How Analytics can Impact Promotion Pricing
This tutorial will be given by Professor Georgia Perakis, William F. Pounds Professor of Management Science, MIT in Room 108A at Convention Center.
Joint work with Lennart Baardman (ORC PhD student), Maxime Cohen, (ORC PhD student), Swati Gupta (ORC PhD student), Jeremy Kalas (EECS Undergraduate), Zachary Leung (recently graduated ORC PhD student), Danny Segev (Visiting Scholar ORC/MIT Sloan from U. Haifa)
as well as Kiran Panchamgam (Oracle RGBU) and Anthony Smith (formerly from Oracle RGBU)
Pricing has been a field that has seen a lot of exciting developments in the recent years. A particular area of pricing that has recently emerged is promotion pricing. In many important settings, promotions are a key instrument for driving sales and profits. Important examples include promotions in grocery retail among others. The Promotion Optimization Problem (POP) is a challenging problem as the retailer needs to decide which products to promote, what is the depth of price discounts, when to schedule the promotions and how to promote the product.
In this talk we will discuss how analytics can have a key impact on promotion pricing. This presentation will reflect our ongoing collaboration over the past few years with Oracle RGBU. We will describe the journey we took with them on introducing analytics tools for promotion planning in the grocery industry. We will describe optimization models we have built in order to determine which products to promote and when, as well as which vehicles to use to promote each product (e.g. flyer versus radio announcements among others) and how deeply to promote each product.
An important consumer behavior we will incorporate and which is a direct consequence of promotions in grocery retail is that consumers stockpile the products on promotion and then experience promotion fatigue after the promotion ends. Therefore, as a first step, we study general classes of demand functions that capture this effect and can be directly estimated from data. Using these demand functions, we model and study the promotion planning problem through an optimization formulation. Unfortunately, the underlying formulation even for a single product is NP-hard and highly nonlinear. We will first propose a linear approximation and show how to solve the problem efficiently as a linear programming (LP) problem. We will illustrate how this approximation idea has applications in many areas beyond pricing. We will discuss analytical bounds on the accuracy of this LP approximation relative to exact problem solution. We will also consider a graphical representation of the problem which will allow us to employ a Dynamic Programming (DP) solution approach as an alternative. We will discuss the tradeoffs between the two approaches (LP vs DP). Furthermore, we will incorporate in the optimization formulations, apart from the pricing aspect, how to decide which vehicle to use each time in order to promote which product. This further complicates the problem. We will introduce greedy and integer optimization ideas in order to solve the vehicle selection problem in a tractable way. These methods are computationally efficient and hence are easy to use in practice. We will also discuss some performance guarantees for these methods.
Finally, we will illustrate how our approach generalizes to consider multiple products within a category that are substitutes and/or complementary. We will discuss the tradeoffs when there are cross product effects.
Together with our industry collaborators from Oracle Retail, our framework allows us to develop a tool which can help supermarket managers to better understand promotions by testing various strategies and business constraints. We show that the formulation we propose solves fast in practice using actual data from a grocery retailer and that the accuracy is high. We calibrate our models using actual data and determine that they can improve profits by 3% just by optimizing the promotion schedule and up to 5% by slightly modifying some business requirements.
Georgia Perakis is the William F. Pounds Professor at the Sloan School of Management at MIT since 1998. She received an M.S. degree and a PhD in Applied Mathematics from Brown University and a BA from the University of Athens in Greece.
Perakis' research studies the role of operations in many areas such as pricing, supply chain management, energy and transportation applications among others. She has widely published in journals such as Operations Research, Management Science, POM, Mathematics of Operations Research and Mathematical Programming among others. She has received the CAREER award from the National Science Foundation and subsequently, the PECASE award from the office of the President on Science and Technology awarded to the 50 top scientists and engineers in the nation. In 2007 she received an honorable mention in the TSL Best Paper Award, she also received the second prize in 2011, the first prize in 2012 and in 2014 in the Best Paper competition of the Informs Service Science Section for some of her papers. In 2015, her work on promotions received the Best Application of Theory Award from NEDSI (Northeast Decision Sciences Institute) Conference. She also received the Graduate Student Council Teaching Award as well as the Jamieson Prize for excellence in teaching and the Samuel M. Seegal prize for “inspiring students to pursue and achieve excellence”. Perakis was the recipient of the Sloan Career Development Chair and subsequently of the J. Spencer Standish Career Development Chair. In 2009, Perakis received the William F. Pounds chair that she currently holds. Her work on promotion pricing work was a Finalist at the Practice Award of the Revenue Management and Pricing Section of INFORMS in 2015. Perakis has passion supervising her students and builds lifelong relationships with them. So far she has graduated seventeen PhD and thirty Masters students.
Perakis has served as the co-director from the MIT Sloan School side for the Leaders for Global Operations (former LFM) program. She is currently the group head of the Operations Management Group at MIT Sloan. She serves as an Associate Editor for the journals Management Science, Operations Research and Naval Logistics Research and a senior editor for POM. Perakis has served as a member of the INFORMS Council. She has also served as the chair of the Pricing and Revenue Management Section of INFORMS and in 2009-2010 as the VP for Meetings of the MSOM Society of INFORMS. She has co-organized the MSOM 2009 conference and served in the organizing committee of the 2010 MSOM conference. She has also been the co-chair and co-organizer of the Annual Conference of the INFORMS Section on Pricing and Revenue Management for several years and the chair of the cluster on the same topics for the annual INFORMS and ISMP conferences for several years.