Improve Forecasts by 30 to 40%
Using real-time data, automation and machine learning algorithms, E2open’s Demand Sensing application creates daily forecasts that reflect current market realities. The application is a core part of the demand-driven digital transformation strategies of leading global companies. Field-proven, it has been used for more than a decade in over 180 countries for $250 billion in annual sales volume.
Real-Time Response to Real-Time Demand
E2open Demand Sensing examines multiple demand signals and combines these inputs to predict near-term demand with superior forecast accuracy compared to traditional time-series approaches.
Highlights include the following:
Near-term forecast accuracy improvements of 30 to 40% compared to traditional methods
Inventory reduction of 10 to 15%, freeing up cash and improving return on capital
Ability to leverage multiple real-time signals to sense demand shifts and respond to changing market conditions
Use of machine learning to quickly process all data, identify patterns and automatically produce a near-term daily forecast
Automatic clustering for forecasting new product volumes based on items with similar behavior
Ability to publish forecasts to supply planning systems without the need for human review, saving time and increasing planner productivity
More accurate projection of the supply required to meet market demands while minimizing inventory
Complementary application that augments existing demand and distribution planning systems