The construction industry is one of the sectors with the lowest level of digitisation to date. Given the scale of the sector, its considerable contribution to the global economy and its impact on the environment, it’s somewhat surprising that this should be the case.
Few within the industry would doubt that an increase in digitisation would have many positive effects. The efficiency and sustainability of the construction supply chain in particular would benefit from this, according to the assessment of industry experts. A practical solution for this is offered by modern, software-based construction planning systems that rely on artificial intelligence (AI).
AI powered solutions to today’s challenges
No industry can currently ignore the issue of sustainability. The construction sector in particular has a lot of catching up to do here and must react accordingly. It’s a lesser-known fact that the construction industry is responsible for around 38% of global CO₂ emissions. Given its carbon footprint, arguably it has a duty to decarbonise to a more palatable level.
Therefore, innovative and promising concepts that contribute to achieving climate protection goals are urgently needed.
An indispensable prerequisite for achieving this goal, is the consistent digitisation and automation of processes. The main goal here is to relieve the burden on supply chains and thereby also reduce CO₂ emissions. However, the construction industry in this country does not yet have the reputation of being a digitalisation pioneer. The processes are still very rigid. This is especially true when it comes to planning the requirements of building materials and designing logistics chains.
Most processes are still based on paper documents, which hinders consistent processes. Waybills and delivery documents are often still signed by hand and can easily get lost. The relevant data must be entered manually into IT systems, which presents many sources of error.
In addition, little attention is paid to the environmental friendliness and CO2 footprint of materials when selecting them. There is also usually no comprehensive overview of which building materials are needed in what quantities, where and when. This leads to complicated and often unnecessary transport routes for trucks and other vehicles.
Material requirements planning: the key to efficiency and sustainability
In order to increase the efficiency of workflows here, maximum transparency is required along the entire supply chain. Those responsible must carefully determine how to adjust the ordering of materials to actual requirements.
This is the only way to effectively counteract excessive waste of valuable resources. According to GIRI somewhere between 10% and 25% of project costs are lost through errors. That’s a double-digit percentage of building materials ordered unnecessarily or used incorrectly. This leads to inefficiencies in construction, drives up costs and is an obstacle on the way to greater sustainability. However, optimised demand planning alone is not enough – attention should also be paid to where the material comes from. It is important to keep in mind that building materials such as concrete are produced in different regions and countries according to different standards. This has a significant impact on quality and therefore also influences the CO2 footprint.
Therefore, it makes sense to purchase materials from regional suppliers. This shortens transport routes, which in turn conserves resources and minimises pollutant emissions.
AI-based construction planning for maximum process efficiency
In order to adequately address all of those challenges, well-thought-out project planning tools are required that are optimised with regard to the processes in the construction industry.
The solutions work particularly effectively when they are equipped with AI. For example, the technology can independently recognise certain conflicts in the procurement workflows. This is the case, for example, when ordering building materials that do not match the type or quantity of the building in question. Here, AI can raise the alarm and initiate an optimisation of the processes. The result? Significantly less material waste and unnecessary transport, which noticeably relieves the burden on the supply chain.
Another advantage of AI-based planning systems is that they can handle large amounts of data extremely well, analyse them comprehensively and draw the right conclusions from them. By way of example, large construction companies work on numerous different projects in parallel and cooperate with a large number of suppliers who are spread across the entire country. The AI-supported evaluation of relevant data makes it possible to quickly see which delivery partners are suitable for a specific construction project.
This brings more efficiency to the supply chain. However, it is important to always keep an eye on the entire ecological balance. This includes the production of the materials, the type of transport and the delivery distance. It is possible that environmentally-friendly concrete with a longer journey proves to be more sustainable when compared to a conventionally produced building material from the neighbouring town.
Such an overall view requires a large amount of valid data, which can be evaluated quickly and thoroughly using an AI solution, thus paving the way for sustainable and economically sensible decisions.
Construction companies and suppliers benefit from demand forecasts
In addition, AI-supported planning tools based on big data analyses can be used to precisely predict future demand for building materials. Depending on the project workload, those responsible in the construction companies can realistically estimate how much concrete, gravel or wood will be needed in the coming weeks.
This improves the coordination of logistics processes, optimises the use of budgets and makes a significant contribution to cost savings. On the other hand, the manufacturers of building materials also benefit; they can use demand forecasts to closely monitor the market and align their production capacities accordingly.
The current share of renewable energies in the power grid can also have an influence on this. If, for instance, a lot of solar and wind energy is currently being fed into the grid, the production rate can be adjusted and increased accordingly. If there is less surplus energy, manufacturers can reduce production again.
Ultimately, this increased flexibility has a positive effect on sustainability and climate protection.
AI tools determine the future of the construction industry
The analysis of large amounts of data and the targeted use of AI-based planning tools will significantly drive the digitalisation of the construction industry in the future – that much is certain. In this way, a variety of positive effects can be achieved, such as an efficient and sustainable supply chain.
- AI in Supply Chain