Using Big Data to Help a Large Office Retailer Improve Margins
The client is a multinational office supply retailer with over 1500 stores in North America.
With hundreds of thousands of SKUs for hundreds of thousands of customers, setting the optimal price for each SKU and customer requires big data capability. The client sought the ability to use recent transactions and prices paid for similar customers buying similar products to determine the price to charge new and existing customers and for new SKUs. We were tasked with creating a pricing strategy vision, more intelligent pricing at point of sale, and better processes through which pricing and sales interact.
In the office products market, distributors operate on thin margins earned across large numbers of transactions, customers, and SKUs. Our approach was to affect small margin improvements to have a big impact on overall earnings. To do that, we leveraged the client’s vast transaction data through analytics, developing a new pricing methodology. The price optimization technology was incorporated into the client’s existing pricing and sales tools to maximize adoption by their people. We also carefully documented the client’s current pricing processes and built new ones, enabling stakeholders to see exactly what was changing and why.
The client adopted our recommendations on a new pricing strategy that enhanced business processes, and added a comprehensive business readiness approach that included training and communication. They realized a return on investment within the first year of deployment, demonstrating the power of making small changes with big data.