Presentation on theme: "Demand and Revenue Management"— Presentation transcript:
1 Demand and Revenue Management Anton J. KleywegtApril 2, 2008
2 Revenue Management What is Revenue Management Why do Revenue ManagementPricing OptimizationDemand Modeling and Forecasting
3 What is Revenue Management Management of inventory, distribution channels and prices to maximize profit over the long runSelling the right product to the right customer at the right time at the right price
4 What is Revenue Management Revenue Management involves the following activitiesDemand data collectionDemand modelingDemand forecastingPricing optimizationSystem implementation and distribution
5 What is Revenue Management Airline industryHow many seats to make available at each of the listed fares, depending on the OD pair, time of year, time of week, remaining seats available, remaining time until departureWhat contracts and prices to provide to corporationsHow many seats to make available to consolidators and travel agents (if at all), and at what pricesHow much capacity to make available to cargo shippers and freight forwarders, and at what prices
6 What is Revenue Management Hotel industryHow much to charge for a room depending on the location, type of room, time of year, time of week, duration of stay
7 What is Revenue Management Ocean cargo industryWhich types of contracts to enter into with shippersHow much capacity to commit to each shipperWhich contract prices to have for each shipperHow to vary prices as a function of direction of trade, commodity, and time of year
8 What is Revenue Management Car rental industryHow much to charge for a rental car depending on the class of car, time of year, time of week, duration of rentRestaurant industryHow much to charge for lunch vs dinner
9 What is Revenue Management Manufacturing industryMake-to-stock: dynamic pricing of inventoryMake-to-order: dynamic pricing of orders, how much discount to give for orders in advanceMake-to-stock and make-to-order: prices of advance orders vs prices of inventory
10 What is Revenue Management Retail industryExample: fashion apparel industryProducts in fashion for a single seasonRetailer wants to sell available inventory for maximum profitPrices higher at start of seasonRetailer has to decide when to mark prices down, and by how much
11 What is Revenue Management Entertainment ticket pricingExample: opera houses let their ticket prices depend onThe performanceThe reviews received so farLocation of seat in opera houseDay of the week of the performanceTime of the day of the performanceTime of performance in the seasonRemaining time until the performanceNumber of remaining seats available
12 What is Revenue Management Golf coursesVariable pricing: Choose prices to vary bytime of dayday of weekseason of yearRound duration controlcontrol tee-time intervalcontrol uncertainty in arrival timecontrol uncertainty in duration
13 Hospital Contract Case Study Major customers of hospitalsInsurance companiesMedicareMedicaidIndividualsHospital contracts with major customersDiscount-off-listed-charges contractsPer-diem contractsCase-rate contractsCapitation contracts
14 Hospital Contract Case Study Example of setting per-diem rates
15 Hospital Contract Case Study Example of setting per-diem ratesObserve that most patients stay for only a few days, although a few patients make the average length of stay quite highStratified per-diem ratesCharge more per day to patients who stay for only a few daysResultsHigher average revenueLower standard deviation of revenue
16 Hospital Contract Case Study Higher average revenue clearly beneficial to the hospitalLower standard deviation of revenueBeneficial to the hospital?Yes. More predictable revenueBeneficial to the insurance company?Yes. More predictable costs
17 What is Revenue Management Overbooking may be part of revenue managementOverbooking important practice in many industries that use reservations, and where cancellations or no-shows may occurairlineshotelscar rentalcruise linesrestaurantscontractors (construction etc)
18 What is Revenue Management OverbookingImportant trade-off between opportunity cost of unused resources if cancellations or no-shows cause resources to be wasted, and cost of oversalesIn 1960’s, Simon and Vickrey proposed the use of auctions to allocate airline seats in case of oversalesAirlines rejected idea for many yearsNowadays, reverse Dutch auctions are widely used to allocate airline seats in case of oversales, and seem to be widely accepted
19 What is Revenue Management Dynamic pricing and the bullwhip effectDynamic pricing can increase demand variabilityThe case of Campbell SoupWild swings in demand and in shipments of chicken noodle soup from the manufacturer to distributors and retail storesIncrease in production, storage and logistics costsFrequent stockouts resulting in lost salesThe culprit: Trade promotions!
20 What is Revenue Management Dynamic pricing and the bullwhip effectDynamic pricing can be used to decrease demand variabilityPeak load pricing: lower prices during off-peak times, higher prices during peak timesAirlinesHotelsGolf coursesElectricity wholesale marketOil/gasoline?
