3 ways technology can help to strengthen supply chains

Supply chains have rarely known stress like this. Geopolitical turmoil, labor shortages, extreme weather conditions, and demand shifts have combined to create global logistical chaos. The reality is that the pain points we have experienced over the past two years are unlikely to ease in the near future.

In today’s constantly changing environment, companies can't rely on doing things 'just in time'. They are subject to fluctuations, both on the demand and the supply side, resulting in variations of forecasts and supply chain constraints. A traditional static process design with a single critical path can simply not cope with this complexity. What's more, teams are working with imperfect data and complex IT systems, and there are growing expectations for supply chains to lead efforts to tackle the climate crisis. The result is that only 1 in 5 companies have reached a sufficient level of supply chain resilience.

This is where technology comes in. Supply chains with process mining and Artificial Intelligence (AI) or machine learning at their core create visibility throughout the whole supply chain. This allows them to monitor and optimize the supply chain continuously, which in turn allows organizations to reduce complexity and operate more efficiently, both financially and ecologically.

Here are three practical steps organizations can take to ramp up the resilience of their supply chains.

The vast majority of organizations have a wealth of data, but are unable to use it effectively to make decisions. Consequently they often revert to doing things the way they have been in the past. Without data-backed insights it is nearly impossible to find the root causes of friction in your supply chain. Revolutionary software solutions, such as process mining, allow leaders to unlock the power of their data.

Take global shipping as an example: At least 60 million containers (25% of all shipping containers) are shipped empty every single year. The underlying issue is that businesses typically run their inventory, production, order management and shipping processes in isolation. In other words the shipping software does not know if there are other orders in the pipeline to fill the remaining capacity. Instead of letting containers travel empty, an organization could use technology to connect insights from all processes to monitor shipping capacity in real time and dynamically make adjustments, such as bundling the order. It is a win-win: fewer containers means less costs and fewer carbon emissions. One Celonis customer, a consumer packaged goods company, is doing precisely that, and as a result they require 300 fewer truck transports per week than they did before.

AI capabilities are increasingly embedded into supply chain management to assist humans with making decisions in sophisticated planning activities, such as demand forecasting, purchase lead time determination, and many more. According to a survey conducted by IBM, more than half of Chief Supply Chain Officers are already using AI.

This is underpinned by three trends: few-shot learning techniques, where a foundational model can be adapted to specific supply chains with relatively small amounts (by consumer web standards) of training data, is making the AI predictions more tailored to the target planning situation; tracking and digitalization through sensors; and digital twin technology.

As AI is evolving rapidly, process mining is becoming exponentially more powerful. Business operations, in particular supply chain management, will benefit significantly from this technology.

By building their supply chains to be more sustainable, leaders will also boost their top and bottom lines. Take inflation as an example: inflationary pressures can be relieved with sustainable supply chain approaches that lower the costs of emissions and waste, while increasing revenue through customer loyalty, and avoiding fines attached to ever-stricter regulatory requirements. Optimizing logistics with machine learning leads to accurate delivery times that keep customers coming back.

Similarly for the bottom line, businesses can lower the risk of human error and improve order accuracy and cycle times with process mining. This results in minimal returns and cancellations, which reduces waste and transport emissions.

Technology has repeatedly emerged as a source of solutions for some of the world’s greatest challenges. Business leaders must now tap into it once more to ramp up the resilience of global supply chains. They need to build supply chains that are efficient, data-led, transparent, and sustainable.