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MIT researchers win 2014 INFORMS Revenue Management and Pricing Section Practice Award

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MIT’s Kris Johnson, Alex Lee, and David Simchi-Levi — along with online retailer Rue La La — have received the 2014 INFORMS Revenue Management and Pricing Section Practice Award for a project that is expected to increase Rue La La’s revenues. The award for the analytics-based pricing-optimization application developed through the Accenture and MIT Alliance in Business Analytics was presented on June 5 at the INFORMS Revenue Management and Pricing Conference in Istanbul.

The Institute for Operations Research and the Management Sciences (INFORMS) is the largest society for professionals in the field of operations research, management science, and analytics. Its annual Revenue Management and Pricing Section Practice Award recognizes outstanding applications of revenue management and pricing techniques. The winner is selected based on impact, originality and innovation, and technical merit.

“Rue La La’s use of the new price-optimization application is an example of how analytics can change the way a company operates. We started this project with the goal of reducing inventory, and ended up with a cutting-edge, demand-shaping application that has a tremendous impact on the retailer’s bottom line,” says David Simchi-Levi, a professor of civil and environmental engineering and engineering systems, and co-chair of the Accenture and MIT Alliance in Business Analytics.

Murali Narayanaswamy, vice president of pricing and operations strategy at Rue La La, says, “This research project fundamentally changed our business. After implementing these analytics techniques, we’re expecting an increase in revenue of more than 10 percent with little impact on demand.”

Rue La La's "virtual boutiques" offer products for a limited time – typically only two or three days – before customers may no longer purchase the products. Correctly pricing these items is challenging, since the company has never sold the majority of these products before. In the past, more than 50 percent of products quickly sold out, suggesting that the price was too low. For other products, the price may have been too high, leaving the company with unwanted inventory.

The pricing-optimization application developed by the Accenture and MIT Alliance in Business Analytics aimed to maximize revenue while maintaining demand for the products. The approach starts with machine learning techniques that develop a demand-prediction model; the resulting data is then fed into a price-optimization model. 

Narendra Mulani, senior managing director of Accenture Analytics and co-chair of the Accenture and MIT Alliance in Business Analytics, says, “The pricing-optimization application developed for Rue La La is an excellent example of how data analytics and machine learning techniques can positively impact an organization and drive value.”

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