Case study: Supply Chain Demand Planning for Global Networking Major

Business Context

The client, a technology major with market dominance in networking equipment and a global presence was looking to improve the SKU forecasting accuracy in order to improve planning efficiency and add incremental value with the help of SFDC data.

How BRIDGEi2i Delivered Value?

BRIDGEi2i built a robust, self-learning, automated regression model determining the relation between quote age and bookings and partnered with the client for the development of a new stream to incorporate the SFDC data with an aim to improve the forecasting process. The end result: the Demand Planning Optimizer helped accurate forecasting of demand at the product family level.

BRIDGEi2i helped the client improve their forecast accuracy by 2%!

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