Demand Planning2019-11-14T16:28:09-05:00

Dramatic Forecast Improvements

Understand, anticipate and shape demand. Using automation and machine learning algorithms, E2open’s Demand Planning application creates the most accurate forecasts possible. Companies can then manage demand by engaging colleagues, customers, channels and other stakeholders. The result is an efficient process for unifying the organization around an accurate demand plan.

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Increased Accuracy and Productivity

E2open’s algorithms bring speed, scalability and more accurate predictions to demand planning. Superior analytics, automation and integration result in ease-of-use and high productivity.

Advanced features facilitate success:

  • Machine learning and analytics for increased accuracy and efficiency

  • Collaborative forecasting to unify stakeholders around a common plan

  • Use of customer and channel data from E2open’s Demand Signal Repository and Channel Data Management applications

  • Process automation so planners can spend more time on strategic issues rather than repetitive tasks

  • Easy integrations for leveraging multiple internal and external data sources

  • Attach rate planning to forecast dependent component demand for configured products

  • More than 10% improvement in long-term forecast accuracy using advanced algorithms

  • 50-70% reduction in planning cycle times through source system integration and process automation

Data Sheet

E2open Demand Planning

Using automation and machine learning algorithms, E2open’s Demand Planning application creates the most accurate forecasts possible.

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Case Study

Seagate Builds Supply Chain Driven by Customer Demand

Discover how Seagate transformed its build-to-forecast model into a responsive build-to-demand model and created an efficient, industry-leading supply chain.

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Prepare for What’s Coming

Anticipate demand as the first step in managing your supply chain. Efficiently develop more accurate forecasts to improve revenues and service while reducing costs.

Forecast Better
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