Turning SKU data into increased revenue

Our client is a major global retailer and distributor with store, ecommerce and B2B retail channels. With over 1 million SKUs, changing customer demands and finite inventory space, not all products can be stocked for fast dispatch to customers. The existing method to decide what items should be in stock was determined by historical sales—this was inefficient, causing working capital to be tied up in inventory that wasn’t selling. On the other hand, inventory that was in demand and not stocked couldn’t be dispatched to customers quickly, impacting sales, revenue and customer experience.

Datasparq built a data product for the client’s inventory management team—a predictive model that determines the optimal inventory to stock. The product took into account a rich set of inputs such as ecommerce product views, ecommerce cart additions, price, product technology and more. The solution advises inventory controllers and category managers on which SKUs should be stocked with a clear explanation as to why. The result is increased sales and revenue, reduced storage costs and improved customer satisfaction.