What is DPRM? INSEAD Ioana Popescu DPRM 6. Professor Ioana Popescu OPTIMIZE PROFITS DYNAMIC PRICING & REVENUE MANAGEMENT. A systematic approach to

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1 DYNAMIC PRICING & REVENUE MANAGEMENT Professor Session 6: Revenue Management. Managing Capacity and Demand Risk Booking limits & Protection levels. The EMSR rule. EasyProfit case/simulation. What is DPRM? A systematic approach to OPTIMIZE PROFITS by managing DEMAND SUPPLY DYNAMIC PRICING REVENUE MANAGEMENT

2 DPRM Overview Basic Frameworks and tools Industry To do 1. Introduction to revenue management 2. Multi pricing in segmented markets Entertainment Poll 1 Demand Estimation & Pricing 3. Static pricing with constraints Adwords/Congestion Group 1 4. Dynamic pricing: markdowns Retail/Consumer Goods Strategy 5. Benefit assessment Fashion Revenue Management 6. Managing capacity & demand risk Airlines/Hotels Poll 2 7. Multi resource management Media/Clouds Poll 3 8. RM for price takers Leasing/Transport Group 2 I.Popescu 2010 The DPRM Process our focus 1. Segment the market 2. Design product line 3. Forecast demand 4. Manage Price Decisions 5. Manage Inventory/ Availability This week Today I.Popescu 2010

3 Origins of RM: a story (1984) PeopleExpress: $1B revenue ; $60M profit fares 70% lower than major airlines cost structure 50% lower How could American compete? AA s dilemma: To Match or Not To Match PE s fares? I.Popescu 2010 Bob Crandall s answer Ultimate Super Saver Fares match People s fares, but: 1. two week prior booking + Saturday night stay 2. restricted availability (DINAMO) I.Popescu 2010

4 Base Airline Customer Segmentation Leisure Customers Very Price Sensitive Book Earlier Flexible to schedule Weekend/Holiday Business Customers Less Price Sensitive Book Later Schedule Sensitive Short weekday travel Segment the market, create differentiated products and let customers self select. I.Popescu 2010 The Results PeopleExpress sold to Continental Airlines at a deep discount one year later. Complex fare structures and computerized revenue management systems developed by all major airlines. What you don t know about RM could kill you! Donald Burr, CEO of People Express, 1986 I.Popescu 2010

5 Keys to American s Success Market Segmentation Using product fences to separate leisure from business travelers. Revenue Management Forecasting future bookings and restricting discount seat availability to ensure future capacity availability. Sell the right product to the right customer at the right price at the right time I.Popescu 2010 EasyProfit Questions Problem features What are the risks and trade offs managed? What is the optimal booking limit policy (logic)? When is revenue management most effective? How can you do better? Other industries/applications

6 Simplest RM Problem Fixed, perishable inventory (capacity C) Two virtual product versions : the same basic resource! (resource substitution) Customer WTP increases with time: High paying customers come later (vs. Retailer) Costs are sunk (MC=0). No cancellations or no shows. No arbitrage. What s wrong with First Come First Serve? Cannibalization (dilution, displacement): product is sold to low end customer and high end customer is turned away due to inventory shortage. Opportunity cost: difference in prices (p B p L ) per hi end customer turned away. RM: In this case it is optimal to limit the sale of the low end product and reserve inventory for high paying customers.

7 RM Strategy Trade offs Cannibalization versus Spoilage (unsold inventory): low end customers are turned away because of an aggressive booking limit, but at the end there is inventory left over. Opportunity cost: revenue p L from low end customer turned away due to the booking limit. Questions: x How to optimally trade off cannibalization vs. spoilage? x What is the value of doing this? Econ 101 revisited (Vertigo) Divide inventory between segments to balance marginal revenue for the last unit allocated to each segment: MR 1 = MR 2 What is different in the EasyProfit case? prices are fixed demand is variable, at each price & over time (arrival pattern)

