How Predictive Analytics Has Transformed Inventory Management In Retail

Every retailer wishes to have the right product at the right place at the right time. In order to achieve this there is a lot of thought put into inventory management, allocation, and replenishment processes. Most retailers begin by creating a plan based on the big picture of their business process, and then they purchase the inventory, and allocate it to stores from the DC. Once inventory begins to run low at a specific store, it is replenished from the DC. This strategy would be nice if real life actually worked that way. Unfortunately, this scenario raises a lot of important questions and concerns.

For Example:

• When products don’t sell well at specific stores, retailers are forced to markdown inventory in order to clear the inventory.
• When there is no more inventories in the DC, or even before inventory is replenished, retailers experience lost sales at stores where these products are still in demand.
• Customers resolve to purchase from a local competitor in order to fulfill the sale.
• Lost sales paint an inaccurate picture of lower demand, which in turns makes a retailer order and allocate less inventory to stores in the future. (This cycle repeats itself.)

IHL Group, a global research and advisory firm specializing in retail technologies describes the challenges mentioned above as “Inventory Distortion”. A recent study done by IHL Group revealed that Inventory Distortion costs retailers collectively nearly $800 Billion globally. Over-stocks and Out-of stocks is not a new retail problem, it has been challenging retailers as long as the retail industry has existed.

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