Companies with warehousing and distribution as their core operations have faced numerous challenges in recent years. This is also true for many other companies operating in various stages of long and complex supply and delivery chains. Supply Chain Management is a rapidly evolving field, featuring several strong trends that are also linked to inventory management and purchasing planning. So, what are these trends, and how do they impact our customers who have digitized and automated their inventory and purchasing processes with IMI SOLO?
An increasingly broad application of Artificial Intelligence (AI) and a rapidly accelerating digital transformation have been identified by many experts as a significant innovation step in the supply chain. Consulting firm Gartner has ranked AI as the most important supply chain trend in their recent trend report. Their analyses show that AI will have a significant business impact when IT technology is utilized effectively. At the same time, Gartner emphasizes the importance of finding a good balance between the new technology’s possibilities and a company’s needs. What works well for one company may not have the same significance for another! Therefore, it is crucial to have a good understanding of AI’s actual business impact and to balance the demands for growth and more efficient processes with the capability of the organization to adopt the technology.
Our early investment in integrating AI into IMI SOLO was spot on
More experts than just Gartner believe that AI has taken a leading position in the supply chain as a tool for driving growth, streamlining inventory management, and optimizing purchasing processes in 2023. There are several reasons why AI has spread so quickly. Although there was no deep recession in 2023, it was a year when many different factors, such as ongoing wars and volatile inflation levels, contributed to a strained global economy. For companies holding inventory, this has meant continued challenges, increasing the need to transition from manual routines to the digitization of inventory management and purchasing processes.
AI plays a crucial role here by offering the ability to replace cumbersome manual routines and personal biases in decision-making with automated and data-driven decision-making. One area where AI offers significant advantages is demand forecasting. Combined with Machine Learning (ML) and the use of algorithms, demand forecasting can be automated, which would otherwise require an enormous amount of manual work.
It was in 2020 that we began the initiative to integrate AI as part of IMI SOLO in collaboration with Chalmers University of Technology. At that time, AI was not the strong trend in the supply chain that it is today, but we had a strong belief that the technology would become highly significant. AI and ML can process large amounts of data, identify patterns, and learn from historical data much faster and more effectively than humans.
We continue to sharpen AI as a tool
For many years, IMI SOLO has used statistical models to simplify the work with demand forecasting. By integrating AI, IMI SOLO can independently improve its algorithms and further refine the results. This is especially crucial for many companies when times are uncertain, and demand fluctuations are large and come quickly!
AI as part of IMI SOLO will continue to be an important and prioritized investment area. We see many opportunities to sharpen AI as a tool. For example, there could be different AI/ML models automatically assigned to different item types, such as high-frequency items, low-frequency items, seasonal items, and new items. The amount of data that AI processes could also be expanded with various online data such as weather forecasts, stock indices, and social media. For all companies that have digitized with IMI SOLO, this enables increasingly accurate forecasts as well as extrapolated forecasts that extend further into the future than was previously possible!
![AI IMI Supply Chain Solutions](https://im.se/wp-content/uploads/2024/06/ai-imi-supply-chain-solutions.jpg)