Challenges Faced In the Rental Car Industry

1. Challenges Faced In the Rental Car Industry CRM RM2003 Workshop Centre de recherches mathematiques University of Montreal May 16, 2003

2. Purpose • Introduce the Rental Car Revenue Management Practice • Illustrate some “interesting” problems • Stimulate interest and facilitate desires to work on challenging real life and timely problems • Win – win applied science • Students Real life problems (relevance) and data (feasibility) • Vendors Communication, focus, and business strategies • Industry Low cost research, development, and diverse thought

3. Agenda • Introduction • Brief Background on DTAG • Our “Revenue Management System” • Car Rental Market Specifics • Challenges & 7 Key Areas of Interest • Q & A

4. Dollar Thrifty Automotive Group • Just recently made the Fortune ™ 1,000 List (# 999) • Over $1 billion in Annual Revenue • Continued growth over past 5 years (Including 2001 & 2002) • Low cost provider – mostly leisure orientated consumers • The most profitable Car Rental company • Dollar is mostly corporately owned and “on airport” • Thrifty is * mostly franchisees • Worlds largest Car Rental Franchise • Internal merger - January 2003 • * New growth initiatives through Corporate acquisitions of target licensees • Resultant is now “Dual Branding”

5. The Complete Revenue Management System “RMS” Human Resource Science Automation Decision Support Processing Performance Measurement

6. Data and Information Flow Rental Transactions Rentals, Returns, Fleet, Walkups, Offsells Reservations Rates & Turndowns Forecast, Optimization, Competitive Rate Placement Rate Management Reports, Graphs, Analysis & Research

7. Rental Car Market Specifics • Supply • Fleet is flexible to a degree depending on time horizon • Fleet is also a significant fixed cost component in the short term • It also moves – (relocates itself) • Demand • Mostly “secondary demand” Inelastic as a market whole • Car Rental is a Commodity to a large extent – (Same cars) • Service is the primary differentiating quality (what % of consumption is it?) • Therefore, very Elastic between companies • Market • Fluid pricing capabilities – dynamic pricing is prevalent • Low barriers to entry – no “geographical markets” per say – most companies can be everywhere • Economies of Scale • Since the fleet is highly leveraged, companies can run enormous volumes and spread the fixed costs over larger revenue base.

8. Areas of Interest • Segmentation • Forecasting and optimization • Business strategy, competitive information and analysis • Decision support • Performance measurement • Data • People

9. 1. Segmentation Methods • Market Segment (Business, Leisure, Tour,..) • Distribution channel • Length of rent (LOR) • Brand • Car class • Arrival date, day of week, and time of day • And yes, to some extent – Advanced days

10. 1. Segmentation • Methods to segment • Fencing off segments • Capitalize on different demand levels and elascticities • When to increase / decrease segmentation •  The end result is pricing

11. Leisure Business Tour 1. Segmentation Illustration

12. 2. Forecasting and Optimization • Forecasting / Proactive Approach • What to forecast? What level of detail? How to forecast (Method)? What to do with a forecast? • Demand • Rate • No Show, Cancellations  Overbooking • Booking (and Demand) Paces and Walkup • Upsell and Upgrade • Competitive information and gaming • Seasonality (Calendar, DOW, Business Cycle) • Unconstraining (Inclusion of Turndowns / Conversions) • Optimization • Tradeoffs, Objective, Methods, and Implementation

13. Forecasting Samples

14. PHX - I

15. PHX - M

16. PHX - 4

17. PHX - L

18. 2. Optimization – Sample Output

19. PHX I – LOR 3-4 RECS

20. PHX L – LOR 1-2 RECS

21. Decision Support Formal Integration Increasing the understanding 3. Competitive Information

22. 3. Competition - Sample

23. One Method for Implementation - Strategy Screens Match # 3 $1 < # 3 Match # 2 $1 < # 2 Match # 1 $1 < Lowest Priced Competitor (#1)

24. 4. Decision Support • Types • Reports • Analysis • Formal • Ad Hoc • Formats • Production systems • Independent “consolidating” DSS • Prototypes and/or informal tools • Support • Technical • Intellectual – Use/Misuse, education and training tools • Purpose • Transcend intuition • Bridge the theory and application • To be the catalyst of better decisions • Gain insight and understanding – Build knowledge

25. DSS Samples - Interfaces

26. DSS Samples - Report

27. DSS - Samples

28. PHX I – LOR 1-2 RECS

29. PHX I – LOR 3-4 RECS

30. PHX L – LOR 1-2 RECS

33. 5. Performance Measurement • Challenges • Lack of a control • Seasonality • Numerous simultaneous variables • Interpretation / subjectivity • Need for aggregation • Internal agenda and bias • Current standard is still year over year and aggregate benchmarks like yield, utilization, and revenue per unit • Performance of what? • System? Implementation? Location? Company?, People?, Industry?

34. Performance Measurement Advancements • Awareness, education, understanding and appreciation • Opportunity cost models • Solid economic theory and foundation, then back with quantification efforts • Turndown and conversion data availability at new levels of “richness”

35. 6. Data • Timeliness matters for production, but perhaps not for research • Not perfect  Messy and erroneous, but consistent • Detailed transaction level • Need to aggregate and join • Lots of it – diverse, but little history • Sample sets are currently available and other are feasible

36. 7. People • People are not only the glue to make it all work, but they are also the catalyst for new ideas • Process, Integrate, Implement, Create, Innovate, Develop, Communicate and Understand!

37. Sample Questions or Research Topics • How correlated is the initial build to final demand? • Ability to segment balanced with the ability to manage • Margin based segmentation (Rev-Cost) with an ability to capitalize on inelastic demand • Understanding the consumer and gaming the competitors • Opportunity cost  Consumer surplus from the industry, company, or finest detail of business • Price elasticity, elasticity, elasticity  From specific channel pricing to fleet acquisition

41. Summary / Q & A