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Montgomery Blair

Montgomery Blair

Montgomery Blair

Vice President of Revenue Management at Hertz Corporation

Montgomery Blair is currently a Vice President of revenue management at the Hertz Corporation. He has over 20 years of experience in the design, development, implementation, testing, training, commercialization and real use of revenue management solutions in several industries. Within car rental he has worked for three different companies spanning eight major brands. Within the multi-family housing industry he was part of the team that developed LRO (Lease Rent Options) which became the leading RM system for that industry. He has helped transform companies via data driven analytics, decision support systems and optimization solutions.
In addition to the hands-on industry experience Montgomery helped start the Revenue Management and Pricing Section of INFORMS where he served as the initial Vice Chair and then later becoming Chair and active Board Member for several years. He was one of the original editors for the Journal of Revenue and Pricing Management where he contributed and served for ten years. He has also been an industry reviewer for the Cornell Hospitality Quarterly.

Track: Revenue Management & Pricing

Monday, April 15th, 1:50-2:40pm

Revenue Management and Pricing in the Car Rental Industry

Car Rental Revenue Management
Years ago the field of revenue management progressed from yield management to more a holistic approach which includes dynamic pricing. As the evolution continues it is now seeking even tighter integration with marketing, sales, e-commerce, customer experience, all things digital, and the supply-side. This expanding scope of “RM” is primed to capitalize on the advancements of computing power and the proliferation of data. RM should be among the first disciplines to not only benefit greatly from advancements in artificial intelligence and push the frontier of its application to decision science. We will share a glimpse into our journey and highlight some key areas, steps we are taking, and the barriers we face as we expand our cognitive technologies within car rental.

  • Descriptive analytics with big data
  • Predictive analytics and the need for solid demand models. The semantics matter as there is a difference between demand, forecast, and plans⋯unconstrained vs. constrained, input vs. output, etc.
  • Prescriptive analytics – advancing beyond traditional optimization
  • Change management – As machines do more of the granular day-to-day work the role that people play and the overall process will change.