8 Breakeven Analysis Risk decision: Balance certain (low) revenue today with the opportunity cost of one unit of supply available in the future. Implementation: Close down the low fare class to additional sales when the certain revenue from selling another low fare unit is exceeded by the expected revenue from saving that unit for a potential high value customer. Two ways to think about it: ProtectQ units for high class that you will not sell to low price class Set a Booking limit: the maximum number of low class sales: BL= C Q Newsvendor logic: balance marginal revenue loss Overage (protect too much) C o = p L Underage (protect too little) C u = p B p L p L P(D B < Q) = (p B p L ) P(D B > Q) P(D B <Q) = C u /(C o +C u ) = (p B p L )/ p B If D B ~ N(μ,σ 2 ), then the optimal protection level Q satisfies: Q = μ + σ Normsinv [ (p B p L )/ p B ] The optimal booking limit is BL=C Q I.Popescu 2010

9 Newsvendor logic: balance marginal revenue loss Overage (protect too much) C o = 80 Underage (protect too little) C u = =40 80 P(D B < Q) = 40 P(D B > Q) P(D B <Q) = C u /(C o +C u ) = 0.33 z =Normsinv(0.33)= 0.43 D B ~ N(36,6 2 ) Q = z= 33 BL=100 33=67 I.Popescu 2010 To Sell or not to Sell? now (low) wait later (high) not at all 0

10 General framework: Decision under Risk sell it now (low) 80 (p L ) Protect Q th unit? wait sell high not sell 120 (p B ) 0 How likely is it that I will sell Q units (or more) at the high price? Expected Marginal Revenue (EMSR) Rule Logic: Set the protection level Q to balance the expected marginal (seat) revenue from business and leisure segments p B * Probability(Q or more business customers arrive) = p L P(D B Q) = p L / p B Generic rule: Sell to leisure as long as the price (p L ) exceeds the opportunity cost of selling to business

11 How to find the optimal protection level Q? p B * Probability(Q or more business customers arrive) = p L 100% 90% Probability that a total of x or more business customers arrive Fare ratio: p L /p B = % 70% 60% 50% 40% 30% 20% 10% 0% Total demand from business customers, x Q=33 Booking Limits EMSR Generic Procedure STEP 1: Forecast demand to come for each product version (fare class) Aggregate distribution (mean & std. dev) Booking curve (arrival process) STEP 2: Calculate the fare ratio: p L / p B STEP 3: Use the demand distribution to calculate the protection level Q P(D B Q) = p L / p B (critical fractile) and the booking limit BL=C Q [logic: balance marginal expected revenues; Littlewood s rule] STEP 4: Accept low fare demand up until the booking limit BL=C Q is reached. After that, close down the low fare class. STEP 5: Go back periodically to STEP 1 to update the booking limit

12 Arrival rate (booking curve) forecasts I.Popescu 2010 When to use EMSR? Relatively limited capacity Perishable service opportunity Demand utilizes one inventory type/resource substitution Segments can be ranked from low to high value Arrival pattern: Lo Hi (low before high) WTP Advance purchase Limited resale/arbitrage Fixed prices

13 How to estimate expected revenue 1. Simulate 2. Plot: the area under the EMSR curves (up to C). 3. Compute: ER= p L (C Q) + p B E[min(D B, Q)] = p L (C Q) + p B μ B p B E[max(D B Q,0)] Déjàvu? Newsvendor loss function; option pricing assumes leisure demand arrives before business and it exceeds capacity (the general formula is messier) Value of protecting capacity

14 Airline Impact Delta Airlines has estimated that selling just one seat per flight at a full fare rather than a discounted fare can add over $50 million to its annual revenues [Belobaba, 1998] American Airlines RM: $1.4 billion incremental revenue in the first 3 years Controlling the mix of fare products can translate into revenue increases of $200 to $500 million for carriers with total revenues of $1 to $5 billion [Fuchs, 1997] Extensions of the EMSR approach Static vs. dynamic booking limit (re solving) Multiple fare classes (pro rated EMSR) Cancellations & no shows (overbooking) Products to manage risks (callable, flexible, opaque) Salvage value (priceline, lastminute ) Demand modeling Price sensitivity Customer choice /substitutes Strategic behavior Learning & Expectation formation

