Inaccuracies in demand forecasting cost businesses millions each year
Demand forecasting is the heart of your business, but the process is complex and errors are frequent and costly. Companies are always working to improve their demand forecasting methods and forecasting models, and need more than commonly used datasets such as historical transactions and seasonality patterns to manage volatility. Experimenting with both quantitative and qualitative modeling is key as companies seek to drive down their forecasting error rate.