Sports Direct

What was the objective?

The business had struggled to keep the amount of product ordered at an appropriate level of stock, individual buyers all planned independently across individual time frames each trying to maximise their own areas of the business, this led to an over-buying situation.

It was difficult to process the data to understand which areas had been overbought, and how to correct the problem once it gradually became known.

The business had tried many alternatives to solve the problem, processes were in place, but they were too laborious to calculate using the in house developed legacy systems, and not accurate enough. The Stock volume simply did not fit into the stores and warehouses causing increased discounting.

What was the solution?

Using the scalability and power of IBM Planning Analytics, and harvesting historic trading patterns across a number of years, the team was able to begin to reliably predict demand across a vast range of product classes, for different price points, even for different genders and age ranges of customers, and adjust for seasonal anomalies.

This provided some interesting actionable insights as a by-product e.g. Childrens Premium Branded Clothing having a more pronounced uplift at Christmas, obvious when you know it right? Customers choose higher priced products for Christmas presents, prior to that the business classed these products as over performing and ordered even more.