Revenue Management & Pricing

Hai Chu

The Walt Disney Company

Revenue Management in the World of Big Data

Innovations from technology and science are enabling the collection, storage and analysis (e.g., machine learning) of data with substantial volume, velocity or variety.  This presentation illustrates the big data implications for revenue management, such as consumer choice modeling, geospatial consumer behavior, and ancillary spend optimization.

Bio

Hai D. Chu, Director of Decision Science for the Walt Disney Parks and Resorts has been at Disney for over 7 years. His primary responsibilities include Revenue Management and Pricing analytics for multiple lines of business across Disney Worldwide Parks & Resorts, including Walt Disney World, Disneyland California, Disneyland Paris, Hong Kong Disneyland and Tokyo Disneyland. Additionally, he provides decision science support and solutions to multiple Disney lines of business, including: media networks (ABC, ESPN), movies (Walt Disney Animation Studios, Marvel Animation Inc., Pixar Animation Studios), Disney Cruise Line, and Theatrical Productions. Prior to joining Disney, Hai Chu was with Amazon.com overseeing the World Wide Capacity Planning & Optimization team responsible for their global networks’ customer service capacity solutions. Previous to Amazon.com, he was at Sabre Holdings, a major provider of airline, hospitality, and travel e-commerce and network solutions. Hai Chu received a MS Mathematical Sciences/Operations Research in 1992 from Clemson University.

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Ferguson

Mark Ferguson

University of South Carolina

Tutorial on B2B Pricing and Customer Segmentation

Do you ever wonder what science is behind many proposed solutions that promise to make your B2B pricing more effective?   The purpose of this workshop is to take a step behind the curtains of the pricing analytics software solutions and examine the fundamental modeling concepts that make them work. Customized pricing is used to exploit the price sensitivities of different customer groups by quoting each segment a customized price. We will start by reviewing some existing segmentation techniques that are used in identifying these distinct groups, and then estimate a forecast for each group that provides a probability of purchase as a function of the quoted price.  This forecast is then incorporated into a price optimization model, resulting in an optimized price for each customer segment. Some common implementation and adoption challenges will also be discussed.

Bio

Dr. Mark Ferguson is a Professor of Management Science in the Darla Moore School of Business, University of South Carolina.  He is the co-author of the books Segmentation, Revenue Management and Pricing Analytics and Pricing Segmentation and Analytics. He has served as president of the INFORMS Manufacturing and Services Operations Management Society and the chair of the INFORMS Revenue Management and Pricing Section. Prior to joining the Moore School in 2011, he was the Steven Denning Professor of Technology and Management at the College of Management at the Georgia Institute of Technology and spent five years as a manufacturing engineer and inventory manager with IBM.

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Dev Koushik

Intercontinental Hotels Group

IHG’s Journey towards Total Hotel Revenue Management

Revenue Management as a discipline has undergone tremendous transformation in the industry. This talk will focus on the journey of Revenue Management into the world of Marketing, Brands, Distribution and Digital space and how it has grown beyond its traditional boundaries into the world of commercial services. The talk will give some tips on how Revenue Management practitioners can leverage their Operations Research background to take advantage of this evolution and drive and implement commercial/operational strategy.

Bio

Dev Koushik, Vice President, Global Revenue Optimization, at InterContinental Hotels Group (IHG), has more than 10 years of experience in the field of Pricing and Revenue Management in the travel and transportation industry. Prior to joining IHG, Dev served as a Scientist in PROS Pricing and Revenue Management Division, where he designed innovative Pricing and Revenue Management solutions for airlines and car rental companies. Dev earned his Master’s in Operations Research at University of Florida and Bachelor’s in Mechanical Engineering from College of Engineering, Guindy, Madras.

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Sheryl Richards

Amtrak, National Railroad Passenger Corporation

Revenue Management in the Passenger Rail Industry

Revenue Management is a discipline that has expanded into many industries over the years since it was first introduced by the airlines.   The techniques of revenue management can be found in advertising, hospitals, parking garages; any field that has perishable inventor, relatively fixed capacity, and fluctuating demand.  While concepts are similar throughout the various industries; execution of those concepts is not!  The passenger rail industry is a perfect example of execution variations.  Amtrak National Railroad Passenger will be the subject of this presentation.  You will learn of the structural differences that create additional levels of complexity to revenue management of passenger travel.  Examples include:

  • Varying degree of walk-up demand
  • Single train #s that stop in up to 40 stations
  • Single train #s that travel over three days from origin to destination
  • Sleeper rooms that can hold beds for 2 – 5 individuals based on the room type
  • Modal competition from air, coaches, and personal vehicles

This talk will illustrate these and other unique considerations and solutions while delivering an overview of the recent revenue management system deployment at Amtrak.

Bio

Sheryl Richards is Vice President of Pricing and Revenue Management at Amtrak, National Railroad Passenger Corporation.  As Vice President she is responsible for the vision and direction of Amtrak’s Revenue Management strategies and tactics.  Responsibilities within her oversight include pricing sensitivity and passenger demand analysis, development and execution of revenue enhancing price and capacity strategies, revenue management optimization strategies and systems, performance oversight, business intelligence analytics and tracking, and decision support web-based applications development and maintenance. In March, 2006 Ms. Richards joined Amtrak with the immediate goal of successfully implementing Revenue Management practices throughout the Northeast Corridor.  In the first six months of revenue management implementation, Amtrak realized 7% revenue benefit on the Northeast Corridor.  Other projects undertaken to improve pricing and revenue management performance include restructuring the pricing and revenue management organizations, upgrading the pricing system, development and implementation of a Revenue Management Alert application and decision support tools, and introduction of a passenger rail spill analysis for capacity management.   Most recent undertakings include the vision and implementation of Fare Families for improved market segmentation and customer satisfaction in 2013 and deployment of an automated Revenue Management Solution for Amtrak in 2014. Prior to joining Amtrak, Ms. Richards was a Senior Management Consultant at Sabre Technologies where she provided subject matter expertise to airlines in the area of Pricing and Revenue Management strategy, tactics, and organizations.  Prior to Sabre, Ms. Richards was Director of International Pricing and Revenue Management for US Airways.  Over the course of her career at US Airways she was also responsible for restructuring and managing negotiated corporate and leisure contract pricing, managing the revenue management demand strategies, and providing leadership over deployment of a Revenue Management Solution.

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Loren Williams

Ernst & Young LLP

Pricing Mediated by Humans: The Role of Sales Rep Discretion

It is frequently the case in B2B pricing contexts (and some B2C, as well) that sale representatives are granted the authority to determine the offer price of products or deals, and negotiate price with customers.  This despite the fact that there are several reasons to expect that such discretion results in sub-optimal prices. In this talk, we discuss both sides of this paradox: why we might expect agents of the firm to transact at prices that differ from the firm’s optimal price; and why firms might prefer such policies. We are informed by a unique set of survey data of firms’ practices in this regard.

Bio

Loren Williams is the Chief Data Scientist at EY (formerly Ernst and Young), serving in EY’s Global Analytics Center of Excellence. His organization is responsible for helping the firm accelerate adoption of analytic methods, tools and technology across all of its service lines.  Prior to this role Loren was a leader in their Advisory consulting practice. Loren’s professional training is in economics.  His early work was in Revenue Management, especially in the travel and media industries; later focusing on pricing in both consumer and B2B industries.  Prior to joining EY, he led analytics teams at several specialized technology companies, designing, developing and delivering decision-support software solutions which leveraged ‘big data’ and sophisticated modelling.

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