Author

Dan Brightmore

Published

11 September 2023

Estimated Read time

5Mins

Read in brochure format

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

Author

James Bristow

Published

25 January 2021

Estimated Read time

5Mins

According to the latest ONS figures, the impact of Covid-19 restrictions on the physical retail sector has been mixed. Stores…

According to the latest ONS figures, the impact of Covid-19 restrictions on the physical retail sector has been mixed. Stores selling hardware, paints and glass, for example, saw a 13% increase in the value of retail sales compared to last year. Others have been hit particularly hard – with clothes store sales down by more than a quarter (26%) in the same time frame.

The forthcoming wave of vaccinations promises to restore the UK’s economy to a more stable position. Nonetheless, we must consider the possibility that changes in consumer behaviour may linger even when lockdowns and social distancing are a thing of the past, as well as how different sub-sectors within the industry will be affected.

Let’s therefore look at two opposing, but equally possible scenarios on the road ahead.

Scenario A – Opening the floodgates

After months of being cooped up at home, customers flock to town centres, industrial parks and shopping centres to exercise their freedom to purchase goods in-person. Sales volumes increase, but supply chains become stretched due to spikes in product demand and store inventories become more difficult to effectively manage.

In addition, disruption to both the need and availability of workers in the months prior leaves stores understaffed, leading to long queues and disgruntled customers. Finally, customers who for months have been encouraged to go cashless are now making far more card and contactless payments, leaving some POS systems struggling with the uptick in data traffic and leading to more frustration for staff and customers alike.    

Scenario B – The high street ghost town

For many, shopping online during the pandemic switched from something people wanted to do to something people needed to do. As a result, those who were previously sceptical or unfamiliar with technology (or who simply preferred shopping in-person) had to familiarise themselves with the process. Of course, although many within this group may still be averse to e-commerce today, we must assume that at least some will use their newfound familiarity to continue shopping online in the post-Covid era.

In this scenario, customers new to e-commerce have been swayed by the user-friendliness, low prices and fast delivery on offer online. As a result, footfall on the high street struggles to recover to pre-pandemic levels, creating a tough environment for the small independent retailers who compete with the online giants.

Preparing for every outcome

While these two scenarios are diametrically opposed, the Internet of Things (IoT) could help address some of the issues described in both situations. Comprising a dynamic network of sensors, devices and equipment, the IoT makes it possible to view and interact with physical objects as easily as files and folders on a computer. In other words, the IoT creates a digital overlay that sits across the physical infrastructure of retail stores, effectively facilitating the agility of online shopping in a physical space.

It will require investment, but securing the future is a goal that pays dividends. Here we look at the solutions the IoT has to offer in these two scenarios.

Solution A – Unlocking efficiency at every stage of the supply chain

Preparing to mitigate the negative outcomes in this scenario requires retailers to take a hard look at the systems they have in place, identify areas in urgent need of greater efficiency, and implement new IoT tools to address them:

  • Real-time supply chain – inventory sensors and POS data are integrated into a direct communication system with supply chain partners, triggering automated manufacturing and production systems and adjusting stock delivery schedules accordingly.
  • Data-driven decisioning – capacity sensors linked to data analytics platforms not only track the number of customers in-store, but analyse seasonally-adjusted data relating to the length of time customers spend in the aisles and predict where and when staff will be needed.
  • Robotic process automation (RPA) – from processing supplier deliveries to quarterly stock counts, RPA systems automate time-consuming tasks that happen behind the scenes, freeing up staff time for better workforce scheduling and more focus on customers.

Solution B – In-store customer experience unmatched by online retailers

Innovations such as live product tracking and same day delivery have recently tipped the customer experience race in online retailers’ favour. To attract new customers and retain their business, brick-and-mortar stores must emulate the dynamic, digital and personalised experience offered by their online counterparts:

  • Interactive digital displays & kiosks – positioned at the store entry, customers can benefit from an optimised in-store journey and a highly personalised experience by viewing commonly bought items, their location within the store and in-the-moment marketing offers based on purchase history.
  • Roaming POS – queuing is eliminated as tablets carried by staff process customer payments anywhere in the store. In addition, RFID scanners built into trolleys and baskets can total large volume purchases in real-time, without needing to take a single item out to scan.
  • Customer application integration – in-store geotargeting systems can link via Bluetooth to customer-facing smartphone applications to help locate specific items and provide other useful pieces of information, such as stock levels, current offers and the location of staff.

LTE & SD-WAN branch networking: laying the foundations for the future of physical retail

Regardless of which scenario becomes a reality, any subsequent IoT strategy must begin with a reliable, secure and agile network. The first step is cutting the cord with fixed broadband connectivity and setting up a private in-store network running on LTE. Also known as wireless WAN (WWAN), this solution offers retailers greater levels of flexibility thanks to out-of-the-box connectivity and unparalleled reliability through multiple network channel management.

The second foundational requirement for retail IoT is SD-WAN. With the sheer quantity of network applications running in most branches, cloud monitoring and troubleshooting features – including automated alerts – SD-WAN enables retailers to cost-effectively manage WAN conditions at widespread locations. Crucially, SD-WAN also allows secure VPNs to be established in a matter of minutes, providing robust protection for devices and sensitive information, such as customer payment data.

