1. 1 Where to Next? E. Andrew Boyd Chief Scientist and Senior VP, Science and Research PROS Revenue Management

2. 2 History  Revenue management in the airline industry has a long and venerable history dating back over 4 decades u Revenue management was born in the airline industry

3. 3 Revenue Management Visibility “Revenue Pricing Optimization represent the next wave of software as companies seek to leverage their ERP and CRM solutions.” – Scott Phillips, Merrill Lynch “One of the most exciting inevitabilities ahead is ‘yield management.’ – Bob Austrian, Banc of America Securities “Revenue Optimization will become a competitive strategy in nearly all industries.” – AMR Research

4. 4 AGIFORS History 1960 Formation of AGIFORS 1970 1980 1990 2000 Formation of AGIFORS Reservations and Yield Management Study Group

5. 5 Research Topics Based on McGill and van Ryzin, 1999, “Revenue Management Research: Overview and Prospects” 1960 1970 1980 1990 2000 Overbooking Forecasting Leg / Class Control O&D Control

6. 6 Historical Conclusions  The fundamentals of revenue management are well-understood  Primary challenge is to put these fundamentals to work u Systems capable of handling the many complexities of an operational system

7. 7 Industry Use Estimates System% Use Leg or Segment Class RM< 50% Fare Class Rationalization< 10% Group< 10% O&D< 2.5%

8. 8 Risk  Failure to institutionalize science  Failure to appreciate the complexity of developing and maintaining high quality software

9. 9 Risk  Failure to institutionalize science  Failure to appreciate the complexity of developing and maintaining high quality software

10. 10 Where to Next?  To remain vital, a discipline must have new challenges  What are potential candidates?

11. 11 Where to Next? Traditional Revenue Management Activities

12. 12 The Centerpiece: PNRs  PNRs contain information not found in leg/class inventory levels, thus providing a much richer source of data than leg/class inventory levels for decision-making u Transaction-level inventory decisions  Changing distribution environment providing increased opportunities for transaction level inventory decisions

13. 13 Sample PNR Information  Flight itinerary  Purchase modification history  Customer identifier  Point of sale / distribution channel  Contract identifier  Special requests

14. 14 Sample PNR PHG 01 E 08800005 010710 010710 225300 XXXXXXXX 000000 I 01 1V XXXXXXXX SNA US XXX 05664901 00000000 XXXXXXXXX XXX I R 0 0 PSG 01 OA 3210 LAX IAH K 010824 1500 010824 2227 010824 2200 010825 0227 HK OA 0 0 PSG 01 OA 9312 IAH MYR K 010824 2330 010825 0037 010825 0330 010825 0437 HK OA 0 0 PHG 01 E 08800005 010710 010711 125400 XXXXXXXX 000000 I 01 1V XXXXXXXX SNA US XXX 05664901 00000000 XXXXXXXXX XXX I R 0 0 PSO 01 EV 0409 K PSG 01 OA 1221 LAX IAH K 010825 0600 010825 1325 010825 1300 010825 1725 HK OA 0 0 PSG 01 OA 0409 IAH MYR K 010825 1455 010825 1636 010825 1855 010825 2036 HK OA 0 0 PSO 01 EV 4281 Y PSG 01 OA 4281 MYR IAH Y 010902 0600 010902 0714 010902 1000 010902 1114 HK OA 0 0 PSG 01 OA 5932 IAH LAX K 010902 0800 010902 0940 010902 1200 010902 1640 HK OA 0 0 PHG 01 E 08800005 010710 010712 142000 XXXXXXXX 000000 I 01 1V XXXXXXXX SNA US XXX 05664901 00000000 XXXXXXXXX XXX I R 0 0 PSO 01 EV 0409 K PSG 01 OA 1221 LAX IAH K 010825 0600 010825 1325 010825 1300 010825 1725 HK OA 0 0 PSG 01 OA 0409 IAH MYR K 010825 1455 010825 1636 010825 1855 010825 2036 HK OA 0 0 PSO 01 EV 4281 Y PSG 01 OA 4281 MYR IAH L 010903 0600 010903 0714 010903 1000 010903 1114 HK OA 0 0 PSG 01 OA 5932 IAH LAX K 010902 0800 010902 0940 010902 1200 010902 1640 HK OA 0 0 PHG 01 E 08800005 010710 010716 104500 XXXXXXXX 000000 I 01 1V XXXXXXXX SNA US XXX 05664901 00000000 XXXXXXXXX XXX I R 0 0 PSO 01 EV 0409 K PSG 01 OA 1221 LAX IAH K 010825 0600 010825 1325 010825 1305 010825 1725 HK OA 0 0 PSG 01 OA 0409 IAH MYR K 010825 1455 010825 1636 010825 1855 010825 2036 HK OA 0 0 PSO 01 EV 2297 L PSG 01 OA 5932 IAH LAX K 010903 0800 010903 0940 010903 1200 010903 1640 HK OA 0 0 PSG 01 OA 2297 MYR IAH Q 010903 1140 010903 1255 010903 1540 010903 1655 HK OA 0 0 PHG 01 E 08800005 010710 010717 111500 XXXXXXXX 000000 I 01 1V XXXXXXXX SNA US XXX 05664901 00000000 XXXXXXXXX XXX I R 0 0 PSO 01 EV 0409 K PSG 01 OA 1221 LAX IAH K 010825 0600 010825 1325 010825 1300 010825 1725 HK OA 0 0 PSG 01 OA 0409 IAH MYR K 010825 1455 010825 1636 010825 1855 010825 2036 HK OA 0 0 PSO 01 EV 2297 Q PSG 01 OA 0981 IAH LAX Q 010903 1420 010903 1608 010903 1820 010903 2308 HK OA 0 0 PSG 01 OA 2297 MYR IAH Q 010903 1140 010903 1255 010903 1540 010903 1655 HK OA 0 0 1 1 2 2 3 3 4 4 5 5

15. 15 PNRs and O&D Forecasting  O&D control requires O&D forecasts u Best optimization methods require O&D forecasts  PNRs provide the best source of data for generating O&D forecasts

16. 16 PNRs and Net Fare Assignment  Make availability decisions based on actual value of purchase u Distinguish a $200 Y class ticket from a $400 Y class ticket u Account for distribution channel, contract, point of sale …  PNRs provide necessary sales information

17. 17 PNRs and Customer Level Control  Tremendous opportunity for double double digit revenue improvements u Cross-sell, up-sell, dynamic packaging u Customer specific pricing u Specialized customer service  Marketing science literature remains largely untapped

18. 18 Where to Next? Non-Traditional Revenue Management Activities

19. 19 Contracts  The sale of large fractions of inventory is governed by contracts  In most cases, contracts receive little if any analytical analysis u Integrating sales and inventory management u Alliances and cooperative agreements u Block inventory valuation

20. 20 Where to Next? E. Andrew Boyd Chief Scientist and Senior VP, Science and Research PROS Revenue Management

21. 21 References  Jeffery McGill and Garrett van Ryzin, “Revenue Management: Research Overview and Prospects,” Transportation Science, 33 (2), 1999  E. Andrew Boyd and Ioana Bilegan, “Revenue Management and e-Commerce,” under review, 2002