

The challenges :
An internationally active industrial company faced the challenge of making its long-term market predictions for various product and regional portfolios more efficient and data-driven. Although numerous structured and unstructured information sources (including extensive market reports) were available, manual analysis and consolidation of this data was time-consuming and resource-intensive. The central challenge was to identify, evaluate, and prepare truly relevant information from mass data for the forecasting process. The goal was therefore to develop a GenAI-supported solution that automatically detects significant developments, summarizes them concisely, and assesses their relevance for the target markets.
Our approach :
In joint workshops, a clear target vision and the requirements for a GenAI-based Market Intelligence tool were first defined. Building on this, we developed a Generative AI workflow that processes large-scale market reports, identifies relevant content structured by product and region, summarizes it in a targeted manner, and automatically evaluates its relevance for each target market. The workflow was iteratively refined and adapted to the specific requirements of the forecasting process, allowing the insights gained to be processed directly.
Our solution :
With the new GenAI-supported workflow, the company can now identify and utilize market information much more efficiently. Relevant trends, risks, and opportunities are automatically detected, evaluated, and prepared for the forecasting process. This significantly increases the timeliness and quality of strategic forecasts and creates much greater transparency regarding global market developments. Furthermore, the solution is scalable and can be flexibly extended to additional markets and product areas. In this way, a sustainable foundation has been established to systematically integrate Generative AI into the company's strategic planning.
Your Contact
Dr. Matthias Emler