Survive and thrive in the future of retail

The past year has been an uphill struggle, not least for retailers contending with limited footfall in their physical stores. Investing in new technology may not be top of mind for all retail businesses in the immediate future. But for those who are able and willing to make small adjustments to innovate may find they are able to unlock efficiencies in their supply chain, improve their in-store experience and attract and retain new customers once lockdown restrictions start to ease.

Author

Dale Benton

Published

25 August 2019

Estimated Read time

5Mins

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!

Author

James Wickes

Published

1 March 2019

Estimated Read time

5Mins

The Internet of Things (IoT) allows devices to send data to cloud storage, where it can be combined with other…

The Internet of Things (IoT) allows devices to send data to cloud storage, where it can be combined with other data, analysed and interpreted using techniques such as predictive analytics, artificial intelligence and deep learning. The resulting knowledge, including identification of patterns and trends, reveals new insights that have the potential to touch every aspect of our lives. Many of us are already using IoT devices in our homes, from smart sensors to voice activated virtual assistants.

However, I believe that to achieve the IoT’s full potential we must add visual data to create the Visual IoT (VIoT). Sight is the most important of our senses, so integrating visual information with other IoT data streams is immensely powerful. It helps a system or device better understand and interpret objects and movement as well as its surroundings based on the visual data it can ‘see’.

We now have the processing power, bandwidth, data storage capacity and computing ability to enable fast, reliable analysis of visual data to a standard that makes it commercially viable. The result, according to McKinsey, is that video analytics will see a compound annual growth rate of more than 50 percent over the next five years, contributing to a potential economic impact for the IoT of $3.9 trillion to $11.1 trillion a year by 2025.

Doing this does not require hundreds of new cameras. Huge volumes of visual data already exist, collected by the analogue and digital cameras that surround us, from traffic and numberplate recognition cameras to CCTV systems. Most of this visual data, however, is currently collected for a single purpose, and only a tiny percentage is ever viewed. Combining it with other IoT data streams and adding analytics would make it immensely valuable.

Our research suggests there are currently some 8.2 million surveillance cameras in the UK, producing 10.3 petabytes2 of visual data every hour. Consolidating this in a cloud infrastructure and combining it with other data sets, from static data such as grid references to dynamic ones such as weather data, could provide clear visual insight into what is happening, why, and what might happen next. Applications could range from speeding up the response to motorway accidents and managing city centre parking to working with people flows in transport hubs and caring for vulnerable people.

We are already seeing companies such as Vodafone integrating cloud-based CCTV with building security systems, adding visual verification to intruder alarms. Such systems can enable home security companies and the police to check properties visually when an alarm goes off and quickly ascertain whether a break-in has occurred. This can provide significant time and cost savings while enabling immediate action to be taken if appropriate.

Cameras combined with analytics can be configured to map patterns of movement in real time, helping to understand the number and flow of people in public spaces such as stations, airport terminals, tourist attractions and shopping malls. This could be used to automate the management of people flow systems, for example changing the direction of escalators and lifts as customer behaviour patterns change during the day. In many cases cameras can be used simply as a sensor with analytics to verify something, for example that the object at the barrier is a red van with a particular numberplate, and take action, such as lifting the barrier, without necessarily recording the image.

Another application is city centre parking. According to the British Parking Association, 30 percent of city centre drivers are simply looking for a parking space. Cameras could monitor roadside parking spots, letting a central system know which are unoccupied. Location data could be shared with a driver’s routing app, with visual data made accessible so they know what they are looking for. It should even be possible for the driver to book a space and authorise payment to be made automatically, with length of stay calculated and payment taken when they leave.

Another exciting possibility is to speed up the response to road traffic accidents. The VIoT offers the possibility of combining data from motorway cameras to help pinpoint the precise location of accidents and to tell first responders in real time about any hold-ups when they are en route. This information could be combined with in-vehicle routing systems to ensure their swift arrival.

Applying analytics to visual data will lead to further applications by revealing patterns and predicting future behaviours. This intelligence will help organisations optimise systems, improve safety and make better, faster, more appropriate decisions. The good news is that machines are doing the ‘watching’ – not people.

Analytics combined with AI and IoT can also play a key role in helping protect more vulnerable members of society. We are already seeing cameras used in care situations to detect pre self-harming or suicidal behaviours, and to monitor individuals to ensure they are being well treated (with appropriate permissions). In the future older people living in their own homes could benefit from cameras which record where and when they are active. Periods of inactivity might indicate a problem and could trigger alerts to family or carers. Cameras at stations could be trained using AI to spot behaviours indicative of potential suicides and issue appropriate alerts to staff.

The big issue is of course privacy, but the right analytical software enables automatic decisions to be made without human involvement, while the General Data Protection Regulation (GDPR) provides additional data protection. There are also many applications in sectors such as the environment that will not involve individuals at all.

James Wickes is cofounder and chief executive at Cloudview

Further information is available in the White Paper VISUAL IoT: WHERE THE IoT, CLOUD AND BIG DATA COME TOGETHER.