21 What is Revenue Management Revenue Management may involve price discrimination, but it does not have to130Consumer surplus=1800P=130-QUnit cost = 10Firm’s profitsunder single price:(130-Q-10)Q6070PFirm profits=3600Deadweight loss=1800MC=10q130
22 Price Discrimination (continued) P=130-QUnit cost = 10What if the firmcould segmentthe market and charge twodifferent prices?130Consumer surplus=160090PFirm profits=480050Deadweight loss=800MC=10q4080130
25 What is Revenue Management The same product sold at different times for different prices is not necessarily price discrimination, because at different times...the production or distribution costs may be differentinventory costs were incurred to keep the product in stock until a later timethe product value may change over time, such as perishable or maturing or seasonal products, fashion goods, antiques.the remaining inventory may be differentinterest is earned if product is sold at an earlier timeconsumers value products differently at different points in timelocking sales in early reduces uncertainty
27 Fairness and Legal Issues Depending on the industry, there may be legal obstacles to revenue managementExamplesRegulated prices of utilities (this is changing)Prices in airline industry were regulated until price and quantity changes had to be approved by CABPricing in ocean cargo industry was regulated until carriers had to provide all shippers with the same essential contract termsSpot market pricing in ocean cargo industry is still regulated - 30 days notice required for price increases
28 Fairness and Legal Issues Golf course examplesKimes and Wirtz survey results (1 = extremely fair, 7 = extremely unfair)Time-of-day pricing: 3.41Varying price (for example, as function of bookings on hand): 6.16Two-for-one coupons for off-peak use: 1.80Time-of-booking pricing: 5.12Reservation fee/Charge for no-shows: 3.19Tee-time interval pricing: 3.95
29 Fairness and Legal Issues Amazon.com exampleFall 2000, Amazon conducted experiment to try to determine price sensitivity of demand for DVDsDiscounts between 20% and 40% offered randomlyCustomers who visited amazon.com multiple times noticed changing pricesFurious response by customers and press, suspecting Amazon varied price by demographicsWhy are varying airline prices accepted by most, and not varying DVD prices?
30 Why do Revenue Management Success storiesAmerican Airlines increased annual revenue with $500 million through revenue managementDelta Airlines increased annual revenue with $300 million through revenue managementMarriott hotels increased annual revenue with $100 million through revenue managementNational Car Rental was saved from liquidation with revenue managementCanadian Broadcasting Corporation increased revenue with $1 million per week
31 Why do Revenue Management Increasing competitionFewer restriction on international tradeMore efficient international transportationLow cost foreign competitorsCompetitors use revenue managementUse revenue management to stay on top
32 Why do Revenue Management At many companies, little cost-cutting juice can easily be extracted from operations. Pricing is therefore one of the few untapped levers to boost earnings, and companies that start now will be in a good position to profit fully from the next upturn. – McKinsey Quarterly, 2003
33 Revenue Management Optimization Control MethodsResource Bucket Control MethodsBid Price Control MethodsDynamic ProgrammingSoftware
34 Revenue Management Optimization Control Methods/Optimization MethodsOD basedStochasticLeg BasedDeterministicStaticDynamic
35 Revenue Management Optimization Resource Bucket Control MethodsIf supply of different products are related, for example if different products use shared resources or capacity, then revenue management should not be done separately for the different productsAlso if demand for products are related, for example complementary goods or substitutesExamplesAirlines: Itineraries with different origin-destination pairs share the same flight legs (resource)Hotels and rental cars: Multiple day bookings share capacity
36 Revenue Management Optimization Bid price methodsSimple single-stage deterministic LP modelInput:Lines of flight (LOF)The flights (legs/segments) each LOF traverses (flight-LOF incidence matrix A)Fares f1,f2,…,fk for each LOFDemand Dj for each LOF-fare combination j (not well-defined notion)Capacity Qi of each flight (leg/segment) iPrimal decision variables:xj = number of seats allocated to LOF-fare combination j
37 Revenue Management Optimization Dynamic programmingState of process: current bookings/seats available for each flight, competitor informationTransitions: take place through bookings and cancellationsDecisions: which prices/fares are quoted when booking requests are receivedPolicy: decision for each state x and time tObjective: determine optimal policyValue function: expected value V(x,t) as function of state x and time tSolving problem involves computing optimal value function V*(x,t)Another benefit: Optimal policy very simple:accept booking request if fare > V*(x,t) - V*(x-1,t)
38 Revenue Management Optimization Optimization Software SurveysFourer, R., “Linear Programming”, OR/MS Today, volume 32, number 3, pp , June 2005, <http://lionhrtpub.com/orms/surveys/LP/LP- survey.html>.Nash, S. G., “Nonlinear Programming”, OR/MS Today, volume 25, number 3, pp , June 1998, <http://lionhrtpub.com/orms/surveys/nlp/nlp. html>.Grossman, T.A., “Spreadsheet Add-Ins for OR/MS”, OR/MS Today, volume 29, number 4, pp , August 2002, <http://lionhrtpub.com/orms/surveys/SSA/SSA. html>.
