AI-powered forecasting:
Why your rolling forecast is blind without predictive analytics.

A conventional rolling forecast describes the process of rolling planning, often based on manual estimates or linear extrapolations. Predictive analytics, on the other hand, is the technological method that uses machine learning and algorithms to recognize patterns in your data, incorporates external drivers, and thus enables a far more accurate artificial intelligence forecast.

No, it complements them. We work according to the principle of “explainable AI” (XAI). This means that the algorithm not only provides a finished target value, but also shows you transparently which drivers led to this result. The controller acts as a pilot (human-in-the-loop), validating the AI suggestions and making the final decision.

Security is a top priority in financial forecasting. Data processing takes place in encrypted, GDPR-compliant environments. We use your data exclusively for your specific models; your sensitive financial information is not used to train public AI models.

Quite the contrary. Our AI agents in controlling are team players. They integrate seamlessly into your existing world – whether you work with Excel, ERP systems, or IBM Planning Analytics. We don’t create a new construction site, but rather close the gaps between your tools.

We avoid lengthy large-scale IT projects. When introducing rolling forecasts, we start with a modular approach based on a specific use case, such as sales forecasting or liquidity planning. We usually achieve the first measurable results and a significant increase in forecast accuracy within a few weeks.