DynamicDynamic PricingPricing toto improveimprove SupplySupply ChainChain PerformancePerformance David Simchi-Levi M.I.T. November 2000 PresentationPresentation OutlineOutline • The Direct-to-Consumer Model – Motivation – Opportunities suggested by DTC • Flexible Pricing Strategies • Future Research Directions CharacteristicsCharacteristics ofof thethe IndustrialIndustrial PartnerPartner • Make-to-stock environment • Annual revenue in 1998 was about $180 billion • Annual spending on supply is more than $70 billion • Huge product variety and a large number of parts • Inventory levels of parts and unsold finished goods is about $40 billion DirectDirect toto ConsumerConsumer (DTC)(DTC) Consumers Retailers Distribution Manufacturer Center TheThe ImpactImpact ofof thethe DTCDTC ModelModel • Valuable Information for the Manufacturer – e.g., accurate consumer demand data TraditionalTraditional SupplySupply ChainChain CustomerCustomer DemandDemand Order Size RetailerRetailer OrdersOrders DistributorDistributor OrdersOrders ProductionProduction PlanPlan Time Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998 TheThe DynamicsDynamics ofof thethe SupplySupply ChainChain CustomerCustomer DemandDemand Order Size ProductionProduction PlanPlan Time Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998 WeWe Conclude:Conclude: In Traditional Supply Chains…. • Order Variability is amplified up the supply chain; upstream echelons face higher variability. • What you see is not what they face. ConsequencesConsequences…….. • Increased safety stock • Reduced service level • Inefficient allocation of resources • Increased transportation costs InIn thethe DTCDTC Model...Model... ProductionProduction PlanPlan CustomerCustomer DemandDemand Volumes Time Source: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998 TheThe ImpactImpact ofof thethe DTCDTC ModelModel • Valuable Information for the Manufacturer – e.g., accurate consumer demand data • Product variety for the Consumer – e.g., allows for an assemble-to-order strategy FromFrom MakeMake--toto--StockStock Model….Model…. Suppliers Assembly Configuration ….to….to AssembleAssemble--toto--OrderOrder ModelModel Suppliers Assembly Configuration AA newnew SupplySupply ChainChain ParadigmParadigm • A shift from a Push System... – Production decisions are based on forecast • …to a Push-Pull System – Parts inventory is replenished based on forecasts – Assembly is based on accurate customer demand TheThe ImpactImpact ofof thethe DTCDTC ModelModel • Valuable information for the Manufacturer – e.g., accurate consumer demand data • Product variety for the Consumer – e.g., allows for an assemble-to-order strategy • Flexibility – e.g., price and promotions RevenueRevenue ManagementManagement • “Allocating the right type of capacity to the right kind of customer at the right price so as to maximize revenue or yield” • Traditional Industries: – Airlines – Hotels – Rental Car Agencies – Retail Industry FOR EXAMPLE… • McGill, J. and G. van Ryzin (1999), Revenue Management: Research Overview and Prospects. Transportation Science, 33, 2, pp. 233-256. TraditionalTraditional RequirementsRequirements • Perishable inventory • Limited capacity • Ability to segment markets • Product sold in advance • Fluctuating demand FOR EXAMPLE… • Weatherford, L. and S. Bodily (1992), A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management, Overbooking, and Pricing. Operations Research 40, 5, pp. 831-844. DynamicDynamic PricingPricing inin ManufacturingManufacturing • Non-perishable inventory • Production schedule needs to be determined • Production has capacity limitations • Demand and prices over time are bi-directional • Lost sales FOR EXAMPLE… • Federgruen, A. and A. Heching (1999), Combined Pricing and Inventory Control under Uncertainty. Operations Research, 47, 3, pp. 454-475. – Stochastic demand, allows for backlogging but not lost sales FlexibleFlexible PricingPricing inin ManufacturingManufacturing • Goals: – To extend the application of dynamic pricing and revenue management to non-traditional areas • Manufacturing industry with non-perishable products • Capacity allocation is the allocation of a perishable resource (i.e., build or no build decisions) – To integrate pricing, production and distribution decisions within the supply chain • “Allocate product to the right customer at the right price and at the right time” ModelModel FeaturesFeatures • Determines “when” and “how much” to sell • Capacity limitations on production • Incorporates lost sales • Known, time-dependent demand curves ModelModel AssumptionsAssumptions • Deterministic model • Single product of discrete units • T periods • Periodically varying parameters: – Production Capacity: Qt – Holding Cost: ht per unit – Production Cost: kt per unit – Upper and lower bounds on price – Concave Revenue Function: Rt(Dt) • Dt: the units of satisfied demand at period t • Example: Demand is a linear function of price RevenueRevenue CurveCurve • Revenue curve incorporates lost sales or limits on demand and remains concave with respect to satisfied demand Customer Revenue Demand Price Satisfied Demand TheThe PricingPricing Problem:Problem: ProblemProblem PPPP Maximize Profit f(D) = ? 1<t<T (Rt(Dt) - ht It - kt Xt ) Subject to: (1) Beginning Inventory: I0 = 0 (2) Inventory Balance: It = It-1 + Xt - Dt , t = 1,2,…,T (3) Production Capacity: Xt ? Qt, t = 1,2,…,T (4) Integrality: It , Xt, Dt, integer ? 0, t = 1,2,…,T At each period t, – Xt is the units of product produced – It is the end of period inventory – Dt is the satisfied demand (sales) WhenWhen doesdoes flexibleflexible pricingpricing matter?matter? • Computational analysis performed to answer the following questions: – How much does flexible pricing affect profit? – When does flexible pricing have the most impact on profit? – What other impacts does flexible pricing have? – How many prices in a horizon are needed to obtain significant profit benefit? ProfitProfit BenefitBenefit • Define profit potential due to flexible pricing to be: Profit with Dynamic Prices Profit Potential ? ? 1 Profit with Constant Price • Profit potential is the percentage of profit to be gained from dynamic prices ComputationalComputational DetailsDetails • Demand curves obtained from an Industrial Partner • Curves are aggregated over a number of products • 10 period problem • Varied capacity, demand, or both ManagerialManagerial InsightsInsights • Flexible pricing has the most impact on profit when: – Capacity is tightly constrained – Variability in capacity or demand exists ImpactImpact ofof ChangesChanges inin CapacityCapacity • As capacity becomes more constrained, the benefit of flexible pricing increases • As the variability in capacity increases, the benefit of flexible pricing increases Effect of Capacity Changes on Flexible Pricing Benefit when Demand is Constant 30% 25% 20% E(Cap/Dem*) = 0.5 15% E(Cap/Dem*) = 0.75 E(Cap/Dem*) = 1.0 % Benefit 10% 5% 0% 0 0.1 0.2 0.3 0.4 0.5 0.6 Coefficient of Variation (Cap/Dem*) ImpactImpact ofof ChangesChanges inin DemandDemand • As the variability in demand increases, the benefit in flexible pricing increases • As capacity becomes more constrained, the benefit in flexible pricing increases Effect of Demand Changes on Flexible Pricing Benefit when Capacity is Constant 25.0% 20.0% 15.0% Cap = 0.5 * Opt Base Dem Cap = 0.75 * Opt Base Dem 10.0% Cap = Opt Base Dem % Benefit 5.0% 0.0% 0 0.2 0.4 0.6 0.8 Coefficient of Variation (Cap/Dem*) OtherOther PotentialPotential ImpactsImpacts • Reduction of variability in sales or production schedule • Increase in average sales • Reduction of inventory • Reduction in average (or weighted average) price ImpactImpact onon VariabilityVariability ofof SalesSales • When demand is variable and capacity is constant, flexible pricing reduces the variability in sales compared to fixed pricing policies. Effect of Pricing Policy on Variability of Sales when Capacity is Constant 0.6 tion 0.5 Flex Pricing: Cap = .75 Base D* aria 0.4 Fix Pricing: Cap = .75 Base D* Demand) 0.3 t of V Flex Pricing: Cap = 1.0 Base Dem* ied en sf 0.2 ti Fix Pricing: Cap = 1.0 Base Dem* ici a ff e (S 0.1 Co 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 Coefficient of Variation (Uncapacitated Demand) ImpactImpact onon ProductionProduction ScheduleSchedule • When demand is variable and capacity is constant, flexible pricing often results in a smoother production schedule than that obtained using fixed pricing policies. Effect of Pricing Policy on Variability of Production Schedule when Capacity is Constant 0.4 0.35 0.3 Flex Pricing: Cap = .75 Base D* ariation 0.25 Fix Pricing: Cap = .75 Base D* 0.2 Flex Pricing: Cap = 1.0 Base Dem* ent of V 0.15 ici Fix Pricing: Cap = 1.0 Base Dem* (Production) 0.1 eff 0.05 Co 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 Coefficient of Variation (Uncapacitated Demand) ImpactImpact onon AverageAverage SalesSales • Flexible pricing policies increase average sales compared to fixed pricing policies. Effect of Pricing Policy on Average Sales when Capacity is Constant 12000 11000 10000 Demand Flex Pricing: Cap = .75 Base D* Fix Pricing: Cap = .75 Base D* 9000 Flex Pricing: Cap = 1.0 Base Dem* 8000 Fix Pricing: Cap = 1.0 Base Dem* ge Satisfied era Av 7000 6000 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 Coefficient of Variation (Uncapacitated Demand) ImpactImpact onon InventoryInventory • Flexible pricing policies decrease the average inventory level compared to fixed pricing policies. Effect of Pricing