Supply chain forecasting and AI in supply chain planning

By Tanja Zimmermann

In a complex and dynamic world, it is increasingly essential for companies to plan their supply chain comprehensively. Globalization and increasing crises are amplifying these existing challenges. The abilities to forecast demand and, based on this, to forecast purchasing and procurement are becoming all the more difficult and important at the same time. Artificial Intelligence offers corresponding possibilities for this. But new types of planning systems must also be designed for this. Are they?

McKinsey conducted a study on the readiness of new IT systems adoption. To do so, it surveyed a dozen supply chain executives, with 90 percent saying they expect to upgrade planning IT in the next five years. Four out of five executives expect to use AI and machine learning in supply chain planning. But there is an important prerequisite for this: if you want to achieve impactful supply chain planning, you also need powerful IT systems. Novel planning systems use AI, machine learning and data analytics to make decisions. As a result, autonomous planning can be enabled. To take advantage of this, the systems need to be suitably modern. What does it actually look like in companies today? In many companies, however, manual workflows and legacy systems prevail. New applications that can meet current challenges in terms of complexity, variety and dynamics are usually not available.

Now, many supply chain managers are finding that they have held on to outdated systems for too long. A new implementation can now be costly and time-consuming. At the same time, this also presents an opportunity to introduce new types of systems. For example, according to the McKinsey study, 20 percent of executives surveyed are already using IT systems modernization to introduce supply chain planning based on AI and machine learning. Sixty percent plan to do so in the future. According to the study, it is important to pay attention to the following points when introducing an IT planning system: A future-oriented process design, a clearly defined vendor selection and an implementation roadmap that first fulfills basic functions. More complicated use cases can then be added in a further step. In addition, it is important to put the customer at the center.

What opportunities can AI-based supply chain planning offer? The technology of 21strategies is third wave AI – a term coined by DARPA – which also includes early detection and analysis of market developments and market changes. This allows certain influencing factors to be tracked and analyzed in real time. Based on this, an optimal strategic-tactical path can be computed. In this way, optimal purchasing and selling times for commodities can be determined. In addition, risks in international trade such as currency, interest rate and commodity price risks can be minimized through AI-based hedging. The AI-based technology gives distinct suggestions for action and provides decision support for optimal hedging. In this way, for example, commodity price changes can be detected early and recommendations for optimal hedging can be made. To find out how AI-based planning can make your supply chain more stable and resilient, simply contact us at 21strategies.