply chain, people, analytics and innovation.    

              Charlotte Tannier, Vice President of Life Sciences Services at N-SIDE, adds that the key differentiator is the transparency between her organisation and Sanofi. “We trust each other and know that we can be fully open with them,” she explains. “We like to build new things together and co-develop innovative solutions.”

              Charlotte Tannier, Vice President of Life Sciences Services at N-SIDE

              Teaming with Sanofi

              Having defined a clear route to success through the Sanofi partnership, Amaury is keen to point out that the relationship has acted as something of a catalyst for future business collaborations with other companies. “There are a lot of good practices that were initiated with Sanofi that now became a standard in our industry,” he discusses.

              Looking ahead, the future of the partnership looks bright and is showing no signs of slowing down. Charlotte explains that the next step is all about “integration.” “For the moment, we have multiple teams and departments that are using the N-SIDE solutions, and many other software are used as well within the organisation. The focus in the short term will be to enable a unified IT landscape and environment,” she reveals. “The objective will be to be fully integrated and to increase the impact of the data they own. Because we believe, with Sanofi, that the way forward is through data. We are also planning to help Sanofi leverage more of the data that we’re generating together to increase its impact.”

              As technology continues to evolve and organisations become even more digitally mature, partnerships built on transparency and trust will be in demand. N-SIDE and Sanofi already have that head start.

              Click here to read more about how Sanofi is driving data-driven performance, resilience, agility and operational excellence within the clinical supply chain.

              • Procurement Strategy

              Our cover story this month focuses on the work of Arianne Gallagher-Welcher. As the Executive Director for the USDA Digital…

              Our cover story this month focuses on the work of Arianne Gallagher-Welcher. As the Executive Director for the USDA Digital Service, in the Office of the OCIO, her team’s mission is to drive a tech transformation at the USDA. The goal is to better serve the American people across all of its 50 states.

              Welcome to the latest issue of Interface magazine!

              Welcome to a new year of possibility where technology meets business at the interface of change…

              Read the latest issue here!

              USDA: The People’s Agency

              “We knew that in order for us to deliver what we needed for our stakeholders, we needed to be flexible – and that has trickled down from our senior leaders.” Arianne Gallagher-Welcher, Executive Director for the USDA Digital Service reveals the strategic plan’s first goal. Above all, the aim is to deliver customer-centric IT so farmers, producers, and families can find dealing with USDA as easy as using an ATM.

              BCX: Delivering insights & intelligence across the Data & AI value chain

              We also sat down with Stefan Steffen, Executive Leader for Data Insights & Intelligence at BCX. He revealed how BCX is leveraging AI to strategically transform businesses and drive their growth. “Our commitment to leveraging data and AI to drive innovation harnesses the power of technology to unlock new opportunities, drive efficiency, and enhance competitiveness for our clients.”

              Momentum Multiply: A culture-driven digital transformation for wellness

              Multiply Inspire & Engage is a new offering from leading South African insurance provider Momentum Health Solutions. Furthermore, it is the first digital wellness rewards program in South Africa to balance mental health and physical health in pursuing holistic wellness. CIO, Ndibulele Mqoboli, discusses re-platforming, cloud migrations, and building a culture of ownership, responsibility, and continuous improvement.

              Clark County: Creating collaboration for the benefit of residents

              Navigating the world of local government can be a minefield of red tape, both for citizens and those working within it. Al Pitts, Deputy CIO of Clark County, talks to us about the organisation’s IT transformation. He explains why collaboration is key to support residents. “We have found our new Clark County – ‘Together for Better’ – is a great way to collaborate on new solutions.”

              Also in this issue, we hear from Alibaba’s European GM Jijay Shen on why digitalisation can be a driving force for SMEs. We learn how businesses can get cybersecurity right with KnowBe4 and analyse the rise of ‘The Mobility Society’.

              Enjoy the issue!

              Dan Brightmore, Editor

              • People & Culture

              Doug Laney is Innovation Fellow at West Monroe and a leading Data & Analytics strategist. We caught up with the author of Infonomics and Data Juice to talk tech and how companies can measure, manage and monetise to realise the potential of their data

              Our cover story explores the rise of data and information as an asset.

              Welcome to the latest issue of Interface magazine!

              Interface showcases leaders aiming to take advantage of data, particularly in a new world of AI technologies where it is the fuel…

              Read the latest issue here!

              How to monetise, manage and measure data as an asset

              Our cover star is pretty big in the world of analytics… We meet the guy who defined Big Data. Doug Laney is Innovation Fellow at West Monroe and a leading Data & Analytics strategist. We caught up with the author of Infonomics and Data Juice to talk tech and learn how companies can measure, manage and monetise to realise the potential of their information. In his first book Laney advised companies to stop being fixated on hindsight-oriented analytics. “It doesn’t actually move the needle on the business. In the stories I’ve compiled over the last decade, 98% have more to do with organisations using data to diagnose, predict, prescribe or automate something. It’s not about asking questions about what happened in the past.”

              Canvas Worldwide: A data-driven media business

              Continuing this month’s data theme, we also spoke with Alisa Ben, SVP, Head of Analytics at full-service media agency Canvas Worldwide. Data has transformed the organisation, and what its clients do. “We look holistically at the client’s business and sometimes the tools we have might be right for them, sometimes not. It’s more about helping our clients achieve their business outcomes.”

              TUI Musement: from digital transformation to digital pioneer

              At travel giant TUI, handling data effectively is paramount when communicating consistently and meaningfully with up to 25 million customers annually. David Garcia, CIO for TUI Musement, talks about the tech evolution driving the travel giant’s provision of experiences, transfers and tours. It’s a big part of its operational shift from local to global. “As a CIO, I’ve always been interested in how the tech innovations we drive can support the business and add value.”

              Hiscox: making cybersecurity more accessible

              Liz Banbury, CISO at Hiscox and president of (ISC)² London Chapter, talks to us about how cybersecurity can become a more accessible, realistic career path for almost anybody. “When I was at school, topics like computer science didn’t even exist,” Banbury explains. “In one of my first jobs, over in Hong Kong, we were still using a typewriter! A lot has changed. My key point here is that there’s a lot of cybersecurity professionals who are really good at their job. They are inspiring, and have come from all walks of life. Crucially, they don’t have a maths, computer science, or technological background at all. But they still make great cybersecurity professionals.

              Portland Community College: Risk vs Speed in Cybersecurity

              Reet Kaur, former Chief Information Security Officer at Portland Community College, discusses the organisation’s transition to the cloud amid a digital transformation journey. I don’t want to work with people who just say yes all the time. I want my ideas challenged to help forge the excellence in the security programmes I help build.”

              DBHDS: Cybersecurity in healthcare

              The Virginia Department of Behavioral Health and Developmental Services (DBHDS) exists to create ‘a life of possibilities for all Virginians’ and transform behavioural health. Its focus is on supporting people across the entire commonwealth. It helps them get the support they need in order to take wellness and recovery into their own hands. In an area like healthcare, sensitive information is all over the place, meaning cybersecurity is a priority – and this is where Glendon Schmitz, CISO at DBHDS, comes in. The security team exists to help the wider organisation achieve its objectives with data. We’re there to protect the business, not the other way around.”

              Also in this issue, we schedule the can’t miss tech events and get the lowdown on IoT security from the Mobile Ecosystem Forum.

              Enjoy the issue!

              Dan Brightmore, Editor

              Welcome to issue 42 of CPOstrategy!

              This month’s cover story sees us speak with Brad Veech, Head of Technology Procurement at Discover Financial Services.

              CPOstrategy - Procurement Magazine

              Having been a leader in procurement for more than 25 years, he has been responsible for over $2 billion in spend every year, negotiating software deals ranging from $75 to over $1.5 billion on a single deal. Don’t miss his exclusive insights where he tells us all about the vital importance of expertly procuring software and highlights the hidden pitfalls associated.

              “A lot of companies don’t have the resources to have technology procurement experts on staff,” Brad tells us. “I think as time goes on people and companies will realise that the technology portfolio and the spend in that portfolio is increasing so rapidly they have to find a way to manage it. Find a project that doesn’t have software in it. Everything has software embedded within it, so you’re going to have to have procurement experts that understand the unique contracts and negotiation tactics of technology.” 

              There are also features which include insights from the likes of Jake Kiernan, Manager at KPMG, Ashifa Jumani, Director of Procurement at TELUS and Shaz Khan, CEO and Co-Founder at Vroozi. 

              Enjoy the issue! 

              Mike Randall, CEO at Simply Asset Finance, discusses how to build a people-first strategy that enables growth.

              As the UK economy continues to balance on the edge of a recession, employee retention is quickly being pushed to the top of CEOs’ lists. Over the past couple of years, the job market has shifted dramatically with previously unheard terms such as ‘the great resignation’, ‘quiet quitting’ and ‘hybrid working’ becoming commonplace. People are rightly prioritising their working situation and job satisfaction levels, questioning whether they believe in the organisations they are committing so much time to.

              Consequently, there has been a power dynamic shift in favour of the workforce. Reportedly in the third quarter of 2022 businesses witnessed over 365,000 job-to-job resignations across the UK. In similar fashion, the phenomenon of ‘quiet quitting’ – doing the bare minimum required of a job – has become a growing concern but its rise is prompted by a growing number of employees feeling disengaged in their roles.

              Against this backdrop of a highly turbulent job market, and increasingly difficult macro-economic pressures, it’s vital for CEOs to prioritise a people-first strategy to ensure healthy growth for their business in 2023. Data from Deloitte has even revealed that experts believe how engaged a workforce feels can directly correlate to overall business output, with 93% of HR and business leaders in agreement that building a sense of belonging is crucial for organisational performance.

              Mike Randall, CEO at Simply Asset Finance

              However, creating the right environment and recruiting, maintaining and nurturing the right talent to ensure a people first approach can be daunting. With this in mind, here are four learnings CEOs might want to consider when approaching this challenge:

              1. Define your beliefs

              Before CEOs and founders can hope to attract the right talent, it is critical to first distil and translate the business vision into something that can be understood by employees. Put simply, this means defining the business’ beliefs.

              Some business leaders may already refer to this as an ‘employer brand’, and it can be key to not only securing better talent, but also saving a business money in the long-term. Data from LinkedIn for example, recently found that a strong employer brand can help to reduce employee turnover by as much as 28% and cost-per-hire by 50%. Defining these beliefs – or the tenets a business does and doesn’t stand for – is therefore the perfect exercise to put a vision onto paper, and clearly communicate it to its prospective talent.

              2. Build a solid culture

              Once these beliefs have been defined, they must be reflected, and built into a strong culture. A business’ beliefs should permeate through the whole organisation – from customer communications, to how staff are treated, to how leaders run the business. Culture should essentially be a representation of a business’ beliefs being put into practice.

              Building a strong culture in a business, however, is not solely about these beliefs but also extends into how employees are equipped with the tools they need to succeed. Companies that invest in learning and development for example, have been found to benefit from a 24% higher profit margin than those that don’t, according to the Association of Talent Development. Training and development should therefore be seen as a worthwhile and necessary investment that can solidify your culture and ensure profitability, not just an unavoidable cost.

              3. Invest in retention

              With research from Oxford Economics estimating the average turnover per employee earning £25,000 a year to be £30,000 plus, there is an evident cost to businesses that fail to invest in retention. Tackling this will mean regularly taking the time to truly understand what makes employees tick – and more specifically, understanding their motivations, attitudes, behaviours, strengths and weaknesses.

              As the past few years have evidenced, individuals are no longer deciding where they work solely based on salary, but are also thinking about employer values, flexibility, and benefits. To avoid employee churn, businesses should regularly take time to understand what drives their employees and implement retention strategies to address these drivers. Gathering and analysing employee data will play an important role here over the coming years, and should be built into a long-term strategy to optimise employee satisfaction.

              4. Build for the future

              A common challenge encountered by modern businesses and startups wanting to take a people first approach, can be their ability to stay committed to it. As a business grows in size and becomes successful, it can be all too easy to let external factors dictate its purpose and for it to lose sight of what it initially stood for. The reality is that when this happens, a business is in its most vulnerable state – as its beliefs become increasingly distant, and worse, employees no longer understand what it stands for.

              When creating a people-first strategy its therefore important to think long-term. If there are external factors that will potentially put this strategy at risk in future, it’s crucial to identify them, and put in practical steps to mitigate them where possible. The pandemic, for example, is a prime example of an external factor that interrupted the status quo of many businesses – disrupting employees, customers and operations in general. While they can be unpredictable in nature, having a plan to get through these times can help to get you back on track and reassure talent that a solution is in place.

              In this economic climate, defining beliefs, building a solid culture, and retention plan should be at the core of every business’ strategy. It’s only when these things are in place that a business can hope to attract and retain talented people that exude the same passion and values built into the heart of a business. As while a business’ growth may be defined by its leaders, it is delivered by its people who are putting that vision into practice.

              Mike Randall, CEO at Simply Asset Finance.

              Procurement is in a state of flux. Against a backdrop of economic uncertainty, the procurement landscape is volatile and requires…

              Procurement is in a state of flux.

              Against a backdrop of economic uncertainty, the procurement landscape is volatile and requires agility to navigate turbulent waters. But, despite significant disruption could there still be opportunity?

              Simon Whatson, Vice President of Efficio Consulting, is optimistic about the future of digital procurement and despite a challenging few years he is confident of a successful bounce back. He gives us the lowdown on the direction of travel for digital procurement in 2023. 

              As an executive with considerable experience in the space, we’d love to learn more about your background and how you ended up in procurement. Why was this the specialism for you and how did you get involved to begin with?

              Simon Whatson (SW): “I think the one-word answer of how I came into procurement was accidental. I studied maths at university, with a year in France, before I began looking for different roles to apply for.

              “Eventually, I was offered a position with a big plumbing and heating merchant with global operations. I worked in that supply chain team for two and a half years. Although it was called supply chain, a lot of the work was procurement, which involved negotiating with suppliers. It was after that stint there, that I discovered consulting and joined a boutique procurement consultancy. Now I am onto my third consultancy and I’m very happy here!

              “In terms of why I’ve stayed, one of the success factors in procurement is being able to work cross-functionally. Procurement doesn’t own any of the spending that it is responsible for helping to optimise. It must work with other functions and the spend owners. I quite like the people side of that, building relationships, almost selling internally to bring teams together. That really appeals to me and is a key reason why I’ve been very happy in procurement.”

              As we move into exploring procurement today in 2023. The space is filled with challenges and complexities. You only need to look at the last few years. Covid, war in Ukraine, inflation – how would you describe the world’s recent challenges and their effect on the industry and what do you feel CPOs and leaders can do to combat these issues?

              SW: “I would flip it around and say that these are not so much challenges but rather opportunities for procurement. When I started my career 18 years ago, procurement was often fighting to get a voice and there were complaints that procurement was not represented at the top table, but the war in Ukraine, inflation, COVID and ESG, these are things which are now on the C-suite agenda and procurement is ideally positioned to help companies face those challenges. If you think about COVID and the war in Ukraine, procurement is in a privileged position to help with this.

              “I see some procurement functions that prefer to do what they know, which focuses on the process and transactional side. However, there are also many forward-thinking CPOs and procurement professionals out there, that have really seized this opportunity of being on the C-suite agenda and drive the thinking and the solutions to some of these big challenges we’re seeing.”

              Although new technology in procurement has been around for well over a decade, digitalisation has become so much more of an important topic. How would you sum up where procurement and supply chain are in terms of digital transformation today?

              SW: “It’s a bit laggard, but digital transformation is difficult, and we have to recognise there are some real trailblazers. There are some firms doing some fantastic things in digital to produce better outcomes. If you contrast your experience when you’re buying something in your private life, it’s much easier than 20 years ago. You can get access to a wealth of pre-sourced things, whether it’s food, a holiday, a car, or a book. You can see reviews of what other people think of these things.

              “But when you go into your workplace as a business user and you want to buy something, it doesn’t quite work like that yet. You often have to fill in a form, send it off and wait for them to come back to you. They might come back a little bit later than you were hoping and might tell you that they don’t have that part on the supply frameworks. I think people sometimes get confused about how it can be so easy to buy something as large as a car or a holiday on their sofa at home, but when they want to buy something at work, it seems to be quite cumbersome. Digital can help a lot with that, but it is incumbent on organisations and procurement functions to figure out how to recreate that customer experience that we’ve become accustomed to in our private lives.”