39 Revenue Management Optimization Decision Support Software SurveysAksoy, Y. and Derbez, A., “Software Survey: Supply Chain Management”, OR/MS Today, volume 30, number 3, pp , June 2003, <http://lionhrtpub.com/orms/surveys/scm/scm-survey.html>.Buede, D., “Decision Analysis Software Survey: Aiding Insight IV”, OR/MS Today, volume 25, number 4, pp , August 1998.Hall, R., “Vehicle Routing Software Survey: On the Road to Recovery”, OR/MS Today, volume 31, number 3, pp , June 2004, <http://lionhrtpub.com/orms/surveys/Vehicle_Routing/vrss .html>.Maxwell, D.T., “Decision Analysis: Aiding Insight VII”, OR/MS Today, volume 31, number 5, pp , October 2004, <http://lionhrtpub.com/orms/surveys/das/das.html>.Swain, J. J., “'Gaming' Reality: Biennial survey of discrete-event simulation software tools”, OR/MS Today, volume 32, number 6, pp , December 2005, <http://lionhrtpub.com/orms/surveys/Simulation/Simulatio n.html>.Swain, J. J., “Power Tools for Visualization and Decision-Making”, OR/MS Today, volume 28, number 1, pp , February 2001.
40 Demand ForecastingThe first law of forecasting: The forecast is always wrongSources of forecast error:Modeling errorParameter errorMeasurement error
41 Demand Forecasting Modeling error The basic form of the demand model is wrongExampleSuppose we want to forecast demand d as a function of price pThe true demand function is d = exp(3-2p) / (1 + exp(3-2p))We try to estimate a linear demand model d = a – bp, with parameters a and b that are estimated with dataNo matter what values we estimate for a and b, the estimated model is wrong – modeling error
42 Demand Forecasting Parameter error The basic form of the demand model is correct, but we do not know the correct values of the parametersExampleThe true demand function is d = exp(3-2p) / (1 + exp(3-2p))We try to estimate a demand model d = exp(a-bp) / (1 + exp(a-bp)), with parameters a and b that are estimated with dataIf we estimate a=3 and b=2 (for example, with good data and a good statistical technique), then the estimated model is correct
43 Demand Forecasting Measurement error The basic form of the demand model is correct, but we do not know the correct values of the parameters, and data errors make it impossible to use statistical techniques to estimate the parameter valuesExampleThe true demand function is d = exp(3-2p) / (1 + exp(3-2p))We try to estimate a demand model d = exp(a-bp) / (1 + exp(a-bp)), with parameters a and b that are estimated with dataBecause of bad data, we estimate a=4 and b=-1
44 Demand ModelingIt is very important to understand and model customer behavior accuratelyIncorrect models of customer behavior can lead not only to suboptimal prices, but can lead to the systematic deterioration of models, prices, and profits over time – the spiral-down effect
45 Demand Modeling Spiral-down effect in airline revenue management For many years, airlines have used following simple model of customer behaviorSome time before departure, customer requests a ticket in a particular fare classAirline accepts or rejects the requestAbove model describes the way airline reservations systems workHowever, it does not accurately describe the way customers behave
46 Demand Modeling Spiral-down effect in airline revenue management Low fare tickets and high fare ticketsAirlines set aside chosen number of seats for high fare ticketsAirlines use observed sales to estimate the supposed “demand for high fare tickets”
47 Demand Modeling Spiral-down effect in airline revenue management Airline allows some low fare salesSome flexible customers (not modeled by the airlines) willing to buy high fare if that is the only option, now buy low fare ticketsAirlines observe more low fare sales and less high fare sales – decrease their estimate of “high fare demand”Airlines set aside fewer seats for high fare tickets, and allow more low fare salesMore customers buy low fare tickets, and the spiral down continuesSpiral-down effect is the consequence of an incorrect model of customer behavior
49 Demand Forecasting Judgmental forecasting methods “Expert” opinion Questionable: See the articlesArmstrong, J.S., “How Expert Are the Experts?”, Inc, pp.15-16, 1981Armstrong, J.S., “The Seer-Sucker Theory: The Value of Experts in Forecasting”, Technology Review, pp.16-24, 1980Consensus methods, such as Delphi technique
50 Demand Forecasting Statistical forecasting methods Non-causal methods Exponential smoothingTime series methodsCausal methodsLinear regressionNonlinear regressionDiscrete choice models (logit, probit, etc)Whatever the method, the basic approach is to find systematic behavior in data that one has reason to believe will continue in the future
51 Demand Forecasting Forecasting software surveys: Yurkiewicz, J., “Forecasting: Predicting Your Needs”, OR/MS Today, volume 31, number 6, pp , December 2004, <http://lionhrtpub.com/orms/surveys/FSS/fss- fr.html>.Swain, J. J., “Desktop Statistics Software: Serious Tools for Decision Making”, OR/MS Today, volume 26, number 5, pp , October 1999.Swain, J. J., “Looking for Meaning in an Uncertain World”, OR/MS Today, volume 28, number 5, pp , October 2001.Swain, J. J., “2005 Statistical Software Products Survey: Essential Tools of the Trade”, OR/MS Today, volume 32, number 1, pp , February 2005, <http://lionhrtpub.com/orms/surveys/sa/sa- survey.html>.
52 Revenue Management Implementation Business case: assessment ofRevenue opportunityDevelopment and support personnel needsDevelopment costMaintenance costHardwareSoftwareDBMSForecastingOptimizationInterfaces
53 Revenue Management Implementation Distribution systemCommunication network hardwareInterfaces with revenue managersInterfaces with customersManagement of customer awareness and customer perceptionsManagement of organizational change
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