1 May 2015
Pricing and Revenue Management
Implementation of Pricing and Revenue Optimization
Introduction
Perhaps one of the most difficult managerial decisions in the 21st century is the decision to make a decision. Analysis paralysis, endless meetings, and corporate structure have made it painstakingly difficult to come to any real conclusions. So when the Chief Financial Officer, Bruce Berman, of Bloomindale’s was tasked with decision to implement ProfitLogic’s Pricing Optimization (PO) system, he called upon Daniel Gabbay, an analyst in the finance division, to make sense of the numbers and guide his decision making process. Berman was considering implementing a PO system to quantify the markdown management and provide insight on how to maximize revenue. In retail, margins are slim and competition is stiff, so every penny gained in top-line growth is vital for a company’s health and future. The PO system requires a substantial up-front investment of a $1 million license fee, training time, and implementation. While ProfitLogic had proven success with other companies, Berman had to know if it would be successful. Unfortunately, this is not an easy question to answer. What exactly does successful look like for Bloomindale’s? How can Berman “know” it was successful? What are the next steps needed to evaluate the program? These questions are the focus of this paper.
Available Information
For this paper, we will operate under the assumptions that the information we have in “Markdown Pricing Optimization at Bloomingdale’s” is the only information Gabbay has. Ideally, the consultants would have released the entire regression analysis and executive summary along with the dataset. This would provide Elmer, Luithly, and Watt the information required to make pointed questions and suggestions, rather than vague generalizations and observations. Without the data and the time to build a regression model, we cannot ultimately make any