Pricing and Customer Value Phil Simchi-Levi Kaminsky David [email protected] Philip Kaminsky Edith Simchi-Levi Outline Customer Value The Fundamentals of Pricing Strategies – Revenue Management & Customized Pricing Mail-in-Rebate strategies Dynamic.
Download ReportTranscript Pricing and Customer Value Phil Simchi-Levi Kaminsky David [email protected] Philip Kaminsky Edith Simchi-Levi Outline Customer Value The Fundamentals of Pricing Strategies – Revenue Management & Customized Pricing Mail-in-Rebate strategies Dynamic.
Pricing and Customer Value Phil Simchi-Levi Kaminsky David [email protected] Philip Kaminsky Edith Simchi-Levi Outline Customer Value The Fundamentals of Pricing Strategies – Revenue Management & Customized Pricing Mail-in-Rebate strategies Dynamic Pricing in SCM – Delayed Pricing vs. Delayed Production McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Customer Value How should a company measure the value of its products or services? The emphasis has moved from internal measures such as quality to customer satisfaction measures. The supply chain has a huge impact on perceived customer value: – Prices vs. service? – Delivery speed vs. price? – Specialization or one-stop shopping? Recall that responding to customer requirements is a basic part of supply chain management. Customer value drives changes in the supply chain, and is a critical input in determining the type of supply chain for a particular product – Large inventories – High level of customization McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi The Dimensions of Customer Value Conformance to requirements – Offer what the customer wants – Demand impacts the supply chain Product Selection – A proliferation of options makes the supply chain difficult to manage – Three trends Specialty stores (Starbucks, Subway) Megastores (Wal-Mart, Target) Specialized Megastores (Home Depot, OfficeMax) – Dealing with the proliferation: Build-to-order Centralized inventories A fixed set of options McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi The Dimensions of Customer Value Price and Brand – Pricing is a key part of the customer experience The correct supply chain supports the correct price Wal-mart – Brand works hand in hand with price As the number of salespeople decreases, the value of brand increases This is particularly true on the internet Value Added Services – It is hard to compete on price alone – Value added services are on the rise due to Commoditization of products The need to get closer to the customer Improving information technology Relationships and Experiences – An increased connection between the firm and its customers Dell manages the PC’s of large customers 3PL The Sony store McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Smart Pricing? Dell: – Same product is sold at a different price to different consumers (private/small or large business/government/academia/health care) – Price of the same product for the same industry varies Amazon – Books.com had a lower price than Amazon 99% of the time, yet Amazon had 80% of the market in 2000 while Books.com only 2% Nikon, Sharp… – Mail-In-Rebate Boise Cascade office – Prices of 12,000 items sold on-line may change as often as daily McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management Example: – A cruise ship with C=400 identical cabins – The Price-Quantity relationship McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management 2000 Price P=2000-2Q 1000 McGraw-Hill/Irwin No. seats © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management Example: – A cruise ship with C=400 identical cabins – The Price-Quantity relationship What is the price that the company should charge to maximize revenue? McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management Price Revenue=480,000 P0=1200 C=400 McGraw-Hill/Irwin No. seats © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management Price Money on the Table=160,000 P0=1200 C=400 McGraw-Hill/Irwin No. seats © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management Price P2=1600 McGraw-Hill/Irwin Q2=200 No. seats © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management Price P1=1200 C=400 McGraw-Hill/Irwin No. seats © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management Price Revenue=1600(200) + 1200(400-200)=560,000 P2=1600 P1=1200 McGraw-Hill/Irwin Q2=200 Q1 =400 No. seats © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management Can we increase revenue more? McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management Price P3=1800 Revenue=1800(100) + 1600(200-100) + 1200(400-200)=580,000 P2=1600 P1=1200 Q3=100 Q2=200 McGraw-Hill/Irwin Q1 =400 No. seats © 2003 Simchi-Levi, Kaminsky, Simchi-Levi How can the firm prevent customers from moving from one class to another? Sensitivity to Duration Sensitivity to Flexibility Low Leisure No Travelers Demand No Business Offer High Sensitivity to Price High McGraw-Hill/Irwin