              With a new generation of leaders growing up with technology, some might say that it could be a key driver in helping to speed the adoption in procurement along. Is this something you would agree with or what would you point to as a key driver?

              SW: “I do think that it will act as one of the catalysts for further digital transformation in organisations, because if procurement doesn’t manage to recreate that customer experience that the new generation expects, then they won’t use procurement going forward and will look to bypass it.

              “The analogy that I’ve used previously in this case is one of travel agents. I remember as a child, my parents were able to take us on holiday and I remember the whole process. We would walk into town to the travel agent, and look at some of the brochures of options. They often then had to phone the various airlines or resorts on our behalf. They might not be able to get through, so we’d have to come back the next day. I remember as a child being quite excited by the whole process but actually, thinking back, it was quite cumbersome. You compare that to now, with being able to review online, and you can get instant answers to your questions. It’s not a coincidence that travel agents don’t really exist anymore.”

              How much of a challenge is it to not get caught leveraging technology for technologies sake? How important is it to stay true to your approach and be strategic?

              SW: “We conducted a study of many procurement leaders and CPOs a few years ago, and one of the things that we found was that about 50% of procurement leaders admitted to having bought technology just on the basis of a fear of missing out, without any real understanding of the benefits that technology was going to bring. That was a real shock and a revealing find because technology is not cheap, and its implementation is quite disruptive. If you’re purchasing a system because everybody else is using it, then there could be some pretty costly mistakes. It is really important to make sure that when buying technology, it is because the benefits are fully understood.

              “My advice to companies when looking to digitalise is own your data, visualise that data, and manage your knowledge. If you can focus on getting those things right in that order, and make your technology decisions to support that goal, then that’s a much better way of thinking about it rather than just jumping in and buying a piece of technology.”

              It’s clear that the procurement space is an exciting, but challenging, place to be. What do you think will play a key role in the next 12 months to push the digital conversation further to take procurement to the next level?

              SW: “Looking forward, one thing that procurement needs to do and continue to do is attract the best people. Ultimately, people are what makes an organisation, and it is what makes a function successful. I think procurement has often not looked for the right skills in the people that it employs. Traditionally, it’s looked for people with procurement experience and while they are valuable and required, we also need leadership potential. People who think a bit more outside the box and aren’t so process driven. A lot of what procurement has done in previous years has been process driven, so if you’re just limiting your search of people to those that have had procurement experience, you’re inevitably going to end up with a lot of people who are process driven.

              “I think being bolder and recruiting people from different backgrounds with different skill sets is the way to go. If procurement can ‘own’ the ESG space, that will help with the younger generation see procurement make a difference. I think that’s one thing that will be key to success going forward.”

              Check out the latest issue of CPOstrategy Magazine here.

              Paul Farrow, Vice President of Hilton Hotels’ Supply Management, sits down with us to discuss how his organisation’s procurement function has evolved amid disruption on a global scale

              The hospitality industry has endured a rough ride over the past few years.

              Following the COVID-19 pandemic which stopped the world in its tracks and now with millions facing a cost-of-living crisis, it’s been a period of unprecedented disruption for those involved in the space and beyond.

              But it’s a challenge met head-on by Paul Farrow, Vice President of Supply Management at Hilton Hotels, and his team who have been forced to respond as the world continues to shift before their eyes.

              Farrow gives us a closer look into the inner workings of his firm’s procurement function and how he has led the charge during his time with Hilton Hotels.

              Could we start with you introducing yourself and talking a little about your role at Hilton Hotels? 

              Paul Farrow (PF): “I’m the Vice President of Hilton’s Supply Management, or HSM as we call it. I’ve been with Hilton Hotels for 12 and a half years, and my role is to head the supply chain function for our hotels across Europe, the Middle East and Africa.

              “Over the past few years, Hilton has grown rapidly and has now got 7,000 hotels in over 125 countries globally. What is really exciting is Hilton Supply Management doesn’t just supply Hilton Hotels and the Hilton Engine because we also now supply our franchisees and competitive flags. While we have 7,000 hotels globally, Hilton Supply Management actually supplies close to 13,000 hotels. That’s an interesting business development for us, and a profit earner too.”

              You’re greatly experienced, I bet you’ve seen supply chain management and procurement change a lot in recent years? 

              PF: “The past two to three years have been tremendously challenging on so many industries but I’d argue that hospitality got hit more than most as a result of the Covid pandemic. Here at Hilton, supply management was really important just to keep the business operational throughout that tough time, but I’m delighted to say we’re fully recovered now.

              “Looking back, it was undoubtedly difficult, and you only have to look at the media to see that we’re now going through a period of truly unprecedented inflation. On top of the normal day job, it’s certainly been a very busy time.”

              Hospitality must have been under an awful lot of pressure during the pandemic… 

              PF: “Most of our teams as a business and all functions have worked together far more collaboratively than ever before through the use of technology and things like Microsoft Teams and Zoom. Trying to work remotely as effectively as possible changed the way we all had to think and the way we had to do. Now we’re back in the workplace and in our offices, we’re actually looking to take advantage of that new approach.”

              Inflation, rising costs, energy shortages, as well as drives towards a circular economy means it’s quite a challenging time for CSCOs and CPOs right now, isn’t it?

              PF: “Those headwinds have caused and created challenges of the like that we’ve not seen before. The war in Ukraine and Russia has meant significant supply chain disruption and supply shortages of some key ingredients and raw materials. China is a significant source of materials and they’re still having real challenges to get their production to keep up with demand.

              “All the local and short-term challenges are around energy and fuel pricing, so throughout the supply chain that’s been a major factor to what we’ve had to deal with. On top of that is the labour shortages. We rely heavily throughout the supply chain and within our business to utilise labour from around the world. In my region, particularly from say Eastern Europe as well as other businesses all fighting for a smaller labour pool than we had before. We are fighting with the likes of the supermarkets, Amazon’s, not just other hotel companies to capture the labour pool we need both in our properties but also within our supply chain supplies themselves.

              Hilton operates a rather unique procurement function, doesn’t it?  

              PF: “We trade off the Hilton name because our brand strength is something that we are able to utilise and we’re very proud of, but we’ve also got additional leverage by having that group procurement model.

              “We’ve got essentially two clients. We’ve got our managed estate which is when an owner chooses to partner with Hilton, they’re signing a management agreement because they want the benefit and value of the Hilton engine. That could be revenue management, how we manage onboarding clients and customers through advertising, as well as the other support we give in terms of finance, HR, marketing and sales as well as procurement.”

              HSM is a profit centre and revenue driver through its group procurement model but how does this work?

              PF: “Our secret sauce is our culture. It’s our people and that filters across all of our team members and indeed all of our functions. The key strategic pillars are the same for health and supply management around culture, maximising performance and so on as they are across the overall global business.

              “Across our 7,000 plus hotels, the majority are actually franchised hotels because that’s the legacy of what still is the model in the US. When I joined Hilton 12 and a half years ago, the reverse is true where nearly all of our hotels in Europe, Middle East and Africa, and indeed in Asia Pacific, were and are managed. In the Europe, Middle East and Africa regions right now we’re building up close to a 50/50 split between managed, leased and franchised.”

              What has pleased you most about the roll-out of the HSM?

              PF: “It’s certainly not been easy because we’ve got 70 countries that sit within our region here in EMEA and Hilton’s penetration in those individual countries is very different. We may have 100 hotels in one of those markets and only one or two in specific countries. Our scale and our ability to get logistics solutions is different by market.

              “Getting everyone on board to what we want to achieve to our guests and to our owners means we have to pull different levers. We have very effective brand standards. If you’re signing up to Hilton, you’re signing up to delivering against those brand standards that we believe are right for our organisation.”

              What kind of feedback have you had from your clients? 

              PF: “Integrity is in our DNA, and we work very closely with our suppliers who we value as partners. These are long-term relationships, and we work hand in hand because we have to see that they’re successful so that we can be successful – it’s really important to what we do and we constantly look for feedback.

              “With our internal and our external customers, we’ll have quarterly business reviews and so we’ll get that feedback through surveys where we are asking them to tell us what we do well and what we could do better. Our partners are now asking what additional value can you do to bring support to our organisation through ESG? So that’s what’s on the table now when it wasn’t before. But it’s not just that – it’s about the security of supply competitiveness, competitiveness of pricing, and a whole bunch of other very important things as well.”

              Looking to the future, what’s on the agenda for the next few years?

              PF: “We’re out there meeting and greeting people in person and there’s always new opportunities that make things exciting in what we do and how we work. Innovation’s very high on our agenda and we’re very proud of what we do in food and beverage. In non-food categories, it’s about how we support our owners and our hotel general managers to find that competitive edge and do the next big thing ahead of our competitors.”

              Anything else important to know?

              PF: “One thing we’ve been able to take full advantage of is how we’ve been able to grow our business by bolting on new customers. I think it’s fantastic that our competitors choose to use Hilton Supply Management because they benchmarked what our capabilities are and how competitive we are.

              “Another key part of the agenda is environmental, social and governance (ESG) sustainability. Responsible sourcing and everything that sits within that is front and centre of what we do. Within that you’ve got human rights, animal welfare, single use plastics as well as general responsible sourcing like managing food waste. The list is very long, but they’re all very important.”

              Check out the latest issue of CPOstrategy Magazine here.

              Here are 10 of the most important leadership skills that CEOs need to demonstrate in 2023.

              In today’s world, a CEO needs to be lots of things to different people. The importance of having the leadership skill to being able to lead through unprecedented disruption was highlighted by the COVID-19 pandemic and helped to define what makes a good CEO.

              Here are 10 of the most important leadership skills that CEOs need to demonstrate in 2023.


              1. Clear communication

              Communicating effectively with employees is one of the most vital skills any leader can have. By adopting a transparent mindset, it leaves little room for miscommunication or misunderstandings. But rather than just being eloquent, CEOs should deliver meaningful content too. A CEO needs to be able to communicate the essence of the business strategy and the methodology for achieving it.

              2. Strong talent management strategy

              People are the most important component of all businesses. CEOs who are able to recruit and retain key employees have a greater chance of increasing productivity and efficiency. After recruiting good people, the key to retaining them is by harnessing a positive work environment that empowers employees to succeed.

              3. Decision-making

              As a leader, thinking strategically to make effective decisions is vital to the success of an organisation. Making decisions is a key part of leadership as well as having the conviction to stand by decisions or agility to adapt when those decisions don’t have the required outcome. While all decisions might not be favourable, making unpopular but necessary calls are important characteristics of a good leader.

              4. Negotiation

              Negotiation is a fundamental part of being a CEO. In a top leadership position, almost every business conversation will be a negotiation. Good negotiations are important to an organisation because they will ultimately result in better relationships, both with staff inside the company and externally. An effective leader will also help find the best long-term solution by finding the right balance and offering value where both parties feel like they ‘win’.

              5. Creativity and innovation

              Being quick-thinking and ready to explore new options are great skills of a CEO. Creative leadership can lead to finding innovative solutions in the face of challenging and changing situations. It means in the midst of disruption, of which it has been increasingly prevalent, leaders can still find answers for their teams. Creative CEOs are those who take risks and empower employees to drop outdated and overused practices to innovate and try new things that could lead to greater efficiency.

              6. Agility

              Without agility over the past few years, businesses would have failed. CEOs were forced to embrace remote working following the advent of the COVID-19 pandemic whether they liked it or not. Now, faced against a potential recession, these macroeconomic events are unavoidable and have to be managed carefully. Effective leaders will have their fingers on the pulse and ready to respond to changes.

              7. Strategic forecasting

              Creating a clear path forward is essential to achieving uninterrupted success. The ability to look into the future and identify trends and issues to then react to is vital. Good CEOs are able to plan strategically and make informed decisions to set goals and plan for the future easily.

              8. Delegation

              CEOs can’t do everything. A leader tends to be pulled in a number of different ways every day and it is impossible to be on top of everything. This means the importance of bringing in a team of people who are trusted and skilled in their respective areas of expertise. Successful CEOs are expert delegators because they recognise the value of teamwork and elevating those around them.

              9. Approachability

              An approachable CEO who welcomes conversation and is an active listener will help employees feel at ease raising issues or concerns. This approach will help build strong relationships with staff and customers and encourage a healthy culture which is beneficial to employee retention. Leaders with strong, trusting and authentic relationships with their teams know that investing time in building these bonds which makes them more effective as a leader and creates a foundation for success.

              10. Growth mindset

              If a CEO arms themselves with a growth mindset it allows them to meet challenges head-on and evolve. This shines a light on improving through effort, learning and persistence. As others may back down in the face of adversity and upheaval, successful CEOs will strive to move forward with confidence. Those with a growth mindset are unlikely to be swayed as they have the tools needed to reframe challenges as opportunities to grow.

              In McKinsey’s latest report ‘Actions the best CEOs are taking in 2023’, we examine three of the biggest trends on the c-level agenda

              Anyone can sail a ship when things are going well. But it takes a strong, robust and characterful CEO to steer a business through choppy waters and out the other side.

              In McKinsey’s latest report ‘Actions the best CEOs are taking in 2023’, the research and advisory firm uncovered which trends are set to have the biggest impact on how CEOs lead their business throughout the year.

              McKinsey’s CEO Excellence Survey surveyed 200 of the best corporate CEOs of the past 15 years. This was completed by whittling down a list of all the current and former CEOs of the 1,000 largest public companies during that timeframe. The list was subsequently filtered based on tenure, including only those who had completed at least six years in the role. From there, the CEOs were continuously shortlisted until the best 200 were determined.

              Each CEO was asked to identify the top three trends that are set to determine how leaders tackle the future. Here is an insight into those findings.

              1. Actions to deal with digital disruption

              CEOs are targeting digital trends in three key ways: developing advanced analytics, enhancing cybersecurity and automating work. OpenAI’s launch of ChatGPT has accelerated the demand of companies looking to embrace advanced analytics for a competitive advantage. Improving cybersecurity is another key action for CEOs with the importance of guarding against external threats paramount amid strengthening and more mature cyberattacks. Lastly, automating work is another key priority to scale efficiency and eliminate boring and manual tasks which free up people’s time.

              2. Actions to deal with the risk of high inflation and economic downturn

              One CEO who is worried about economic uncertainty told McKinsey: “Act early to lower costs and protect the balance sheet so that you are stronger and leaner when the economy begins to turn more favourably.” McKinsey found that companies that outperformed the 2008 financial crisis cut operating costs by 1% before the downturn while the others expanded costs by the same percentage. The best performers reduced their debt by $1 for every $1 of book capital before the downturn. This can be done by reducing operating expenses, redesigning products and services as well as reassessing strategic and economic assumptions.

              3. Actions to deal with the escalation of geopolitical risk

              According to McKinsey, there are three actions to help manage the escalation of global and national crises. CEOs are targeting building robust compliance capabilities, creating resilience in supplier networks and investing in monitoring and response capabilities. These actions come following the challenges presented by COVID-19, the war in Ukraine and now inflation concerns. Many firms are choosing to build their trade compliance organisations and improve how they screen different customers and companies. While a defensive approach is the way forward for many, some companies see the turbulent times as an opportunity.

              What does today’s CEO need to do to accelerate an organisation’s digital transformation journey?

              Digital transformation journeys are no one-size-suits-all. There is no singular way to welcome a new wave of technology into operations.

              Since the turn of the century, digitalisation has had an increasingly influential impact on the way CEOs make decisions. Today’s world is full of disruption and potential risk. And with technology growing in complexity it can be challenging to lead such a revolution against a backdrop of economic uncertainty.

              Embracing digital

              According to KPMG 2022 CEO Outlook, which draws on the perspectives of 1,325 global CEOs across 11 markets, 72% of CEOs agree they have an aggressive digital investment strategy intended to secure first-mover or fast-follower status.

              Advancing digitalisation and connectivity across the business is tied (along with attracting and retaining talent) as the top operational priority to achieve growth over the next three years. This digital transformation focus could be driven as a result of increasingly flexible working conditions and greater focus on cybersecurity threats.

              However, the prospect of recession is threatening to halt digital transformation in the short-term. KPMG research found that four out of five CEOs note their businesses are pausing or reducing their digital transformation strategies to prepare for the anticipated recession.

              This is reinforced further when 70% say they need to be quicker to shift investment to digital opportunities and divest in those areas where they face digital obsolescence.

              When a company’s digital transformation ambition is mismatched to its readiness, it is the CEO’s responsibility to close the gap. According to Deloitte, in order to do this successfully, the CEO must assess the current level of organisational readiness for change.

              This covers four key pillars that are mixed together to work out an organisation’s overall readiness: leadership, culture, structure and capabilities.

              How CEOs can close the gap

              Leadership: CEOs need to ensure their c-suite and other key executives are motivated and equipped to execute the vision. CEOs interviewed by Deloitte in a recent study emphasised the importance of the leadership team supporting the transformation vision and having a positive attitude and willingness to transform.

              Culture: A large potential barrier to readiness in the organisation is down to culture. Low cultural readiness takes the form of bureaucratic, reactive and risk-averse ways of working that are at against the collaborative, proactive learning mindset needed for ambitious transformation.

              Structure: If a company hopes to operate differently, it could mean the need for organising in an alternative way. CEOs will often need to lead the reorganisation of teams, assignment of new roles, revision of incentives, strategies to collapse organisational hierarchies or layers to increase agility.

              Capabilities: CEOs need to equip their organisation with four key capabilities to harness digital for a superior capacity for change. These are nimbleness, scalability, stability and optionality which are often enabled or supercharged by digital technologies which are critical factors for competing in an increasingly disrupted world.

              For now, one of the CEOs most important roles when steering the ship through disruption is to be ahead of the latest trends and tackle change head-on. By embracing a new digital future that will provide the company with long-lasting benefits, it will help create a brighter and future-proofed firm for years to come even after the CEO is gone.

              Expert analysis of the tech trends set to make waves this year

              Digital transformation is a continuing journey of change with no set final destination. This makes predicting tomorrow a challenge when no one has a crystal ball to hand.

              After a difficult few years for most businesses following a disruptive pandemic and now battling a cost-of-living crisis, many enterprises are increasingly leveraging new types of technology to gain an edge in a disruptive world. 

              With this in mind, here are what experts predict for the next 12 months…


              1. Process Mining


              Sam Attias, Director of Product Marketing at Celonis

              Sam Attias, Director of Product Marketing at Celonis, expects to see a rise in the adoption of process mining as it evolves to incorporate automation capabilities. He says process mining has traditionally been “a data science done in isolation” which helps companies identify hidden inefficiencies by extracting data and visually representing it.

              “It is now evolving to become more prescriptive than descriptive and will empower businesses to simulate new methods and processes in order to estimate success and error rates, as well as recommend actions before issues actually occur,” says Attias. “It will fix inefficiencies in real-time through automation and execution management.”


              2. The evolution of social robots


              Gabriel Aguiar Noury, Robotics Product Manager at Canonical

              Gabriel Aguiar Noury, Robotics Product Manager at Canonical, anticipates social robots to return this year. After companies such as Sony introduced robots like Poiq, Aguiar Noury believes it “sets the stage” for a new wave of social robots. 

              “Powered by natural language generation models like GPT-3, robots can create new dialogue systems,” he says. “This will improve the robot’s interactivity with humans, allowing robots to answer any question. 

              3d rendering cute artificial intelligence robot with empty note

              “Social robots will also build narratives and rich personalities, making interaction with users more meaningful. GPT-3 also powers Dall-E, an image generator. Combined, these types of technologies will enable robots not only to tell but show dynamic stories.”


              3. The rebirth of new data-powered business applications


              In today’s fast-moving world, technology doesn’t sleep. Through the help of experts, we’ve compiled a need-to-know list of 23 predictions for 2023

              Christian Kleinerman, Senior Vice President of Product at Snowflake, says there is the beginning of a “renaissance” in software development. He believes developers will bring their applications to central combined sources of data instead of the “traditional approach” of copying data into applications. 

              “Every single application category, whether it’s horizontal or specific to an industry vertical, will be reinvented by the emergence of new data-powered applications,” affirms Kleinerman. “This rise of data-powered applications will represent massive opportunities for all different types of developers, whether they’re working on a brand-new idea for an application and a business based on that app, or they’re looking for how to expand their existing software operations.”


              4. Application development will become a two-way conversation


              Adrien Treuille, Head of Streamlit at Snowflake

              Adrien Treuille, Head of Streamlit at Snowflake, believes application development will become a two-way conversation between producers and consumers. It is his belief that the advent of easy-to-use low-code or no-code platforms are already “simplifying the building” and sharing of interactive applications for tech-savvy and business users. 

              “Based on that foundation, the next emerging shift will be a blurring of the lines between two previously distinct roles — the application producer and the consumer of that software.”

              He adds that application development will become a collaborative workflow where consumers can weigh in on the work producers are doing in real-time. “Taking this one step further, we’re heading towards a future where app development platforms have mechanisms to gather app requirements from consumers before the producer has even started creating that software.”


              5. The Metaverse


              Paul Hardy, EMEA Innovation Officer at ServiceNow

              Paul Hardy, EMEA Innovation Officer at ServiceNow, says he expects business leaders to adopt technologies such as the metaverse in 2023. The aim of this is to help cultivate and maintain employee engagement as businesses continue working in hybrid environments, in an increasingly challenging macro environment.

              “Given the current economic climate, adoption of the metaverse may be slow, but in the future, a network of 3D virtual worlds will be used to foster meaningful social connections, creating new experiences for employees and reinforcing positive culture within organisations,” he says. “Hybrid work has made employee engagement more challenging, as it can be difficult to communicate when employees are not together in the same room. 

              “Leaders have begun to see the benefit of hosting traditional training and development sessions using VR and AI-enhanced coaching. In the next few years, we will see more workplaces go a step beyond this, for example, offering employees the chance to earn recognition in the form of tokens they can spend in the real or virtual world, gamifying the experience.”


              6. The year of ESG?


              Cathy Mauzaize, Vice President, EMEA South, at ServiceNow

              Cathy Mauzaize, Vice President, EMEA South, at ServiceNow, believes 2023 could be the year that environmental, social and corporate governance (ESG) is vital to every company’s strategy.

              “Failure to engage appropriate investment in ESG strategies could plunge any organisation into a crisis,” she says. “Legislation must be respected and so must the expectations of employees, investors and your ecosystem of partners and customers.

              “ESG is not just a tick box, one and done, it’s a new way of business that will see us through 2023 and beyond.”


              7. Macro Trends and Redeploying Budgets for Efficiency


              Ulrik Nehammer, President, EMEA at ServiceNow, says organisations are facing an incredibly complex and volatile macro environment. Nehammer explains as the world is gripped by soaring inflation, intelligent digital investments can be a huge deflationary force.

              “Business leaders are already shifting investment focus to technologies that will deliver outcomes faster,” he says. “Going into 2023, technology will become increasingly central to business success – in fact, 95% of CEOs are already pursuing a digital-first strategy according to IDC’s CEO survey, as digital companies deliver revenue growth far faster than non-digital ones.”  


              8. Organisations will have adopted a NaaS strategy


              David Hughes, Aruba’s Chief Product and Technology Officer

              David Hughes, Aruba’s Chief Product and Technology Officer, believes that by the end of 2023, 20% of organisations will have adopted a network-as-a-service (NaaS) strategy.

              “With tightening economic conditions, IT requires flexibility in how network infrastructure is acquired, deployed, and operated to enable network teams to deliver business outcomes rather than just managing devices,” he says. “Migration to a NaaS framework enables IT to accelerate network modernisation yet stay within budget, IT resource, and schedule constraints. 

              “In addition, adopting a NaaS strategy will help organisations meet sustainability objectives since leading NaaS suppliers have adopted carbon-neutral and recycling manufacturing strategies.”


              9. Think like a seasonal business


              According to Patrick Bossman, Product Manager at MariaDB corporation, he anticipates 2023 to be the year that the ability to “scale out on command” is going to be at the fore of companies’ thoughts.

              “Organisations will need the infrastructure in place to grow on command and scale back once demand lowers,” he says. “The winners in 2023 will be those who understand that all business is seasonal, and all companies need to be ready for fluctuating demand.”


              10. Digital platforms need to adapt to avoid falling victim to subscription fatigue


              Demed L’Her, Chief Technology Officer at DigitalRoute

              Demed L’Her, Chief Technology Officer at DigitalRoute, suggests what the subscription market is going to look like in 2023 and how businesses can avoid falling victim to ‘subscription fatigue’.  L’Her says there has been a significant drop in demand since the pandemic.

              “Insider’s latest research shows that as of August, nearly a third (30%) of people reported cancelling an online subscription service in the past six months,” he reveals. “This is largely due to the rising cost of living experienced globally that is leaving households with reduced budgets for luxuries like digital subscriptions. Despite this, the subscription market is far from dead, with most people retaining some despite tightened budgets. 

              “However, considering the ongoing economic challenges, businesses need to consider adapting if they are to be retained by customers in the long term. The key to this is ensuring that the product adds value to the life of the customer.”


              11. Waking up to browser security 


              Jonathan Lee, Senior Product Manager at Menlo Security

              Jonathan Lee, Senior Product Manager at Menlo Security, points to the web browser being the biggest attack surface and suggests the industry is “waking up” to the fact of where people spend the most time.

              “Vendors are now looking at ways to add security controls directly inside the browser,” explains Lee. “Traditionally, this was done either as a separate endpoint agent or at the network edge, using a firewall or secure web gateway. The big players, Google and Microsoft, are also in on the act, providing built-in controls inside Chrome and Edge to secure at a browser level rather than the network edge. 

              “But browser attacks are increasing, with attackers exploiting new and old vulnerabilities, and developing new attack methods like HTML Smuggling. Remote browser isolation is becoming one of the key principles of Zero Trust security where no device or user – not even the browser – can be trusted.”


              12. The year of quantum-readiness


              Tim Callan, Chief Experience Officer at Sectigo

              Tim Callan, Chief Experience Officer at Sectigo, predicts that 2023 will be the year of quantum-readiness. He believes that as a result of the standardisation of new quantum-safe algorithms expected to be in place by 2024, this year will be a year of action for government bodies, technology vendors, and enterprise IT leaders to prepare for the deployment.

              “In 2022, the US National Institute of Standards and Technologies (NIST) selected a set of post-quantum algorithms for the industry to standardise on as we move toward our quantum-safe future,” says Callan.

              “In 2023, standards bodies like the IETF and many others must work to incorporate these algorithms into their own guidelines to enable secure functional interoperability across broad sets of software, hardware, and digital services. Providers of these hardware, software, and service products must follow the relevant guidelines as they are developed and begin preparing their technology, manufacturing, delivery, and service models to accommodate updated standards and the new algorithms.” 


              13. AI: fewer keywords, greater understanding


              AI expert Dr Pieter Buteneers, Director of AI and Machine Learning at Sinch

              AI expert Dr Pieter Buteneers, Director of AI and Machine Learning at Sinch, expects artificial intelligence to continue to transition away from keywords and move towards an increased level of understanding.

              “Language-agnostic AI, already existent within certain AI and chatbot platforms, will understand hundreds of languages — and even interchange them within a single search or conversation — because it’s not learning language like you or I would,” he says. “This advanced AI instead focuses on meaning, and attaches code to words accordingly, so language is more of a finishing touch than the crux of a conversation or search query. 

              “Language-agnostic AI will power stronger search results — both from external (the internet) and internal (a company database) sources — and less robotic chatbot conversations, enabling companies to lean on automation to reduce resources and strain on staff and truly trust their AI.”


              14. Rise in digital twin technology in the enterprise


              John Hill, CEO and Founder of Silico

              John Hill, CEO and Founder of Silico, recognises the growing influence digital twin technology is having in the market. Hill predicts that in the next 20 years, there will be a digital twin of every complex enterprise in the world and anticipates the next generation of decision-makers will routinely use forward-looking simulations and scenario analytics to plan and optimise their business outcomes.

              “Digital twin technology is one of the fastest-growing facets of industry 4.0 and while we’re still at the dawn of digital twin technology,” he explains. “Digital twins will have huge implications for unlocking our ability to plan and manage the complex organisations so crucial for our continued economic progress and underpin the next generation of Intelligent Enterprise Automation.”


              15. Broader tech security


              Tricentis CEO, Kevin Thompson

              With an exponential amount of data at companies’ fingertips, Tricentis CEO, Kevin Thompson says the need for investment in secure solutions is paramount.

              “The general public has become more aware of the access companies have to their personal data, leading to the impending end of third-party cookies, and other similar restrictions on data sharing,” he explains. “However, security issues still persist. The persisting influx of new data across channels and servers introduces greater risk of infiltration by bad actors, especially for enterprise software organisations that have applications in need of consistent testing and updates. The potential for damage increases as iterations are being made with the expanding attack surface. 

              “Now, the reality is a matter of when, not if, your organisation will be the target of an attack. To combat this rising security concern, organisations will need to integrate security within the development process from the very beginning. Integrating security and compliance testing at the upfront will greatly reduce risk and prevent disruptions.”


              16. Increased cyber resilience 


              Michael Adams, CISO at Zoom

              Michael Adams, CISO at Zoom, expects an increased focus on cyber resilience over the next 12 months. “While protecting organisations against cyber threats will always be a core focus area for security programs, we can expect an increased focus on cyber resilience, which expands beyond protection to include recovery and continuity in the event of a cyber incident,” explains Adams.

              “It’s not only investing resources in protecting against cyber threats; it’s investing in the people, processes, and technology to mitigate impact and continue operations in the event of a cyber incident.” 


              17. Ransomware threats


              Michal Salat, Threat Intelligence Director at Avast

              As data leaks become increasingly common place in the industry, companies face a very real threat of ransomware. Michal Salat, Threat Intelligence Director at Avast, believes the time is now for businesses to protect themselves or face recovery fees costing millions of dollars.

              “Ransomware attacks themselves are already an individual’s and businesses’ nightmare. This year, we saw cybergangs threatening to publicly publish their targets’ data if a ransom isn’t paid, and we expect this trend to only grow in 2023,” says Salat. “This puts people’s personal memories at risk and poses a double risk for businesses. Both the loss of sensitive files, plus a data breach, can have severe consequences for their business and reputation.”


              18. Intensified supply chain attacks 


              Dirk Schrader, VP of security research at Netwrix

              Dirk Schrader, VP of security research at Netwrix, believes supply chain attacks are set to increase in the coming year. “Modern organisations rely on complex supply chains, including small and medium businesses (SMBs) and managed service providers (MSPs),” he says.

              “Adversaries will increasingly target these suppliers rather than the larger enterprises knowing that they provide a path into multiple partners and customers. To address this threat, organisations of all sizes, while conducting a risk assessment, need to take into account the vulnerabilities of all third-party software or firmware.”


              19. A greater need to manage volatility 


              Paul Milloy, Business Consultant at Intradiem, stresses the importance of managing volatility in an ever-moving market. Milloy believes bosses can utilise data through automation to foresee potential problems before they become issues.

              “No one likes surprises. Whilst Ben Franklin suggested nothing can be said to be certain, except death and taxes, businesses will want to automate as many of their processes as possible to help manage volatility in 2023,” he explains. “Data breeds intelligence, and intelligence breeds insight. Managers can use the data available from workforce automation tools to help them manage peaks and troughs better to avoid unexpected resource bottlenecks.”


              20. A human AI co-pilot will still be needed


              Artem Kroupenev, VP of Strategy at Augury, predicts that within the next few years, every profession will be enhanced with hybrid intelligence, and have an AI co-pilot which will operate alongside human workers to deliver more accurate and nuanced work at a much faster pace. 

              “These co-pilots are already being deployed with clear use cases in mind to support specific roles and operational needs, like AI-driven solutions that enable reliability engineers to ensure production uptime, safety and sustainability through predictive maintenance,” he says. “However, in 2023, we will see these co-pilots become more accurate, more trusted and more ingrained across the enterprise. 

              “Executives will better understand the value of AI co-pilots to make critical business decisions, and as a key competitive differentiator, and will drive faster implementation across their operations. The AI co-pilot technology will be more widespread next year, and trust and acceptance will increase as people see the benefits unfold.”


              21. Building the right workplace culture


              Harnessing a positive workplace culture is no easy task but in 2023 with remote and hybrid working now the norm, it brings with it new challenges. Tony McCandless, Chief Technology Officer at SS&C Blue Prism, is well aware of the role organisational culture can play in any digital transformation journey.

              Workers are the heart of an organisation, so without their buy in, no digital transformation initiative stands a chance of success,” explains McCandless. “Workers drive home business objectives, and when it comes to digital transformation, they are the ones using, implementing, and sometimes building automations. Curiosity, innovation, and the willingness to take risks are essential ingredients to transformative digitalisation. 

              “Businesses are increasingly recognising that their workers play an instrumental role in determining whether digitalisation initiatives are successful. Fostering the right work environment will be a key focus point for the year ahead – not only to cultivate buy-in but also to improve talent retention and acquisition, as labor supply issues are predicted to continue into 2023 and beyond.”


              22. Cloud cover to soften recession concerns


              Amid a cost-of-living crisis and concerns over any potential recession as a result, Daniel Thomasson, VP of Engineering and R&D at Keysight Technologies, says more companies will shift data intensive tasks to the cloud to reduce infrastructure and operational costs.

              “Moving applications to the cloud will also help organisations deliver greater data-driven customer experiences,” he affirms. “For example, advanced simulation and test data management capabilities such as real-time feature extraction and encryption will enable use of a secure cloud-based data mesh that will accelerate and deepen customer insights through new algorithms operating on a richer data set. In the year ahead, expect the cloud to be a surprising boom for companies as they navigate economic uncertainty.”


              23. IoT devices to scale globally


              Dr Raullen Chai, CEO and Co-Founder of IoTeX, recognises a growing trend in the usage of IoT devices worldwide and believes connectivity will increase significantly. 

              “For decades, Big Tech has monopolised user data, but with the advent of Web3, we will see more and more businesses and smart device makers beginning to integrate blockchain for device connectivity as it enables people to also monetise their data in many different ways, including in marketing data pools, medical research pools and more,” he explains. “We will see a growth in decentralised applications that allow users to earn a modest additional revenue from everyday activities, such as walking, sleeping, riding a bike or taking the bus instead of driving, or driving safely in exchange for rewards. 

              “Living healthy lifestyles will also become more popular via decentralised applications for smart devices, especially smart watches and other health wearables.”

              The digital landscape is changing day by day. Ideas like the metaverse that once seemed a futuristic fantasy are now…

              The digital landscape is changing day by day. Ideas like the metaverse that once seemed a futuristic fantasy are now coming to fruition and embedding themselves into our daily lives. The thinking might be there, but is our technology really ready to go meta? Domains and hosting provider, Fasthosts, spoke to the experts to find out…

              How the metaverse works

              The metaverse is best defined as a virtual 3D universe which combines many virtual places. It allows users to meet, collaborate, play games and interact in virtual environments. It’s usually viewed and accessed from the outside as a mixture of virtual reality (VR), (think of someone in their front room wearing a headset and frantically waving nunchucks around) and augmented reality (AR), but it’s so much more than this…

              These technologies are just the external entry points to the metaverse and provide the visuals which allow users to explore and interact with the environment within the metaverse. 

              This is the ‘front-end’ if you like, which is also reinforced by artificial intelligence and 3D reconstruction. These additional technologies help to provide realistic objects in environments, computer-controlled actions and also avatars for games and other metaverse projects. 

              So, what stands in the way of this fantastical 3D universe? Here are the six key challenges:

              Technology

              The most important piece of technology, on which the metaverse is based, is the blockchain. The blockchain is essentially a chain of blocks that contain specific information. They’re a combination of computers linked to each other instead of a central server which means that the whole network is decentralised. This provides the infrastructure for the development of metaverse projects, storage of data and also allows them the capability to be compatible with Web3. Web3 is an upgraded version of the internet which will allow integration of virtual and augmented reality into people’s everyday lives. 

              Sounds like a lot, right? And it involves a great deal of tech that is alien to the vast majority of us. So, is technology a barrier to widespread metaverse adoption?

              Jonothan Hunt, Senior Creative Technologist at Wunderman Thompson, says the tech just isn’t there. Yet.

              “Technology’s readiness for the mass adoption of the metaverse depends on how you define the metaverse, but if we’re talking about the future vision that the big tech players are sharing, then not yet. The infrastructure that powers the internet and our devices isn’t ready for such experiences. The best we have right now in terms of shared/simulated spaces are generally very expensive and powered entirely in the cloud, such as big computers like the Nvidia Omniverse, cloud streaming, or games. These rely heavily on instancing and localised grouping. Consumer hardware, especially XR, is still not ready for casual daily use and still not really democratised.

              “The technology for this will look like an evolution of the systems above, meaning more distributed infrastructure, better access and updated hardware. Web3 also presents a challenge in and of itself, and questions remain over to what extent big tech will adopt it going forward.”

              Storage

              Blockchain is the ‘back-end’, where the magic happens, if you will. It’s this that will be the key to the development and growth of the metaverse. There are a lot of elements that make up the blockchain and reinforce its benefits and uses such as storage capabilities, data security and smart contracts. 

              Due to its decentralised nature, the blockchain has far more storage capacity than the centralised storage systems we have in place today. With data on the metaverse being stored in exabytes, the blockchain works by making use of unutilised hard disk space across the network, which avoids users within the metaverse running out of storage space worldwide. 

              In terms that might be a bit more relatable, an exabyte is a billion gigabytes. That’s a huge amount of storage, and that doesn’t just exist in the cloud – it’s got to go somewhere – and physical storage servers mean land is taken up, and energy is used. Hunt says: “How long’s a piece of string? The whole of the metaverse will one day be housed in servers and data centres, but the amount or size needed to house all of this storage will be entirely dependent on just how mass adopted the metaverse becomes. Big corporations in the space are starting to build huge data centres – such as Meta purchasing a $1.1 billion campus in Toledo, Spain to house their new Meta lab and data centre – but the storage space is not the only concern. These energy-guzzlers need to stay cool! And what about people and brands who need reliable web hosting for events, gaming or even just meeting up with pals across the world, all that information – albeit virtual – still needs a place to go.

              “The current rising cost of electricity worldwide could cause problems for the growth of data centres, and the housing of the metaverse as a whole. However, without knowing the true size of its adoption, it is extremely difficult to truly determine the needed usage. Could we one day see an entire island devoted to data centre storage? Purely for the purposes of holding the metaverse? It seems a little ‘1984’, but who knows?”

              Identity

              Although the blockchain provides instantaneous verification of transactions with identity through digital wallets, our physical form will be represented by avatars that visually reflect who we are, and how we want to be seen. 

              The founder of Saxo Bank and the chairman of the Concordium Foundation, Lars Seier Christensen, argues, “I think that if you use an underlying blockchain-based solution where ID is required at the entry point, it is actually very simple and automatically available for relevant purposes. It is also very secure and transparent, in that it would link any transactions or interactions where ID is required to a trackable record on the blockchain.”

              Once identity is established, it is true that it could potentially become easier to assess creditworthiness of parties for purchasing and borrowing in the metaverse due to the digital identity and storage of each individual’s data and transactions on the blockchain. However, although it sounds exciting, there must be considerations into how it could impact privacy, and how this amount of data will be recorded on the blockchain. 

              Security

              There are also huge security benefits to this set up. The decentralised blockchain helps to eradicate third-party involvement and data breaches, such as theft and file manipulation, thanks to its powerful data processing and use of validation nodes. Both of these are responsible for verifying and recording transactions on the blockchain. This will be reassuring to many, given the widespread concerns around data privacy and user protection in the metaverse.

              To access the blockchain all we will need is an internet connection and a device, such as a laptop or smartphone, this is what makes it so great as it will be so readily available. However, to support the blockchain, we’re relying on a whole different set of technologies.  Akash Kayar, CEO of web3-focused software development company Leeway Hertz, had this to say on the readiness of the current technology available: “The metaverse is not yet completely mature in terms of development. Tech experts are researching strategies and

              testing the various technologies to develop ideas that provide the world with more feasible and intriguing metaverse projects.

              “Projects like Decentraland, Axie Infinity, and Sandbox are popular contemporary live metaverse projects. People behind these projects made perfect use of notable metaverse technologies, from blockchain and cryptos to NFTs.

              “As envisioned by top tech futurists, many new technologies will empower the metaverse in the future, which will support the development of a range of prolific use cases that will improve the ability of the metaverse towards offering real-life functionalities. In a nutshell, the metaverse is expected to bring extreme opportunities for enterprises and common users. Hence, it will shape the digital future.”

              Currency & Payments

              Whilst it’s only considered legal tender in two countries, cryptocurrency is currently a reality and there is a strong likelihood that it will eventually be mass adopted. However, the metaverse is arguably not yet at the same maturity level, meaning cryptocurrency may have to wait before it can finally fully take off. 

              Golden Bitcoin symbol and finance graph screen. Horizontal composition with copy space. Focused image.

              There is no doubt that cryptocurrency and the metaverse will go hand-in-hand as the former will become the tender of the latter with many of the current metaverse platforms each wielding its native currency. For example Decentraland uses $MANA for payments and purchases. However, with the volatility of crypto currencies and the recent collapse of trading platform FTX indicating security lapses, we may not yet be ready for the switch to decentralised payments. 

              Energy

              Some of the world’s largest data centres can each contain many tens of thousands of IT devices which require more than 100 megawatts of power capacity – this is enough to power around 80,000 U.S. households (U.S. DOE 2020) and is equivalent to $1.35bn running cost per data centre with the cost of a megawatt hour averaging $150. 

              According to Nitin Parekh of Hitachi Energy, the amount of power which takes to process Bitcoin is higher than you might expect: “Bitcoin consumes around 110 Terawatt Hours per year. This is around 0.5% of global electricity generation. This estimate considers combined computational power used to mine bitcoin and process transactions.” With this estimate, we can calculate that the annual energy cost of Bitcoin is around $16.5bn. 

              However, some bigger corporations are slowly moving towards renewable energy to power their projects in this space, with Google signing close to $2bn worth of wind and solar investments in order to power its data centres in the future and become greener. Amazon has also followed in their footsteps and have become the world’s largest corporate purchaser of renewable energy. 

              They may have plenty of time yet to get their green processes in place, with Mark Zuckerberg recently predicting it will take nearly a decade for the metaverse to be created: “I don’t think it’s really going to be huge until the second half of this decade at the earliest.”

              About Fasthosts

              Fasthosts has been a leading technology provider since 1999, offering secure UK data centres, 24/7 support and a highly successful reseller channel. Fasthosts provides everything web professionals need to power and manage their online space, including domains, web hosting, business-class email, dedicated servers, and a next-generation cloud platform. For more information, head to www.fasthosts.co.uk

              John MClure, CISO at Sinclair Group – a diversified media company and America’s leading provider of local sports and news – talks about the evolution of cybersecurity and the cultural shift placing it at the forefront of business change

              This month’s cover story explores how Sinclair Broadcast Group is embracing the evolution of cybersecurity and placing the role of the CISO at the forefront of business transformation.

              Welcome to the latest issue of Interface magazine!

              Communication, secure and at speed, is a vital component of the transformation journey for both the modern enterprise and its relationship with stakeholders, be they customers or partners. Putting the right building blocks in place to deliver successful change management is at the heart of the inspiring stories in the latest issue of Interface.

              Read the latest issue here!

              Sinclair Broadcast Group: a cyber transformation

              Our cover star John McClure progressed from a career in the military and work as a consultant in the intelligence industry to fight a new kind of foe… As CISO for Sinclair Broadcast Group, a diversified media company and America’s leading provider of local sports and news, he talks about the evolution of cybersecurity, the battle to meet the rising velocity and sophistication of cyber-attacks and the cultural shift of the role of CISO placing it at the forefront of business change.

              “Sinclair is unique in terms of its different business units and how it operates. It’s my job as CISO leading our cyber team not to be an obstacle for the business; we’re here to help it move faster to keep up with market forces, and to move safely. We’re here to engineer solutions that work for the enterprise but also help us maintain a positive security posture.”

              State of Florida: digital government services

              We also hear from CIO Jamie Grant who is leading the State of Florida’s Digital Service (FL[DS]) on its charge to transform and modernise the way government is accessed and consumed. He is building a team of talented, goal-oriented and customer-obsessed individuals to drive a digital transformation with innovation at its heart. “Leadership is really about developing the team and investing in the people. And it turns out that when you get their backs, they appreciate it and then you can achieve anything.”

              ResultsCX: putting people first

              Jamie Vernon, SVP for IT & Infrastructure at AI-powered customer experience solution specialist ResultsCX, discusses what drives customer care in the 21st century, and the part technology has to play.

              “We are the custodians of our customers’ customers,” says Vernon. “In this increasingly tenuous relationship with their customers, they trust us. My leadership takes that responsibility very seriously, and charges each of us with doing everything we can to provide a perfect call, or email, or chat, every time, thousands of times a minute, around the clock and around the calendar.”

              Jamie Vernon, SVP for IT & Infrastructure at AI-powered customer experience solution specialist ResultsCX, discusses what drives customer care in the 21st century, and the part technology has to play.

              “We are the custodians of our customers’ customers,” says Vernon. “In this increasingly tenuous relationship with their customers, they trust us. My leadership takes that responsibility very seriously, and charges each of us with doing everything we can to provide a perfect call, or email, or chat, every time, thousands of times a minute, around the clock and around the calendar.”

              Also this month, Sarita Singh, Regional Head & Managing Director for Stripe in Southeast Asia, talks about how the fast-growing payments platform is driving financial inclusion across Asia and supporting SMEs with end-to-end services putting users first, and we get expert advice for the modern CEO from the University of Oxford’s Saïd Business School.

              Enjoy the issue!

              Dan Brightmore, Editor

              Our cover story this month investigates how Fleur Twohig, Executive Vice President, leading Personalisation & Experimentation across Consumer Data & Engagement Platforms, and her team are executing Wells Fargo’s strategy to promote personalised customer engagement across all consumer banking channels

              This month’s cover story follows Wells Fargo’s journey to deliver personalised customer engagement across all its consumer banking channels.

              Welcome to the latest issue of Interface magazine!

              Partnerships of all kinds are a key ingredient for organisations intent on achieving their goals… Whether that’s with customers, internal stakeholders or strategic allies across a crowded marketplace, Interface explores the route to success these relationships can help navigate.

              Read the latest issue here!

              Wells Fargo: customer-centric banking

              Fleur Twohig, Wells Fargo

              Our cover story this month investigates the strategy behind Wells Fargo’s ongoing drive to promote personalised customer engagement across all consumer banking channels.

              Fleur Twohig, Executive Vice President, leading Personalisation & Experimentation across the bank’s Consumer Data & Engagement Platforms, explains her commitment to creating a holistic approach to engaging customers in personalised one-to-one conversations that support them on their financial journeys.

              “We need to be there for everyone across the spectrum – for both the good and the challenging times. Reaching that goal is a key opportunity for Wells Fargo and I have the pleasure of partnering with our cross-functional teams to help determine the strategic path forward…”

              IBM: consolidating growth to drive value

              We hear from Kate Woolley, General Manager of IBM Ecosystem, who reveals how the tech leader is making it easier for partners and clients to do business with IBM and succeed. “Honing our corporate strategy around open hybrid cloud and artificial intelligence (AI) and connecting partners to the technical training resources they need to co-create and drive more wins, we are transforming the IBM Ecosystem to be a growth engine for the company and its partners.”

              Kate Woolley, IBM
              Kate Woolley, IBM

              America Televisión: bringing audiences together across platforms

              Jose Hernandez, Chief Digital Officer at America Televisión, explains how Peru’s leading TV network is aggregating services to bring audiences together for omni-channel opportunities across its platforms. “Time is the currency with which our audiences pay us, so we need to be constantly improving our offering both through content and user experiences.”

              Portland Public Schools: levelling the playing field through technology

              Derrick Brown and Don Wolf, tech leaders at Portland Public Schools, talk about modernising the classroom, dismantling systemic racism and the power of teamwork.

              Also in this issue, we hear from Lenovo on how high-performance computing (HPC) is driving AI research and report again from London Tech Week where an expert panel examined how tech, fuelled by data, is playing a critical role in solving some of the world’s hardest hitting issues, ranging from supply chain disruptions through to cybersecurity fears.

              Enjoy the issue!

              Dan Brightmore, Editor

              Conventional robots, like giant industrial robots used in the car industry, are set to reach $14.9bn value this year, up from $12bn in 2018.

              Robotics play a huge role in the manufacturing landscape today. A growing number of businesses use manufacturing robots to automate repetitive tasks, reduce errors, and enable their employees to focus on innovation and efficiency, causing the entire sector’s impressive growth.

              According to data presented by AksjeBloggen.com, the global market value of conventional and advanced robotics in the manufacturing industry is expected to continue rising and hit $18.6bn in 2021, a 40% increase in three years.

              Market Value Jumped by $5.4B in Three Years

              Robots have numerous roles in manufacturing. They are mainly used for high-volume, repetitive processes where their speed and accuracy offer tremendous advantages. Other manufacturing automation solutions include robots used to help people with more complex tasks, like lifting, holding, and moving heavy pieces.

              Companies turn to robotics process automation to cut manufacturing costs, solve the shortage of skilled labor and keep their cost advantage in the market.

              In 2018, the global market value of conventional and advanced robotics in the manufacturing industry amounted to $13.2bn, revealed the BCG survey. In 2019, this figure rose to $14.8bn and continued growing. Statistics show the market value of manufacturing robots hit $16.6bn in 2020. This figure is expected to jump by $2bn and hit $18.6bn in 2021.

              Conventional robots, like giant industrial robots used in the car industry, are set to reach $14.9bn value this year, up from $12bn in 2018.

              The market value of advanced manufacturing robots, which have a superior perception, adaptability, and mobility, tripled in the last three years and is expected to hit $3.7bn in 2021. Combined with big data analytics, advanced manufacturing robots allow companies to make intelligent decisions based on real-time data, which leads to lower costs and faster turnaround times.

              The BCG survey also showed most manufacturers believe advanced robotic systems will have a massive role in the factory of the future and plan to increase their use. More than 70% of respondents defined robotics as a significant productivity driver in production and logistics.

              European and Asian Companies Lead in the Use of Advanced Manufacturing Robots

              Analyzed by regions, European and Asian companies lead in the use of advanced robots, while manufacturers from North America lag behind. However, the survey showed 80% of respondents from the US plan to implement advanced robotics in the next few years.

              The survey also revealed that manufacturers in emerging markets, especially China and India, are more enthusiastic about using advanced robots than those in industrialized countries. These companies may be looking to automation as a way to overcome a skilled labor shortage and improve their ability to compete in international markets.

              Germany had the largest robot density in the manufacturing industry among European countries, with 346 installations per 10,000 employees in 2019. Sweden, Denmark, and Italy followed with 277, 243, and 212 installations per 10,000 employees, respectively.

              Statistics also show that companies in the transportation and logistics and technology sector lead in implementing advanced robotics, with 54% and 53% of manufacturers who already use such solutions. The automotive industry and consumer goods sector follow with 49% and 44% share, respectively.

              Manufacturers in the engineered products, process, and health care industries lag behind, with 42%, 41%, and 30% of companies that use advanced manufacturing robots. However, around 85% of manufacturers in these sectors plan to start using advanced robotic systems by 2022.

              Gurpreet Purewal, Associate Vice President, Business Development, iResearch Services, explores how organisations can overcome the challenges presented by AI in 2021.

              2020 has been a year of tumultuous change and 2021 isn’t set to slow down. Technology has been the saving grace of the waves of turbulence this year, and next year as the use of technology continues to boom, we will see new systems and processes emerge and others join forces to make a bigger impact. From assistive technology to biometrics, ‘agritech’ and the rise in self-driving vehicles, tech acceleration will be here to stay, with COVID-19 seemingly just the catalyst for what’s to come. Of course, the increased use of technology will also bring its challenges, from cybersecurity and white-collar crime to the need to instil trust in not just those investing in the technology, but those using it, and artificial intelligence (AI) will be at the heart of this. 

              1. Instilling a longer-term vision 

              New AI and automation innovations have led to additional challenges such as big data requirements for the value of these new technologies to be effectively shown. For future technology to learn from the challenges already faced, a comprehensive technology backbone needs to be built and businesses need to take stock and begin rolling out priority technologies that can be continuously deployed and developed. 

              Furthermore, organisations must have a longer-term vision of implementation rather than the need for immediacy and short-term gains. Ultimately, these technologies aim to create more intelligence in the business to better serve their customers. As a result, new groups of business stakeholders will be created to implement change, including technologists, business strategists, product specialists and others to cohesively work through these challenges, but these groups will need to be carefully managed to ensure a consistent and coherent approach and long-term vision is achieved. 

              2. Overcoming the data challenge

              AI and automation continue to be at the forefront of business strategy. The biggest challenge, however, is that automation is still in its infancy, in the form of bots, which have limited capabilities without being layered with AI and machine learning. For these to work cohesively, businesses need huge pools of data. AI can only begin to understand trends and nuances by having this data to begin with, which is a real challenge. Only some of the largest organisations with huge data sets have been able to reap the rewards, so other smaller businesses will need to watch closely and learn from the bigger players in order to overcome the data challenge. 

              3. Controlling compliance and governance

              One of the critical challenges of increased AI adoption is technology governance. Businesses are acutely aware that these issues must be addressed but orchestrating such change can lead to huge costs, which can spiral out of control. For example, cloud governance should be high on the agenda; the cloud offers new architecture and platforms for business agility and innovation, but who has ownership once cloud infrastructures are implemented? What is added and what isn’t? 

              AI and automation can make a huge difference to compliance, data quality and security. The rules of the compliance game are always changing, and technology should enable companies not just to comply with ever-evolving regulatory requirements, but to leverage their data and analytics across the business to show breadth and depth of insight and knowledge of the workings of their business, inside and out. 

              In the past, companies struggled to get access and oversight over the right data across their business to comply with the vast quantities of MI needed for regulatory reporting. Now they are expected to not only collate the correct data but to be able to analyse it efficiently and effectively for regulatory reporting purposes and strategic business planning. There are no longer the time-honoured excuses of not having enough information, or data gaps from reliance on third parties, for example, so organisations need to ensure they are adhering to regulatory requirements in 2021.

              4. Eliminating bias

              AI governance is business-critical, not just for regulatory compliance and cybersecurity, but also in diversity and equity. There are fears that AI programming will lead to natural bias based on the type of programmer and the current datasets available and used. For example, most computer scientists are predominantly male and Caucasian, which can lead to conscious/unconscious bias, and datasets can be unrepresentative leading to discriminatory feedback loops.

              Gender bias in AI programming has been a hot topic for some years and has come to the fore in 2020 again within wider conversations on diversity. By only having narrow representation within AI programmers, it will lead to their own bias being programmed into systems, which will have huge implications on how AI interprets data, not just now but far into the future. As a result, new roles will emerge to try and prevent these biases and build a more equitable future, alongside new regulations being driven by companies and specialist technology firms.

              5. Balancing humans with AI

              As AI and automation come into play, workforces fear employee levels will diminish, as roles become redundant. There is also inherent suspicion of AI among consumers and certain business sectors. But this fear is over-estimated, and, according to leading academics and business leaders, unfounded. While technology can take away specific jobs, it also creates them. In responding to change and uncertainty, technology can be a force for good and source of considerable opportunity, leading to, in the longer-term, more jobs for humans with specialist skillsets. 

              Automation is an example of helping people to do their jobs better, speeding up business processes and taking care of the time-intensive, repetitive tasks that could be completed far quicker by using technology. There remain just as many tasks within the workforce and the wider economy that cannot be automated, where a human being is required.

              Businesses need to review and put initiatives in place to upskill and augment workforces. Reflecting this, a survey on the future of work found that 67% of businesses plan to invest in robotic process automation, 68% in machine learning, and 80% investing in perhaps more mainstream business process management software. There is clearly an appetite to invest strongly in this technology, so organisations must work hard to achieve harmony between humans and technology to make the investment successful.

              6. Putting customers first

              There is growing recognition of the difference AI can make in providing better service and creating more meaningful interactions with customers. Another recent report examining empathy in AI saw 68% of survey respondents declare they trust a human more than AI to approve bank loans. Furthermore, 69% felt they were more likely to tell the truth to a human than AI, yet 48% of those surveyed see the potential for improved customer service and interactions with the use of AI technologies.

              2020 has taught us about uncertainty and risk as a catalyst for digital disruption, technological innovation and more human interactions with colleagues and clients, despite face-to-face interaction no longer being an option. 2021 will see continued development across businesses to address the changing world of work and the evolving needs of customers and stakeholders in fast-moving, transitional markets. The firms that look forward, think fast and embrace agility of both technology and strategy, anticipating further challenges and opportunities through better take-up of technology, will reap the benefits.

              With virtually all companies looking at AI, what are some of the key risks they need to consider before implementation?

              Today virtually all companies are forced to innovate and many are excited about AI. Yet since implementation cuts across organisational boundaries, shifting to an AI-driven strategy requires new thinking about managing risks, both internally and externally. This blog will cover “the seven sins of enterprise AI strategies”, which are governance issues at the board and executive levels that block companies from moving ahead with AI. by By Jeremy Barnes, Element AI

              1- Disowning the AI strategy

              This is probably the most important sin. In this case, a CEO and board will say that AI is a priority, but delegate it to a different department or an innovation lab. However, success is not based on whether or not a company uses an innovation lab—it’s whether they are truly invested in it. The bottom line is that the CEO and board need to actively lead an AI strategy.

              2- Ignoring the unknowns

              This happens when companies say they believe in AI, but don’t reach a level of proficiency where it’s possible to identify, characterise and model the threats that emerge with new advances. Even if it is decided not to go all-in on AI innovation, it’s still important that there is a hypothesis for how to address AI within a company and an early warning system so the decision can be re-evaluated early enough to act.  Being a fast follower requires as much organizational preparation and lead time as leadership.

              3- Not enabling the culture

              The ability to implement AI is about an experimentation mindset. That and an openness to failure need to be adopted across the company. Organisations need to keep in mind that AI doesn’t respect organisational boundaries. Most companies want high-impact, low-risk solutions that could simply lead to optimising, rather than advancing new value streams. It is hard to accept increased risk in exchange for impact but it will come as part of the continuous cultural enablement of an experimental mindset.

              4- Starting with the solution

              This is the most common sin. It’s important to be able to understand the specific problems you’re trying to solve, because AI is unlikely to be a solution for all of them, and especially not blindly implementing a horizontal AI platform. Have the conversation at board level to ensure that an overarching AI strategy, and not simply quick-fix solutions, is the priority.

              5- Lose risk, keep reward

              As mentioned in the third sin, it is natural for companies to want to implement AI without any risk. But there is no reward without risk. A vendor motivated to decrease risk will also decrease innovation and ultimately impact by making successes small and failures non-existent. AI creates differentiation only for companies that are willing to learn from both their successes and their failures. A company that doesn’t effectively balance risk in AI will ultimately increase its risk of disruption.

              6- Vintage accounting

              Attempting to fit AI into traditional financial governance structures causes problems. It doesn’t fit nicely into budget categories and it’s hard to value the output. The link between what you put in and what you get out can be less tangible or predictable, which often makes it harder to square with existing plans or structures. Model the rate of return on AI activities and all data-related activities. This demands that these activities affect profit (not just loss) and assets (not just liabilities).

              7- Treating data as a commodity

              The final sin concerns data and its treatment as a commodity. Data is fundamental to AI. If data is poorly handled, it can lead to negative impacts on decision-making. Data should be treated as an asset. The stronger, deeper and more accurate the dataset, the better models that you can train and more intelligent insights you can generate. But, at the same time, when personally identifiable information is stored about customers, it can be stolen, risking heavy penalties in some jurisdictions. You need to build towards data from a use case rather than invest blindly in data centralisation projects. So, now you know what not to do. Here are some of the simple things that you can do to move ahead. First, talk to your board about how long it will take to become an AI innovator, modelling it out, rather than simply discussing it conceptually.

              Second, prepare for change and put in place monitoring. AI shifts all the time, so you’ll want to regularly check in to adjust and pivot your strategy. It’s important to develop a basic skill set so you can redo planning exercises with your board. Third, model out risks in both action and inaction. But don’t model them in a traditional approach, which is to push risk down to different business units and then compensate those units for reducing risk rather than managing trade-offs. Instead, view those trade-offs in terms of risks and rewards, and start to think about how you are accounting for the assets and liabilities of AI. Ultimately, you want to start to model what is the actual rate of return for all these activities that you are doing. Then benchmark it against what you see in other companies from across the industry, and that will give you a good picture of the current situation and where to go.

              Understanding what it isn’t is just as important as understanding what it is, says Jim Logan who has nearly three decades of experience in financial services and technology…

              I’ve been working in the financial services space for close to thirty years now. I’ve seen many trends and technologies emerge. Some take hold, several are just a flash in the pan. Regardless of how long a concept sticks around, one thing remains: Terminology plays a material role in shaping perceptions. In a world where messaging tends to over complicate things, too many acronyms and too many buzzwords all work against what should be the primary objective: clearly illustrating value. I’ve found this to be equally true when it comes to artificial intelligence or ‘AI’.

              Generally speaking, the word artificial doesn’t readily call to mind a positive image, does it? By definition, the word “artificial” has listed meanings of, “insincere or affected” and “made by humans as opposed to happening naturally.”  It is the second part of this definition I’d like to explore a bit further.

              Artificial Intelligence is, in fact, created by humans. And it isn’t a new fad or concept. Many don’t realize that the term was first coined by John McCarthy, Ph.D. and Stanford computer and cognitive scientist, back in 1955.  AI has continued to evolve as a material concept, with practical applications across many industries, ever since.

              For financial service professionals, particularly those of us involved with fighting financial crime and preventing money laundering, AI can have tremendous impact and practical application.  Before we dive a bit deeper, I feel it’s important to first understand what AI isn’t.

              AI is not intended to simply be a digital worker, certainly not within financial services and fighting financial crime. Yes, AI can automate various functions. We’re all familiar with the concept of ‘bots’ and virtual assistants. However, those are rudimentary examples of robotic process automation. True AI is human led and a continuous, instantaneous learning process that drives tangible value. AI is not merely a play to cut costs or replace human capital. Rather, AI enhances the bottom line by keeping compliance staff costs flat in the immediate term and enables our human experts to more appropriately manage their time, by focusing talent on investigations that matter the most.

              One of the most valuable aspects of AI, in the context of anti money laundering and compliance, is the speed by which it can be deployed. We’re talking about time to market and time to value in a matter of weeks. Not months, not multiple quarters – simply weeks. But I don’t mean a generic, black box concept. I’m specifically referring to a highly precise, tailored AI solution that has extensive proof points and, more importantly, far-reaching global regulatory approval.

              AI shouldn’t simply be an extension of legacy rules-based routines, nor a way to further automate the process of scoring or risk weighted alert suppression. That simply dilutes the true value of AI, and does not maximize the cost and efficiency benefits.

              The cost of compliance continues to grow at a staggering pace, particularly for financial institutions and insurance companies. Equally of concern, the impact of fines for non-compliance has also skyrocketed in the last decade. Specifically to the tune of $8.4 billion last year across North America alone.

              What if you could literally solve every single name screen, sanction, and transaction alert? What if you could achieve this without sacrificing any aspect of control and security? What if you could increase the throughput, efficiency and accuracy of your compliance operations without adding a single dollar of staff expense to your budget?

              Let’s stop talking in terms of what if and have a meaningful conversation regarding how. I’m helping clients achieve all of these measures today and that is from a perspective proven in production. Here at Silent Eight we’re a team founded by engineers and data scientists, solving real world challenges in the anti money laundering and financial compliance market.

              Artificial Intelligence isn’t scary…it isn’t a black box…and it isn’t the futuristic world of tomorrow – it is the here and now, and it’s battle tried and tested.

              Temenos, the banking software company, partners with Microsoft to offer AI-driven Financial Crime Mitigation solution to help banks combat surge cybercrime during Covid-19 outbreak.

              Temenos, the banking software company, announced today a joint effort with Microsoft to enable access to its AI-powered, Financial Crime Mitigation (FCM) SaaS solution to allow banks to protect both their customers and their organization from financial crime increase during the pandemic, particularly as banks have moved to remote working to protect their staff. Temenos AI-powered, Financial Crime Mitigation SaaS solution based on Microsoft’s fast, scalable and secure Azure cloud platform can be deployed within weeks. 

              Temenos and Microsoft are opening up access to banks for a 14-day trial, available until 30 of June. As part of the collaboration with Microsoft, Temenos is offering system access and online tutorials for users to familiarize themselves with navigation of the system and learn how it can support them in a revised operating landscape. Temenos unveiled the open access initiative of its FCM software at its virtual event Temenos Community Forum Online, 29-30 April.

              Temenos FCM provides enterprise-wide financial crime protection for a highly regulated and fast-changing environment. It allows banks’ operators to respond to alerts and collaborate with team members while working remotely. Throughout the Covid-19 crisis, Temenos customers from Tier 1 banks to regional banks and neobanks have continued to benefit from Temenos FCM’s comprehensive coverage regardless of the fact that their teams are working remotely.

              Financial regulators worldwide and organizations such as the European Central Bank are warning that the Covid-19 pandemic may result in an increase in financial crime and other misconduct due to market disruptions, reduced staff, and other factors, as has been the case during past global crises. Opportunistic fraudsters and criminals are adapting their methods of targeting people and countries in distress as new threat vectors open up.

              The Financial Actions Task Force (FATF), the global standard setter for combating money laundering and terrorism financing, warns businesses to remain vigilant for emerging money laundering and terrorist financing risks as criminals may seek to exploit gaps and weaknesses in Anti-Money Laundering/Combating the Financing of Terrorism (AML/CFT) systems under the assumption that resources are focused elsewhere. Fraudsters have already been very quick to adapt well-known fraud schemes to target individual citizens, businesses and public organizations. These include various types of adapted versions of telephone fraud schemes, supply scams and decontamination scams.

              Jean-Michel Hilsenkopf, Chief Operating Officer, Temenos, said: We are proud to be able to offer our cloud-native and AI technology to support banks in the fight against financial crime, which has increased as a result of the pandemic. As a strategic global banking software partner of Microsoft, we are pleased to join efforts to deliver Temenos Financial Crime Mitigation as SaaS on Microsoft Azure’s resilient, secure and proven cloud platform. We are committed to providing robust and up-to-date sanction screening, AML, KYC and fraud management protection combined with powerful AI-driven transaction monitoring and sanction screening to help banks worldwide.”

              Marianne Janik, Country General Manager, Microsoft Switzerland, said: “We have been pioneering with Temenos in the cloud for a decade. We are proud to join forces to help banks use the power of Temenos’ market-leading Financial Crime Mitigation solution based on our secure, scalable and resilient global Azure cloud platform to combat financial crime surge due to Covid-19.” 

              More than 200 banks use Temenos FCM SaaS solution, which covers watch-list screening, anti-money laundering, fraud prevention – suspicious activity prevention – and KYC, delivering industry-leading levels of detection and false positives of under 2% vs industry average of 7% and above. Temenos FCM can be deployed as a standalone, or integrated into any banking or payments platform including cloud-native, cloud-agnostic Temenos Transact and Temenos Infinity. It provides unrivalled levels of detection and resilience against financial crime and Total Cost of Ownership (TCO) savings of more than 50%. Temenos FCM provides banks with the next generation of AI-driven FCM capabilities that can run on any public cloud, as a service or on premise.

              The global developer of artificial intelligence solutions is releasing a free search platform to help clinical and scientific researchers find answers and patterns in research papers

              Information on COVID-19 is evolving fast and this AI-powered platform leverages a semantic search model that will allow users to quickly connect disparate information. The platform can execute searches based on specific inquiries, along with critical paragraphs copied from a relevant paper. Unlike keyword searches, the queries do not need to be specifically structured, and actually perform better in longer form. This initial version is configured to work with the COVID-19 Open Research Dataset (CORD-19) corpus. Element AI is looking for users and organizations from various groups to test the platform and suggest other data sets and features that could best fit their needs.

              The group’s Element AI is looking to work with include:

              Clinical researchers who need to incorporate many phenomena to make a rich model of the pandemic and its impacts.

              Government, Public Safety and Public Health authorities looking to find best practices across different countries.


              Pharmaceutical companies working on new therapies or vaccine trials, as well as identifying existing therapies that could provide immediate help.

              -Scientific researchers and data scientists who are working on novel ways to connect research across the body of knowledge already available for COVID-19.

              “Research data and reports are being published at an unprecedented pace as organizations scale up their efforts to respond to COVID-19. We want to contribute, and this free platform is our way to help the community locate and gather knowledge to find answers and patterns,” said Jean-François (JF) Gagné, CEO and Co-founder of Element AI. “We encourage the scientific and healthcare community to use this free platform and engage with our team to quickly ramp up and collaboratively meet the needs of the people working to slow down and contain COVID-19. We hope that their feedback and collaboration will help us quickly add features and datasets on top of what we already have made available” added Gagné.

              The COVID-19 platform leverages technology from the Element AI Knowledge Scout product, which uses natural language techniques to tap into structured and unstructured sources of information. The first version will be progressively updated in coming weeks as additional datasets emerge. The site can be accessed at: https://www.elementai.com/covid-research.

              Mauro Guillén Zandman, Professor of International Management, The Wharton School, University of Pennsylvania, USA Srikar Reddy, Managing Director and Chief…

              Mauro Guillén Zandman, Professor of International Management, The Wharton School, University of Pennsylvania, USA

              Srikar Reddy, Managing Director and Chief Executive Officer, Sonata Software Limited and Sonata Information Technology Limited

              Artificial intelligence (AI) relies on big data and machine learning for myriad applications, from autonomous vehicles to algorithmic trading, and from clinical decision support systems to data mining. The availability of large amounts of data is essential to the development of AI.  But the scandal over the use of personal and social data by Facebook and Cambridge Analytica has brought ethical considerations to the fore. And it’s just the beginning. As AI applications require ever greater amounts of data to help machines learn and perform tasks hitherto reserved for humans, companies are facing increasing public scrutiny, at least in some parts of the world. Tesla and Uber have scaled down their efforts to develop autonomous vehicles in the wake of widely reported accidents. How do we ensure the ethical and responsible use of AI? How do we bring more awareness about such responsibility, in the absence of a global standard on AI?

              The ethical standards for assessing AI and its associated technologies are still in their infancy. Companies need to initiate internal discussion as well as external debate with their key stakeholders about how to avoid being caught up in difficult situations.

              Consider the difference between deontological and teleological ethical standards. The former focuses on the intention and the means, while the latter on the ends and outcomes. For instance, in the case of autonomous vehicles, the end of an error-free transportation system that is also efficient and friendly towards the environment might be enough to justify large-scale data collection about driving under different conditions and also, experimentation based on AI applications.

              By contrast, clinical interventions and especially medical trials are hard to justify on teleological grounds. Given the horrific history of medical experimentation on unsuspecting human subjects, companies and AI researchers alike would be wise to employ a deontological approach that judges the ethics of their activities on the basis of the intention and the means rather than the ends.

              Another useful yardstick is the so-called golden rule of ethics, which invites you to treat others in the way you would like to be treated. The difficulty in applying this principle to the burgeoning field of AI lies in the gulf separating the billions of people whose data are being accumulated and analyzed from the billions of potential beneficiaries. The data simply aggregates in ways that make the direct application of the golden rule largely irrelevant.

              Consider one last set of ethical standards: cultural relativism versus universalism. The former invites us to evaluate practices through the lens of the values and norms of a given culture, while the latter urges everyone to live up to a mutually agreed standard. This comparison helps explain, for example, the current clash between the European conception of data privacy and the American one, which is shaping the global competitive landscape for companies such as Google and Facebook, among many others. Emerging markets such as China and India have for years proposed to let cultural relativism be the guiding principle, as they feel it gives them an edge, especially by avoiding unnecessary regulations that might slow their development as technological powerhouses.

              Ethical standards are likely to become as important at shaping global competition as technological standards have been since the 1980s. Given the stakes and the thirst for data that AI involves, it will likely require companies to ask very tough questions as to every detail of what they do to get ahead. In the course of the work we are doing with our global clients, we are looking at the role of ethics in implementing AI. The way industry and society addresses these issues will be crucial to the adoption of AI in the digital world.

              However, for AI to deliver on its promise, it will require predictability and trust. These two are interrelated. Predictable treatment of the complex issues that AI throws up, such as accountability and permitted uses of data, will encourage investment in and use of AI. Similarly, progress with AI requires consumers to trust the technology, its impact on them, and how it uses their data. Predictable and transparent treatment facilitates this trust.

              Intelligent machines are enabling high-level cognitive processes such as thinking, perceiving, learning, problem-solving and decision-making. AI presents opportunities to complement and supplement human intelligence and enrich the way industry and governments operate.

              However, the possibility of creating cognitive machines with AI raises multiple ethical issues that need careful consideration. What are the implications of a cognitive machine making independent decisions? Should it even be allowed? How do we hold them accountable for outcomes? Do we need to control, regulate and monitor their learning?

              A robust legal framework will be needed to deal with those issues too complex or fast-changing to be addressed adequately by legislation. But the political and legal process alone will not be enough. For trust to flourish, an ethical code will be equally important.

              The government should encourage discussion around the ethics of AI, and ensure all relevant parties are involved. Bringing together the private sector, consumer groups and academia would allow the development of an ethical code that keeps up with technological, social and political developments.

              Government efforts should be collaborative with existing efforts to research and discuss ethics in AI. There are many such initiatives which could be encouraged, including at the Alan Turing Institute, the Leverhulme Centre for the Future of Intelligence, the World Economic Forum Centre for the Fourth Industrial Revolution, the Royal Society, and the Partnership on Artificial Intelligence to Benefit People and Society.

              But these opportunities come with associated ethical challenges:

              Decision-making and liability: As AI use increases, it will become more difficult to apportion responsibility for decisions. If mistakes are made which cause harm, who should bear the risk?

              Transparency: When complex machine learning systems are used to make significant decisions, it may be difficult to unpick the causes behind a specific course of action. Clear explanations for machine reasoning are necessary to determine accountability.

              Bias: Machine learning systems can entrench existing bias in decision-making systems. Care must be taken to ensure that AI evolves to be non-discriminatory.

              Human values: Without programming, AI systems have no default values or “common sense”. The British Standards Institute BS 8611 standard on the “ethical design and application of robots and robotic systems” provides some useful guidance: “Robots should not be designed solely or primarily to kill or harm humans. Humans, not robots, are the responsible agents; it should be possible to find out who is responsible for any robot and its behaviour.”

              Data protection and IP: The potential of AI is rooted in access to large data sets. What happens when an AI system is trained on one data set, then applies learnings to a new data set?

              Responsible AI ensures attention to moral principles and values, to ensure that fundamental human ethics are not compromised. There have been several recent allegations of businesses exploiting AI unethically. However, Amazon, Google, Facebook, IBM and Microsoft have established a non-profit partnership to formulate best practices on artificial intelligence technologies, advance the public’s understanding, and to serve as a platform about artificial intelligence.

              Peltarion, leading AI innovator and creator of an operational deep learning platform, today announced the findings of a survey of…

              Peltarion, leading AI innovator and creator of an operational deep learning platform, today announced the findings of a survey of AI decision-makers examining what they see as the impact of the skills shortage, and suggestions on how to overcome it. The research, ‘AI Decision-Makers Report: The human factor behind deep learning’, presents the findings of a survey of 350 IT leaders in the UK and Nordics with direct responsibility for shepherding AI at companies with more than 1,000 employees.

              The report finds that many AI decision-makers are concerned about the business impact of the deep learning skills shortage. 84% of respondents said their company leaders worry about the business risks of not investing in deep learning, with 83% saying that a lack of deep learning skills is already impacting their ability to compete in the market. These companies are exclusively focusing on recruiting data scientists (71% of AI decision-makers are actively recruiting to plug the deep learning skills gap), and this is already impacting their ability to progress with AI projects:

              • Almost half (49%) say the skills shortage is causing delays to projects
              • 44% believe the need for specialist skills is a major barrier to further investment in deep learning
              • However, almost half (45%) say they are struggling to hire because they don’t have a mature AI program already in place

              “This report shows that companies can’t afford to wait for data science talent to come to them to progress their AI projects. The fact is, many organisations are already starting to lose their competitive edge by waiting for specialised data scientists. The current approach, which relies on hiring an isolated team of data scientists to work on deep learning projects, is delaying projects and putting strain on the talent companies do have,” explains Luka Crnkovic-Friis, Co-Founder and CEO at Peltarion. “In order to solve the deep learning skills gap, we need to make use of transferrable talent that can be found right under companies’ noses. Deep learning will only reach its true potential if we get more people from different areas of the business using it, taking pressure off data scientists and allowing projects to progress.” 

              Less than half (48%) of respondents said they currently employ data scientists who can create deep learning models, compared to 94% that have data scientists who can create other machine learning models. This shortage is having a direct impact on teams: 93% of AI decision-makers say their data scientists are over-worked to some extent because they believe there is no one else who can share the workload. However, with the right tools, others can make a serious impact on AI projects.

              “Organisations need to move projects forward by bringing on existing domain experts and investing in tools that will help them input into AI projects. This will reduce the strain on data scientists and lower deep learning’s barrier to entry,” concludes Crnkovic-Friis. “We need to make deep learning more affordable and accessible to all by reducing its complexity. By operationalising deep learning to make it more scalable, affordable and understandable, organisations can put themselves on the fast track and use deep learning to optimise processes, create new products and add direct value to the business.” 

              AI is no longer science-fiction writers dream, it’s being implemented in industries all over the world. We look at 5…

              AI is no longer science-fiction writers dream, it’s being implemented in industries all over the world. We look at 5 examples of how AI is revolutionising the retail experience Written by: Dale Benton

              Marks and Spencer

              In early 2019, M&S announced a new Technology Transformation Program, one that will allow M&S to become a digital-first business and deliver key improvements in customer experience. As part of this transformation, M&S has partnered with Microsoft to investigate and test the capabilities of technology and artificial intelligence in a retail environment. M&S will look to integrate machine learning, computer vision and AI across every endpoint – both in its stores and behind the scenes. Every surface, screen and scanner in its stores will create data – and enable employees to act upon it. Every M&S store worldwide will be able to track, manage and replenish stock levels in real time – and deal with unexpected events.

              https://www.marksandspencer.com/
              https://twitter.com/marksandspencer
              https://www.facebook.com/MarksandSpencer

              John Lewis/Waitrose

              The John Lewis Partnership is currently partaking in a three-year trial, deploying robots to one of its farms, which grows produce for its Waitrose & Partners brand.  The robots, named Tom, Dick and Harry, are delivered in partnership with the Small Robot Company. Each will be equipped with a camera and AI technology to gather topographical data, while autonomously obtaining accurate, plant-by-plant data in order to enable higher farming efficiency.  The data will also be used to develop further machine learning capabilities. The trial will also provide the John Lewis Partnership’s Room Y innovation team with valuable insight to support innovation and inform how robotics and Artificial Intelligence (AI) could be used further in other areas of the business.

              https://www.johnlewis.com/
              https://twitter.com/JLandPartners
              http://www.facebook.com/johnlewisretail

              Walmart

              One of the biggest retail companies in the world has been piloting and implementing artificial intelligence solutions across its stores for a number of years.  As part of a technology program, called Missed Scan Detection, Walmart has deployed AI-equipped cameras in more than 1,000 of its stores. These cameras, developed in part with Everseen, tracks and analyses activities at both self-checkout registers and those manned by Walmart employees. If an item isn’t scanned at checkout, the cameras will detect the and notify a checkout attendant of the problem. The AI technology allows Walmart to monitor its inventory product quantities, but also significantly reduce theft across its stores.

              https://www.walmart.com/
              https://www.facebook.com/walmart

              Amazon

              Amazon Go represents a whole n era of shipping. The concept is simple, walk into an Amazon Go store, pick up whatever you want and walk back out.  The idea is to create a “Just Walk Out” experience. Described as the “most advanced shopping technology”, customers simply download the Amazon Go app. Powerful machine learning and AI technology automatically detects when products are taken from or returned to the shelves, keeping track of them all in a virtual cart. Once customers leave, Amazon will collate all of the data and produce a receipt and charge the customer’s Amazon account.

              amazon.co.uk

              https://twitter.com/amazon
              https://www.facebook.com/AmazonUK/

              Morrisons

              One of the UK’s largest food retailers with more than 120,000 colleagues in 494 stores serving over 11 million customers every week, Morrisons turned its attention to AI with JDA Software. Looking to vastly improve the customer experience, Morrisons looked at reducing queues at checkouts, and improving on-shelf availability. Morrisons invested in Blue Yonder – a Demand Forecast & Replenishment solution from JDA, which uses Artificial Intelligence (AI) technology to improve demand planning and reinvigorate replenishment based on customer behaviour in every store. Over a 12-month period, Morrisons was able to generate up to 30% reduction in shelf gaps and a 2-3 day reduction in stockholding in-store. AI technology has also enabled Morrisons to close the execution gap, optimizing availability while reducing wastage, enhancing shelf presentation and meeting stockholding targets.

              groceries.morrisons.com
              https://www.twitter.com/morrisons
              http://www.facebook.com/Morrisons

              By Craig Summers, Managing Director, Manhattan Associates Customer experience can be make or break for retailers. In fact, recent research…

              By Craig Summers, Managing Director, Manhattan Associates

              Customer experience can be make or break for retailers. In fact, recent research shows that flawed customer experiences could be costing British retailers up to £102 billion in lost sales each year. This shouldn’t be news to retailers; the modern consumer demands a connected, consistent experience that is personalised to them, whether it’s online or instore. The same research found that running out of stock in-store was the biggest contributor to lost revenue, with 79 per cent of consumers saying they would not return to make a purchase if they found their desired item was out of stock. This frustration is only amplified if an out of stock product is marketed to the consumer. 

              Personalisation isn’t anything new but if the basics aren’t right, retailers risk not delivering on customer experience. Many retailers still aren’t getting it right – and, explains Craig Summers, Managing Director, Manhattan Associates, inept personalisation is affecting the bottom line.

              Misplaced Personalisation

              The way in which retailers can engage with customers has changed radically over the past decade, from social media onwards. Add in the compelling appealing of Artificial Intelligence (AI) and the promise of incredibly accurate and timely promotional offers, and personalisation has become a foundation of any retail strategy. Yet while the marketing activity is becoming ever more sophisticated, personalisation cannot be delivered by marketing alone. 

              Without integrating marketing activity to the core operation, retailers risk repelling rather than engaging customers. Product offers that are out of stock in the customer’s size. Promotions not on offer at the local store. Incentives to buy an item the customer has already purchased – not a problem for a standard food or household item, incredibly annoying if it’s an expensive mountain bike or cashmere jumper. Customers are becoming increasingly familiar with ostensibly personalised offers that fail to deliver a great experience.

              What is the thinking behind a promotion that cannot be purchased by the customer? Why set such high expectations when they cannot be met? Enticing a customer to click through an emailed offer may be the measure of marketing success – but when that customer is unable to make a purchase because the desired item is not available in his or her size, that is at least one lost sale and a bottom line retail failure.

              Complete Experience

              Are retailers listening to what their customers want from personalisation? Great personalised offers will not deliver any value if they are not linked to the rest of the business. Smart technologies, such as AI, without any doubt have a role to play in delivering personalisation – but they are not the foundation. The foundation is getting the basics right. It is ensuring that when a customer wants to buy a product – online or instore – it is available. It is about providing Store Associates with the ability to track stock anywhere in the supply chain, reserve it for a customer to try on instore or have it sent direct to their destination of choice.  It is about combining stock availability information with customer insight to make intelligent suggestions, both instore and via marketing promotions. 

              Bottom line success is, essentially, about the quality of the interaction. And that means considering not just the accuracy of the promotional offer but the complete customer experience. What is achievable today? What can be done well? If a product is being promoted to an individual, is it available in the right size? Is it available locally, or only in flagship outlets? It is these disconnected experiences that are fundamentally undermining customer experience and brand value.

              Conclusion

              The future of customer personalisation is incredibly exciting. AI promises the ability to predict a customer’s desires before the customer. Fabulous. But only fabulous if that product is available to buy, at a time and place to suit that individual. Right now personalisation is about the retailer; it is about being clever with promotions.  It needs to be about the customer; it needs to be about delivering the quality of experience that drives sales.

              Retailers need to go back to basics: use technology to recreate the ‘corner shop model’ of the past, at scale. By creating a truly immersive experience for their customers, retailers can find a way to make personalisation profitable again.

              The uptake of artificial intelligence by industry will drastically change the UK job market in the coming years – with…

              The uptake of artificial intelligence by industry will drastically change the UK job market in the coming years – with 133 million new jobs expected to be created globally.

              In the UK alone, up to a third of jobs will be automated or likely to change as a result of the emergence of AI – impacting 10.5 million workers.

              The findings come from a new report – Harnessing the Power of AI: The Demand for Future Skills – from global recruiter Robert Walters and market analysis experts Vacancy Soft.

              Ollie Sexton, Principal at Robert Walters comments:

              “As businesses become ever more reliant on AI, there is an increasing amount of pressure on the processes of data capture and integration. As a result, we have seen an unprecedented number of roles being created with data skill-set at their core.

              “Our job force cannot afford to not get to grips with data and digitalisation. Since 2015 the volume of data created worldwide has more than doubled – increasing (on average) by 28% year-on-year.

              “Now is the perfect time to start honing UK talent for the next generation of AI-influenced jobs. If you look at the statistics in this report we can see that demand is already rife, what we are at risk of is a shortage of talent and skills.”

              Demand for Data Professionals

              IT professionals dedicated to data management appear to be the fastest growing area within large or global entities, with volumes increasing ten-fold in three years – an increase in vacancies of 160% since 2015.

              More generally speaking, data roles across the board have increased by 80% since 2015 – with key areas of growth including data scientists and engineers.

              What has been the most interesting to see is the emergence of data scientist as a mainstream profession – with job vacancies increasing by a staggering 110% year-on-year. The same trend can be seen with data engineers, averaging 86% year-on-year job growth.

              Professional Services Hiring Rapidly

              The rise of cybercrime has resulted in professional services – particularly within banking and financial services – hiring aggressively for information security professionals since 2016, however since then volumes have held steady.

              Within professional services, vacancies for data analysts (+19.5%), data manager (+64.2%), data scientist (+28.8), and data engineer (+62%) have all increased year-on-year.

              Top Industries Investing in AI

              1. Agriculture
              2. Business Support
              3. Customer Experience
              4. Energy
              5. Healthcare
              6. Intellectual Property
              7. IT Service Management
              8. Manufacturing
              9. Technical Support
              10. Retail
              11. Software Development

              Tom Chambers, Manager – Advanced Analytics and Engineering at Robert Walters comments:

              “The uptake of AI across multiple industries is bringing about rapid change, but with that opportunity.

              “Particularly, we are seeing retail, professional services and technology industries’ strive to develop digital products and services that are digitally engaging, secure and instantaneous for the customer – leading to huge waves of recruitment of professionals who are skilled in implementing, monitoring and gaining the desired output from facial recognition, check-out free retail and computer vision, among other automation technologies.

              “Similarly, experimental AI is making huge breakthroughs in the healthcare industry, with the power to replace the need for human, expert diagnoses.

              “What we are seeing is from those businesses that are prepared to invest heavily in AI and data analytics, is they are already outperforming their competitors – and so demand for talent in this area shows no signs of wavering.”

              To download a copy of the report click here.

              In a world awash with a seemingly never-ending list of technology buzzwords such as automation, machine learning and Artificial Intelligence…

              In a world awash with a seemingly never-ending list of technology buzzwords such as automation, machine learning and Artificial Intelligence (AI) to name a few, AI is one such technology that is moving away from simple hype and stepping closer to reality in procurement.

              Here, CPOstrategy looks at 5 ways in which AI is being utilised in procurement…

              This featured in the August issue of CPOstrategy – read now!

              Efficiency and accuracy

              Procurement, by its very nature, is tasked with handling huge quantities of spend and with spend comes spend data. Often described by leading CPOs as a repetitive task, understanding and sorting that spend data is now being achieved through the implementation of AI.

              Through the use of AI, procurement teams can remove human error, increase efficiency and realise greater value from spend data.

              Chatbots

              One of the biggest ways in which AI is being implemented around the world is in the customer interaction space. In telcos, for example, customer support can now be handled via a highly developed AI chatbot that uses legacy data and context to provide real-time, and unique, solutions for customers.

              In procurement, chatbots follow a similar path for both internal and external customers.  With tailored and context-aware interactions, chatbots create an omni-channel user experience for all stakeholders in the procurement ecosystem.

              Supplier risk identification

              Procurement and risk go hand in hand and one of the biggest risks is identifying and working with the right partner. Working in partnerships, which ultimately proves to be a failure, can be extremely costly and so AI is now being used to reduce the risk of failure.

              Machine Learning technology, powered by AI, captures and analyses large quantities of supplier data, including their spend patterns and any contract issues that have emerged in previous partnerships, and creates a clearer picture of a supplier in order for the procurement teams to be able to identify whether this particular partner is right for them – without spending a penny.

              Benchmarking efficiency

              Benchmarking is key to any organisation’s ambition to measure and continuously improve its processes, procedures and policies. In procurement, organisations such as CIPS are used as examples of best practice in which procurement functions all over the world can benchmark against and identify any gaps.

              Similar to supplier risk identification, AI can be implemented within ERP systems to analyse the entirety of data that passes through procurement and present this key data in easy to digest formats.

              Examples include data classification, cluster analysis and semantic data management to help identify untapped potential or outliers in which procurement teams can improve their processes.

              Purchase order processing/Approving purchasing

              Procurement has evolved from its traditional role as simply managing spend into a strategic driver for a number of organisations all around the world.

              As the role of the CPO has changed, technology such as AI has been implemented to free up their time from the menial tasks (such as PO processing and approving purchases), allowing them to spend more time in areas of growth. 

              AI software can be used to automatically review POs and match them to Goods Receipt Notes as well as combining with Robotics Process Automation (RPA) to capture, match and approve purchases through the use of contextual data. This contextual data allows AI to identify and make decisions based on past behaviour.

              Liked this? Listen to Natalia Graves, experienced Chief Procurement Officer, discusses the complexities of digital transformation in procurement!

              By Robert Douglas, Europe Planning Director at Adaptive Insights, a Workday company Now, more than ever, agility is the currency…

              By Robert Douglas, Europe Planning Director at Adaptive Insights, a Workday company

              Now, more than ever, agility is the currency of success. And while agility may be about responding intelligently to the changing nature of the marketplace, those responses must be rooted in a plan. Today, many organizations leverage newer technologies in the cloud for planning, having moved away from manual spreadsheets. And while the cloud offers greater collaboration and the ability to easily combine both historical and real-time data, it’s just the beginning. Digital transformation is changing and will continue to change the definition of best practice planning in organisations. As such, the next step for business planning revolves around two key areas—advancements in AI and machine learning, and increased automation.

              The power of ‘what if’

              What-if scenarios are already incredibly powerful for strategic decision-makers. Organisations can model different versions of the future based on historical information and predictive analytics before choosing the best path forward. Consolidating executional data within organisations is the first step in capitalising on future AI opportunities. However, there is a lot more to come. In fact, compared with what AI is going to make possible, scenario planning is still in its infancy.

              Today’s scenario planning is a good proof of concept, but as long as humans are driving the creative process—it relies on people to ask the right questions of the right data—what-if planning is going to be constrained by available resources. The most advanced decision-making today is typically supported by a few best-estimate scenarios—maybe four or five at most. However, in truth, there are many more possible futures to potentially prepare for, and what looks like best practice now is going to seem vastly limited in scope before too long.

              As the volume and variety of available data grows, and access to that data gets easier, AI and machine learning algorithms will make it possible to drill down, consolidate, and leverage incredibly granular information at the highest levels.

              AI and machine learning use cases

              To consider how these AI and machine learning algorithms will work, let’s look at a use case of a CEO aiming to achieve a 40 percent growth target over a two-year period and wants to model what that looks like to present at the annual executive offsite. AI and machine learning-enabled planning could help to quickly and automatically find the optimal growth path, while accommodating any conditions and assumptions on the fly.

              Essentially, the planning system could measure historical performance and recommend a market segment mix strategy, along with the associated budget increases in the specific marketing and sales activities needed to support it. If they then decide they need to cap growth in sales to smaller businesses in order to also expand into enterprises and international markets—while also maintaining expenses at a certain increase—an alternative, optimised model could be quickly created without any manual lifting.

              A future with machine learning

              The future of business planning is not just about thinking bigger—it is about making better decisions and operationalising them faster. That’s where machine learning comes in. Increased automation, driven by algorithms, is going to blur the boundaries between planning, execution, and analysis until planning cycle times have all but evaporated.

              Planners will be able to ask deep, complex strategy questions and see the results modelled in real time. As the data becomes more trusted, they will be able to make significant, informed, “just-in-time” decisions, confident in the patterns surfaced in the data. And as the line between planning and transactions systems begins to blur and disappear, plans will automatically cascade down to operational departments—even down to individual workflows—in real time.

              ‘Strategy’ will become the province of human-driven innovation while planning becomes an organic, ongoing exercise of continuous improvement inextricably linked to the transactional systems that execute plans.

              Leading the change

              Today finance acts as the central junction within business planning and is, therefore, a natural steward for change, helping normalise new habits and behaviours for the rest of the organisation. As such, there is a strong case to be made for finance teams to double down on their new position as stewards of change by acting as transformation leaders—both for existing processes, and for future, unknown developments.

              Finance’s role will change significantly in order to leverage technology developments in the data-driven, AI future. Driving collaboration with business partners, breaking down data silos, and embracing new technologies and processes to keep pace with today’s rapidly changing business environment will be key. The result will be an augmented, intelligent planning process that delivers true business agility.

              Everyone wants to implement Artificial Intelligence (AI) and Business Intelligence (BI) solutions. AI alone is anticipated to generate $15.7 trillion…

              Everyone wants to implement Artificial Intelligence (AI) and Business Intelligence (BI) solutions. AI alone is anticipated to generate $15.7 trillion in GDP by globally 2030, and as this market grows, AI and BI will shift from industry buzzwords, to key market differentiators, before eventually becoming the new normal in the corporate landscape.

              Yet bringing AI and BI on board is a big leap if it’s your first major data project. Stibo Systems’ Claus Jensen, Head of Emerging Technology, comments on the role of MDM as a vital foundation to implement emerging data technology.

              Most CEOs don’t trust their own data.*

              Let that sink in for a moment.

              Almost every business is looking to data solutions to fuel the next phase of growth and innovation. AI and BI are firmly on the agenda, yet a report by Forbes Insights and KPMG found 84% of CEOs are concerned with the quality of the data they’re basing their decisions on.

              That’s a significant disconnect. Businesses at board level want to implement ‘next generation’ data projects, but don’t trust the data that will be fed into them. For CDOs and other data leads, this presents a difficult situation. They need to meet demand for cutting-edge data projects, knowing that there is a certain level of mistrust in the data at their disposal.

              For many CDOs, that mistrust isn’t limited to the CEO. Think about the data you are currently processing: how confident are you that it’s being accurately sourced, entered, saved, stored, copied and presented? How well do you know that data journey once it leaves your sphere of control? Are you certain that a single source of truth is being maintained?

              The data gold rush

              It may only be major data breaches that make the headlines, but in the global gold rush for data, too many businesses fail to accurately extract, store and interpret data.

              Mistakes are made at every stage in the process – in fact, so bad are we at processing data, a report by Royal Mail Data Services claims that around 6% of annual revenue is lost through poor quality data.

              It’s equally bleak in the US, where Gartner’s Data Quality Market Survey puts the average cost to US business at $15 million per year.

              Despite this, we’re rapidly moving the conversation from data capture to artificial intelligence (AI), business intelligence (BI) and connected devices (IoT) – and for good reason.

              Putting aside the issue of bad data (we’ll come back to that), businesses now have access to more data than they can handle – according to SAS’ Business Intelligence and Analytics Capabilities Report, 60% of business leaders struggle to convert data into actionable insights, and 91% of companies feel that they are incapable to doing it quickly enough to make useful changes. 

              Business Intelligence and Analytics Capabilities Report

              In large businesses, where data streams are blended from many sources, machine learning can help data scientists monitor figures to flag outliers, irregularities and noteworthy patterns.

              Once flagged, business leaders can use BI to bring those patterns to life, helping pave the way for the most appropriate, and profitable, action.

              Stibo Systems’ Head of Emerging Technology, Claus Jensen, believes it’s only a matter of time before we see AI regularly used within business product features – with machine learning automating tasks thanks to effective data interpretation.

              Jensen and his team are working at the forefront of data: building master data management solutions in conjunction with AI and BI. “We’re entering into a new era of data analytics,” says Jensen. “Data scientists aren’t going away, but they can do more and more high-level work as certain use cases are solved by AI.” 

              One of these use cases is machine learning-based auto classification. “For retailers onboarding thousands and thousands of new products every month, it’s really time consuming for them to have the vendor categorise the product into the vendor taxonomy.

              “Machine learning can automate this based on product description and image.”

              Running before we can walk

              As exciting as this sounds, businesses eager to install new uses for data often face significant challenges: their data isn’t watertight, or it’s siloed, often both.

              In a piece penned for the Financial Times, Professor of Economics at Stanford Graduate School of Business, Paul Oyer, wrote: “Smart managers now know that algorithms are as good as the data you train them on.” In other words, AI (and analytics for that matter) can only ever be as good as the date you feed it.

              Which brings us back to the question of trust. What needs to happen for CEOs to trust their own data?

              While there’s no single answer to this question, a master data management (MDM) solution is a good place to start.

              “You can think of MDM as the foundation, a layer, that provides a single source of the truth for data,” explains Jensen. “Analytics and machine learning is only useful if the data you’re working on is accurate. That’s where MDM comes in; it ensures information presented, and actions taken, are based on fact and reality.

              “Otherwise, business analytics is just a nice and colourful way to look at bad data, and what’s the point in that?”

              To find out more about how MDM can turn data into business value through actionable insights, forming a solid foundation to AI and BI, visit https://www.stibosystems.com/solution/embedded-analytics-platform.

              In today’s market expectations are growing and the stakes are high, with one mistake potentially costing a retailer their reputation….

              In today’s market expectations are growing and the stakes are high, with one mistake potentially costing a retailer their reputation. Due to this level of risk, brands find reducing their hands on approach to processes difficult, but what they don’t realise is that technology such as Artificial Intelligence and Machine Learning could prove to be their hero, not their villain. Entrusting their data and brand values to such technologies may seem like a scary step, but as David Griffiths, Senior Product Marketing & Strategy Manager, Adjuno, discusses, it’s one that will free up retail teams to add value and cut costs.

              In AI should we trust?

              There is a great deal of obstacles to overcome when it comes to the stigma attached to AI. A key challenge facing the progression of this technology is that individuals simply do not trust it. The fear of the unknown is one concern that pops up most commonly, with people battling a perceived perception that those who use this technology will lack control.

              But a new age of retail is approaching and there is now an even greater need for brands to define their processes in order to keep up. Consumers want to receive products that are of a high-quality and they want to receive them now. These expectations are taking us beyond the traditional methods of retailing and leading us into a world immersed in technology, a world that benefits from the helping hand of AI.

              Informing key decisions

              With AI, retailers will be able to gain valuable insights in warehouse management, logistics and supply chain management, and make more informed and proactive decisions. This technology makes it easier to analyse huge volumes of data in an efficient fashion, helping to detect patterns and providing an endless loop of forecasting. Using this knowledge to identify factors and issues impacting the performance of the supply chain, such as weather events, retailers will be able to take a forward-thinking approach to decision-making. An approach that will lead to reduced costs and delays. 

              By extending human efficiency in terms of reach, quality and speed, this technology can also help to eliminate the more mundane and routine work that’s faced by employees across the retail spectrum. From tackling flow management by assessing key products to ensuring there is enough stock available to improving production planning, a more informed use of time will help equip brands to face every consumer request and demand.

              This is particularly important for those brands whose product line extends further than apparel wear, and steps into the realm of hardware. With diversity comes a need for more proof points and in turn, an extended volume of data. Retailers will be battling to work across an even greater number of suppliers and distribution centres, and accommodating the expectations of a larger customer base. Considering this, it is fundamental that every last bit of data is refined and utilised to streamline processes. AI is providing retailers with a platform to do this, offering the potential for significant changes across the entire product journey.

              A data conundrum  

              The benefits of using AI to consolidate data are endless. Traditionally, teams have relied on spreadsheets to collate information, hindering their ability to forward plan. With AI this is no longer the case, a much more accurate picture of the hero products, sizes and colours likely to sell, can be achieved by looking at multiple scenarios in real time and pulling them together.

              This doesn’t mean that AI will replace creative buying teams. AI doesn’t forecast trends, it can’t predict what consumers will be buying in 2020, it can only report on the product lines. It can however help buying teams assess partners, analyse stock patterns, track costs, enable capacity planning and help optimise shipments. This data is invaluable to teams, especially for any new buyers who may need extra guidance. 

              Conclusion

              AI is set to transform the retail scene as we know it. But in order to make implementation a success, there shouldn’t just be a focus on the evolution of data management, there must be an evolution of mindsets too. After all, if a retailer fails to jump on board with AI and embrace a new era of change, then their customers will be the ones who suffer.

              Companies that use voice plus touch interactions with their products and services are actually seen as less trustworthy and less…

              Companies that use voice plus touch interactions with their products and services are actually seen as less trustworthy and less engaging by their users, according to new research from emlyon business school.

              The research, conducted by Margherita Pagani, Director of the AIM Research Center on AI in Value Creation and Professor of Digital Marketing at emlyon business school, and colleagues from ESSCA School of Management and Florida State University, College of Business, analysed the impact and differences between ‘touch’ interaction and ‘touch and voice’ interaction on personal consumer engagement and brand trust.

              The researchers created two separate experiments, focused on a utilitarian product and then a hedonic product, both of which had over 90 participants belonging to generation Y, which is commonly equipped with the latest smartphones and frequently use them for business interactions. For both experiments, participants had to interact with the brand using their smartphone including a phone call to the company to ask a specific set of questions.

              One group was required to interact with the brand through the smartphone using a touch-only interaction, and the other used both touch and voice interaction – either Apple’s Siri or OK Google. After interacting with the company, participants were asked to rate their customer experience. The participant’s answers were then measured to evaluate personal engagement with the tasks, their level of trust with the brand and their privacy concerns.

              The researchers found that participants who used the touch-only interaction experienced a much higher level of personal engagement with the brand compared to those who used the touch plus voice interaction.

              Prof. Pagani says,

              “Many companies have introduced new AI products that use voice-activation such as Amazon’s Alexa, Google’s Home Assistant or Apple’s Siri. These have been introduced in order to increase customer experiential engagement, stimulate the interaction and collect more data that allow to better personalise the experience through machine learning.  However, our study shows that in the initial phase of adoption, adding voice recognition actually has the opposite desired effect. Even if voice may be considered as a way to develop a much more natural interaction, the level of cognitive efforts required to the brain using two sensory modes (voice and touch) are higher. Therefore, consumers find it harder to completely engage with the product and can easily be distracted”.

              The researchers also found that participants who used the touch-only interaction felt as though they had more control over the information they shared and therefore had greater confidence in the brand. Users stated that they found it much simpler to input information using only one sensory method; touch.

              “The lack of familiarity with how these digital voice interactions actually work is likely to be the reason as to why consumers are less trusting of brands that use both touch and voice. Whilst the use of touch also garners much more control for a consumer, as opposed to voice”.   The study, published in the ‘Journal of Interactive Marketing’ is the first of its kind to explore the effects of new voice-based interface modes on marketing relationships. Whilst technology multiplies the way that consumers can interact with brands, this study shows that too much interaction can actually harm a company, and offers managers guidance on how to increase personal engagement and brand trust.

              Welcome to the June issue of Interface Magazine! Read the latest issue now! This month’s cover features Gary Steen, TalkTalk’s…

              Welcome to the June issue of Interface Magazine!

              Read the latest issue now!

              This month’s cover features Gary Steen, TalkTalk’s Managing Director of Technology, Change, and Security, Gary Steen regarding the telco’s commitment to thinking, and acting, differently in a highly competitive marketplace…

              TalkTalk is an established telecommunications company that fosters a youthful, pioneering spirit. “I like to think of TalkTalk as a mature start-up,” says Managing Director of Technology, Change and Security, Gary Steen. “We are mature in terms of being in the FTSE 250, with over four million customers, relying on our services every day through our essential, critical national infrastructure. But that said, I definitely think we start our day thinking as a start-up would. What can we do differently? How do we beat the competition? How do we attract great talent? We’ve got to come at this in a different way if we are going to succeed in the marketplace. We are mature, but we think like a start-up.”

              Elsewhere we speak to Natalia Graves, VP Head of Procurement at Veeam Software who reveals the secrets to a successful procurement transformation. Graves was tasked with looking at the automating, simplifying, and accelerating of Veeam’s procurement and travel processes and systems around them, including evaluating and rolling out a company-wide source-to-pay platform. “It has been an incredible journey,” she tells us from her office in Boston, Massachusetts. We also feature exclusive interviews with PTI Consulting and cloud specialists CSI.

              Plus, we reveal 5 of the biggest AI companies in fintech and list the best events and conferences around.

              Enjoy the issue!

              Kevin Davies

              IPsoft has introduced 1Bank, the first conversational banking solution featuring virtual agent Amelia. It has been rated the top virtual…

              IPsoft has introduced 1Bank, the first conversational banking solution featuring virtual agent Amelia. It has been rated the top virtual agent in conversational AI by Everest Group.

              Chetan Dube, CEO at IPsoft, commented: “With 1Bank we provide the most humanlike digital experience in the marketplace, built from the knowledge we’ve gained serving six of the world’s leading banks with conversational AI. We are giving banks the possibility of providing customers with their own personal banker around the clock.”

              1Bank answers FAQs, but also resolves complex customer needs, by understanding customer intent. It can also switch context, mid-conversation. Its machine learning Learning (ML) abilities also mean that 1Bank can improve over time.

              Some of the tasks 1Bank can carry out are:

              • advising on unpaid bills, proactively informing customers of an incoming bill and communicating any insufficient funds, making a money transfer and asking if the customer wants to set up payment for the bills when they are due.
              • recommending and setting up recurring payments, making payments from different accounts, opening and closing accounts.
              • helping customers locate transactions.
              • assisting with individual and potentially fraudulent charges on credit cards and disputing them, getting a new pin, getting a balance transfer or applying for a new credit card.
              • creating travel alerts after a customer made an airline purchase and proactively recommending the next step, such as, when traveling to exchange and withdrawing cash.

              1Bank can integrate with existing tools and interfaces, and it can be added to existing applications to help customers quickly access the information and service they need. This includes mobile apps, desktop or kiosk apps, website modules, or within consumer chat applications, such as Facebook Messenger and Amazon Echo.

              It is a measure of how much we take sophisticated technology for granted that the appearance of a pop-up chatbot…

              It is a measure of how much we take sophisticated technology for granted that the appearance of a pop-up chatbot screen, asking questions and providing sensible responses, is no longer considered remarkable.

              Chatbots today inhabit websites, intranets, apps, and social media platforms, and have become so ubiquitous as to become almost invisible. Interacting with a text screen is a natural activity, and most users don’t seem to care much about whether the other side of the conversation is a human or a bundle of code.

              From a corporate perspective, chatbots can be a win/win. Increasingly reliable in their responses and cheap to operate, they are available night and day and are instantly scalable. Whether your site or app has one visitor a day or thousands, the bot is always eager to help.

              We’ve come a long way from the disastrous early attempts at providing AI assistance – remember Microsoft’s paperclip? – but what a good chatbot does today is much the same as that much-loathed animated character: identify what a user is trying to do, and offer appropriate help.

              Artifical intelligence

              You will have heard of the Turing Test, which held that if a computer could provide responses that were indistinguishable from those of a human, the machine had to be considered intelligent. Are we there yet?

              Despite some well-publicised claims, the answer is still, probably, no. In 2014 a program called Eugene Goostman successfully tricked Turing Test judges into believing it was a 13-year-old Ukrainian boy. This controversial victory is still a failure, though, because nobody expects or wants to find an adolescent behind a real-world help screen.

              More relevant is the Loebner Prize for the most convincing chatbot. This awards bronze medals each year to the best contenders, but has never made a silver (text) or gold (audio visual) award – the equivalent of a Turing Test pass.

              A glance at the best entries from the 2018 competition shows why. Eleven bots were asked 20 questions, winning two points for a human-like answer and one for a plausible response. Out of a maximum of 40 points, the winner scored 27 and the lowest just 12.

              Even simple questions can make the tech fall over. The winner, a chatbot called Tutor by Ron C Lee, answered “Do you know how to make toast?” with “No, we haven’t”.

              Chatbot limitations

              While there remain limits on what a chatbot can convincingly do, this need not be a problem if it is deployed in the right way. Recent research from Penn State University found that while many appreciate an apparently empathetic response from a bot, those who believe machines are actually capable of consciousness do not.

              “The majority of people do not believe in machine emotion, so took expressions of empathy and sympathy as courtesies,” said researcher Bingjie Liu. “However, people who think it’s possible that machines could have emotions had negative reactions from the chatbots.”

              The answer is only to use them for things they are good at, says James Williams, who leads the development of advanced chatbots with Nottingham-based software company MHR. While chatbots are now common in consumer interfaces, he notes, there is much potential in the enterprise space.

              Business bots

              When applied within the company’s flagship human resources (HR) software, Williams says the conversational interface is an excellent way to simplify common transactions. “You’ll hear us talk a lot about reducing friction,” he says, which means anything that slows down a routine interaction.

              An example is an employee submitting an expenses claim, which MHR’s Talksuite does through an AI-driven chatbot. “Taking a picture of a receipt is a natural thing to do, and the AI will recognise the image, understanding the content as well as the context. Bots are really good for processes with lots of rules or lots of steps, and here it just asks a few questions and saves the employee a lot of hassle. Less friction.”

              Knowing when not to deploy a bot can be just as valuable. Williams recounts one client which had deployed a complex chatbot for its newly joining employees, known in HR circles as the onboarding process. “The chatbot went through everything plus the kitchen sink, so the employee was there for 20 minutes or more being interrogated by a machine. It was just awful. A web-based form is a much better interface in this situation.”

              His final advice is to consider the image the bot projects. “Any personality in a chatbot tends to come accidentally, unlike a website or an app. If you let software developers write the conversation, you might end up with a bot that’s actually a bit of a dick. People make judgements on things like language and punctuation. It’s fine to be personable and friendly, but it should be clear when the user is talking to a bot and when any transition to a human interaction takes place.”

              Quest Solution Inc, provides supply chain and artificial intelligence (AI) based machine vision solutions. It has been awarded a project by…

              Quest Solution Inc, provides supply chain and artificial intelligence (AI) based machine vision solutions. It has been awarded a project by a leading supply chain and logistics provider in the US. The release doesn’t detail who the leading supply chain provider is, but it does reveal that the project is valued at around $US7 million.

              A patent that will allow for a robot to live at your home and handle your deliveries has been filed by Amazon. The patent outlines plans for a robot that will completely transform last mile delivery capabilities, even potentially delivering packages in the early hours between 2am and 6am.

              Back to AI, NFI Industries and Transplace are paying attention to this technology through partnerships with firms that add AI capabilities to transportation and distribution. Both companies have announced a partnership with Noodle.ai with the goal of enhancing logistics services and technology capabilities.

              In a video interview with CNBC, Lance Fritz, the CEO of Union Pacific, is concerned that supply chain disruption won’t return to normal. He believes the biggest concern lies in trade and that the challenges with China should be resolved as soon as possible.

              In an interview with Sky News, Peter Schwarzenbauer, BMW board member responsible for Mini and Rolls Royce, has said that the firm will need to think about moving production from the UK in the event of a no-deal Brexit. Remaining would be too costly for the organisation and some production would move to countries like Austria. Toyota shares similar concerns with Johan van Zyl, head of Toyota’s European operations, telling the BBC that Brexit hurdles would ‘undermine Toyota’s competitiveness’.

              Blockchain remains an interesting solution for many in the supply chain and Blockchain Labs for Open Collaboration (BLOC) has recently started working with NYK, a Japanese shopping company, and BHP, a mining company, to establish a sustainable biofuel supply chain using BLOC’s blockchain fuel assurance platform.

              Also in the news: HighJump, a global supply chain solutions provider, awarded five women in its Top Women Leaders in Supply Chain awards; Cryptobriefings Kiana Danial examines whether VeChain can deliver a supply chain solution; Apple releases a supply chain document that reveals how iPhone, airpods and other products are all zero waste; and SIGTTO GM, Andrew Clifton, looks to the LNG supply chain.