15 but airlines operate networks O&D control next session Managing capacity & demand risk Key Points Optimal decision balances expected marginal revenue per inventory unit from each segment (EMR1= EMR2) Sell to a given segment as long as the margin exceeds the opportunity cost RM systems: sophisticated statistical and optimization tools designed to measure opportunity costs

16 Some RM Success Stories 1978 Airline deregulation in the U.S People Express vs. American Airlines 1991 RM for AA $1.4 billion in 3 years 1996 National Car Rental 1997 SNCF (Sabre); AA $1 billion; Marriott (4.7%) 1999 Deregulation Europe: telecom, media, energy e Distribution supports dynamic pricing & profiling 2000 manufacturing & retail (Dell, Ford, Gap) 2001 NBC (TV advertising) 2003 Texas Children s hospital (PROS) 2006 Eurostar (15.5%), Harrah s I.Popescu 2010 When General Conditions for DPRM legal constraints/regulation ability to segment the market some market power (ability to differentiate) limited arbitrage manage customer fairness perception & acceptance cost of implementation < revenue benefit **Operational (e.g. supply) constraints increase the value of DPRM I.Popescu 2010

17 Perception of Fairness Citizen Cane William Randolph Hearst ( ) and the price of art

18 Amazon Sept 27, 2000: Washington Post reports that an Amazon.com customer paid $24.49 for a DVD; one week later he was quoted $26.24 for the same DVD. After deleting a certain cookie, the price fell to $22.74! $26.24 Loyal Customer $22.74 Unknown Customer Customer Reaction Amazon is over in my book. I will never buy another thing from those guys!! I am so offended by what they did that I ll never buy another DVD from them again. Amazon is suck (sic). Source: dvdtalk.com One week later, Jeff Bezos reimbursed 6896 Amazon customers ~ $21,000.

19 I.Popescu DPRM 3 DPRM Issues with personalized prices Key issues: implementation & customer alienation Self ID incentive (student, card, coupons, search cost..) Non comparable (B2B contracts, insurance, loans) Diminishing marginal value of refining segmentation

20 Coca Cola Did you know? Over 1 billion cans of Coca Cola are sold every day in the world, and about 12% of those sales come from non human dispensers. Coca Cola is a product whose utility varies from moment to moment. In a final summer championship, when people meet in a stadium to enjoy themselves, the utility of a chilled Coca Cola is very high. So it is fair it should be more expensive. The machine will simply make this process automatic. Douglas Ivester,Chairman and CEO interview with Veja (NYT, Oct 28, 1999) Customer Perception ICE COLD SOFT DRINKS NOW $5.00

21 and Public Reaction a cynical ploy to exploit the thirst of faithful customers San Francisco Chronicle lunk headed idea Soda jerks Ticks me off Honolulu Star Bulletin Miami Herald Edmonton Sun What do you think? Epilogue Dec. 6, 1999: Ivester on voluntary retirement. June 2000: Doug Daft disclaimer: We are exploring innovative technology and communications systems that can actually improve product availability, promotional activity, and even offer consumers an interactive experience when they purchase a drink from a vending machine.. Why was this a problem for Coca Cola?

22 Dual Entitlement Most consumers believe that they are entitled to a reasonable price and firms are entitled to a reasonable profit (Kahenman, Knetsch, and Thaler, AER). Principle of dual entitlement: Buyer feels that both parties taking part in the transaction have gained. Implications: Raising price to recoup costs is OK Raising prices just to increase profits is NOT Information about the reason for price changes helps acceptance Next time: managing multiple resources The Break.com case read the case + study questions (c pack) + task (handout) Simplified data file: Break data for poll.xls (poll data worksheet) Answer the online poll by 3pm the day before class: 1) Which of these 7 deals is the least appealing to Break under current circumstances (see details)? 2) How can you improve the current practice for accepting contracts (see case p.7)? Friday: Group Assignment 2 (TNG case report) I.Popescu 2010