FinlandManufacturing2023 – ongoingStora Enso
Sensible ML financial forecasting and scenario simulation
Stora Enso reported early forecast improvements with OneStream's Sensible ML
Problem
Stora Enso wanted more accurate financial forecasts and clearer explanations of the factors affecting predictions. Its planning covered commodity prices and accounts-payable spending.
Approach
Stora Enso implemented OneStream's Sensible ML for forecasting and scenario simulation. It incorporated external macroeconomic indicators into predictions. Finance teams used dashboards to examine historical data and alternative scenarios.
Results
No published figures
Takeaway
Finance executives reported early accuracy improvements, but disclosed neither the error reduction nor the evaluation period.
Categories
- Size
- Large enterprise
- Industry
- Manufacturing
- Business function
- Finance, risk and legal
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and ML
- Adoption
- Vendor solution
- Evidence
- Vendor case study
Sources
Source summaries
OneStream reported initial forecast-accuracy improvements for pulp and wood prices, chemical prices and accounts-payable spending. Stora Enso finance executives also described better explanations of forecast drivers and improved planning efficiency. No numerical accuracy results were disclosed.
Full details are in the original sources.