Travelers Low © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management “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 McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Traditional Requirements Perishable inventory Limited capacity Ability to segment markets – early-bird booking – over the weekend Product sold in advance Fluctuating demand McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Airline Revenue Management Two components of airline revenue maximization: – Customized Pricing: Various “fare products” offered at different prices for travel in the same O-D market – Yield Management (YM): Determines the number of seats available to each “fare class” on a flight, by setting booking limits on low fare seats McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management: Yield Management There are only two price classes – Leisure: (f2) $100 per ticket – Business: (f1) $250 per ticket Total available capacity= 80 seats Distribution of demand for business class is known McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Business Class: Demand Distribution Probability 0.3 0.25 0.2 0.15 0.1 0.05 0 0 5 10 15 20 25 Demand for Business Class McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 30 Revenue Management: Capacity Allocation There are only two price classes – Leisure: (f2) $100 per ticket – Business: (f1) $250 per ticket Total available capacity= 80 seats Distribution of demand for business class is known Enough demand for the leisure class McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Revenue Management: Capacity Allocation Objective: How many seats to allocate to the business class to maximize expected revenue McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Expected Revenue Expected Revenue 10000 9500 9000 8500 8000 7500 0 5 10 15 20 25 30 Business Class McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 35 Expected Revenue Expected Revenue 10000 9500 9000 8500 8000 7500 0 5 10 15 20 25 30 Business Class McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 35 Revenue Management: Capacity Allocation Optimality Condition: Choose the number of seats for the business class such that marginal revenue from each class is the same McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Optimality Condition Margina Revenue Business 300 250 200 150 100 50 0 0 McGraw-Hill/Irwin 5 10 15 20 25 30 © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 35 Optimality Condition Margina Revenue Business 300 250 200 150 Marginal Revenue Leisure 100 50 0 0 McGraw-Hill/Irwin 5 10 15 20 25 © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 30 35 Optimality Condition Margina Revenue Business 300 250 200 150 Marginal Revenue Leisure 100 50 0 0 McGraw-Hill/Irwin 5 10 15 20 25 © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 30 35 Benefits of Revenue Management in the Airline Industry Evidence of airline revenue increases of 4 to 6 percent: – With effectively no increase in flight operating costs RM allows for tactical matching of demand vs. supply: – Booking limits can help channel low-fare demand to empty flights – Protect seats for highest fare passengers on forecast full flights McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Mail-in-Rebate What is the manufacturer trying to achieve with the rebate? – Why the manufacturer and not the retailer? Should the manufacturer reduce the wholesale price instead of the rebate? Are there other strategies that can be used to achieve the same effect? McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Mail-in-Rebate A Retailer and a manufacturer. – Retailer faces customer demand. – Retailer orders from manufacturer. Variable Production Cost=$200 Selling Price=? Retailer Manufacturer Wholesale Price=$900 McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Demand-Price Relationship 10000 Demand P=2000-0.2Q 2000 McGraw-Hill/Irwin Price © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Retailer Expected Profit (No Rebate) 1,600,000 1,400,000 Retailer Expected Profit 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 500 1,000 1,500 2,000 2,500 3,000 3,500 3,654 4,110 O rd e r McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 4,567 4,547 Retailer Expected Profit (No Rebate) 1,600,000 $1,370,096 1,400,000 Retailer Expected Profit 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 500 1,000 1,500 2,000 2,500 3,000 3,500 3,654 4,110 O rd e r McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 4,567 4,547 Manufacturer Profit (No Rebate) 6,000,000 Manufacturer Profit 5,000,000 4,000,000 3,000,000 2,000,000 1,000,000 7, 85 5 7, 44 1 7, 02 8 6, 61 4 6, 20 1 5, 78 8 5, 37 4 4, 96 1 4, 54 7 4, 56 7 4, 11 0 3, 65 4 3, 50 0 3, 00 0 2, 50 0 2, 00 0 1, 50 0 1, 00 0 50 0 0 Order McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Manufacturer Profit (No Rebate) 6,000,000 Manufacturer Profit 5,000,000 4,000,000 3,000,000 $1,750,000 2,000,000 1,000,000 7, 85 5 7, 