Demand forecasting was becoming a hot topic as companies of all sizes and sectors faced the same need and challenges. Accurate predictions were essential for optimizing operations, but the complexity and variability in demand patterns made it difficult for existing solutions to meet these needs effectively.

Each situation required a case-by-case, limited analysis and treatment. We were always asked to choose the “right” model from many existing ones, and other market solutions were expensive, ineffective for forecasting, and arduous to implement. Highlighting the need for a more efficient and adaptable approach.

We witnessed a significant advancement in new technologies, seeing Machine Learning and AI as game-changers. These innovations promised the ability to handle complex data patterns and improve prediction accuracy, inspiring us to explore their potential in demand forecasting.

2019 was a landmark year for us. Partnering with the University of Maastricht, a PhD student rediscovered that no single model is the “best model” in all situations. Instead, the best results consistently emerged from the “best combination” of multiple models, paving the way for a more robust solution.

Recognizing the need to automate as much as possible, we aimed to eliminate manual actions from the forecasting process. Choosing models and weighting results manually for thousands of products was impractical; automation was crucial for efficiency and scalability in demand forecasting.

We reached a crucial step by enhancing the accessibility of our solution. Leveraging our service via an API or a user-friendly web interface allows users to simply connect, load their data, and let AI handle the rest, making advanced forecasting accessible to all.

Today, FaaS4U is a solution of having high potential value in terms of profitability, inventory management, and forecast accuracy. By leveraging AI and ML, our solution changes the game, offering a significant competitive advantage and transforming the landscape of demand forecasting.