44 1 7, 02 8 6, 61 4 6, 20 1 5, 78 8 5, 37 4 4, 96 1 4, 54 7 4, 56 7 4, 11 0 3, 65 4 3, 50 0 3, 00 0 2, 50 0 2, 00 0 1, 50 0 1, 00 0 50 0 0 Order McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Retailer Expected Profit ($100 Rebate) 1,800,000 1,600,000 1,400,000 Retailer Expected Profit 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 4,547 Order McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 4,961 Retailer Expected Profit ($100 Rebate) 1,800,000 $1,644,115 1,600,000 1,400,000 Retailer Expected Profit 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 4,547 Order McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 4,961 Manufacturer Profit ($100 Rebate) 6,000,000 Manufacturer Profit 5,000,000 4,000,000 3,000,000 2,000,000 1,000,000 McGraw-Hill/Irwin Order 8, 26 8 7, 85 5 7, 44 1 7, 02 8 6, 61 4 6, 20 1 5, 78 8 5, 37 4 4, 96 1 4, 54 7 4, 56 7 4, 11 0 4, 00 0 3, 50 0 3, 00 0 2, 50 0 2, 00 0 1, 50 0 1, 00 0 0 © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Manufacturer Profit ($100 Rebate) 6,000,000 Manufacturer Profit 5,000,000 4,000,000 3,000,000 $1,810,392 2,000,000 1,000,000 McGraw-Hill/Irwin Order 8, 26 8 7, 85 5 7, 44 1 7, 02 8 6, 61 4 6, 20 1 5, 78 8 5, 37 4 4, 96 1 4, 54 7 4, 56 7 4, 11 0 4, 00 0 3, 50 0 3, 00 0 2, 50 0 2, 00 0 1, 50 0 1, 00 0 0 © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Retailer Expected Profit (Reduced Wholesale Price $100 ) 1,800,000 1,600,000 Retailer Expected Profit 1,400,000 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 Order McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 5,024 Retailer Expected Profit (Reduced Wholesale Price $100 ) 1,800,000 $1,654,508 1,600,000 Retailer Expected Profit 1,400,000 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 Order McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 5,024 Manufacturer Profit (Reduced Wholesale Price $100) 5,000,000 4,500,000 Manufacturer Profit 4,000,000 3,500,000 3,000,000 2,500,000 2,000,000 1,500,000 1,000,000 500,000 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 5,024 4,961 5,374 5,788 6,201 6,614 7,028 Order McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 7,441 7,855 Manufacturer Profit (Reduced Wholesale Price $100) 5,000,000 4,500,000 Manufacturer Profit 4,000,000 3,500,000 3,000,000 2,500,000 $1,800,000 2,000,000 1,500,000 1,000,000 500,000 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 5,024 4,961 5,374 5,788 6,201 6,614 7,028 Order McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi 7,441 7,855 Mail-in-Rebate Strategy No Rebate With Rebate ($100) Reduce Wholesale P ($100) McGraw-Hill/Irwin Retailer Manufacturer 1,370,096 1,750,000 1,644,115 1,810,392 1,654,508 1,800,000 © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Total 3,120,096 3,454,507 3,454,508 Mail-in-Rebate Strategy No Rebate With Rebate ($100) Reduce Wholesale P ($100) Global Optimization McGraw-Hill/Irwin Retailer Manufacturer 1,370,096 1,750,000 1,644,115 1,810,392 1,654,508 1,800,000 © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Total 3,120,096 3,454,507 3,454,508 3,929,189 Managerial Insights Mail in Rebate allows supply chain partners to move away from sequential strategies toward global optimization – Provides retailers with upside incentive Mail in Rebate outperforms wholesale price discount for manufacturer Other advantages of rebates: – Not all customers will remember to mail them in – Gives manufacturer better control of pricing McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Smart Pricing Customized Pricing – Revenue Management Techniques Distinguish between customers according to their price sensitivity – Influence retailer pricing strategies – Move supply chain partners toward global optimization McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi Smart Pricing Dynamic Pricing – Changing prices over time without necessarily distinguishing between different customers – Find the optimal trade-off between high price and low demand versus low price and high demand McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi When does Dynamic Pricing Provide Significant Profit Benefit? Limited Capacity Demand Variability Seasonality in Demand Pattern Short Planning Horizon McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi The Internet makes Smart Pricing Possible Low Menu Cost Low Buyer Search Cost Visibility – To the back-end of the supply chain allows to coordinate pricing, production and distribution Customer Segmentation – Difficult in conventional stores and easier on the Internet Testing Capability McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi A Word of Caution Amazon.com experimented with dynamic pricing – customers responded negatively Coca-Cola distributors rebelled against a seasonal pricing scheme Opaque fares (priceline.com, hotwire.com) – Determining the correct mix of opaque and regular fares is difficult. McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi