1. Conjoint Analysis - 1 New Product Design G Role of design in new product development G Conjoint Analysis for product design G Kirin case G “Courtyard by Marriott”

2. Conjoint Analysis - 2 Where companies want to put their efforts in new product development: u Getting our new products to the market on time, as planned (76% of companies interviewed). u Improving the appeal of our new products to customers (73%). u Developing our new products faster from concept to introduction (68%). u Developing products that are easier to manufacture, sell, install, and service (61%). u Reducing costs/investments related to new product development and introduction (47%). u Reducing the payback period of our new products (47%). u Increasing the number of new products (44%) Arthur D. Little Worldwide Survey

3. Conjoint Analysis - 3 Breakdown of Success Factors: Process versus Environment Source: Robert G. Cooper, Winning at New Products (1993)

4. Success measured using four factors: (1) whether it met or exceeded management’s criteria for success, (2) the profitability level (1-10 scale), (3) market share at the end of three years, and (4) whether it met company sales and profit objectives (1-10 scale). Source: Robert G. Cooper, Winning at New Products (1993 ) Kodak -2/99 - 4

5. Source: Robert G. Cooper, Winning at New Products (1993) Kodak -2/99 - 5

6. Source: Robert G. Cooper, Winning at New Products (1993) Kodak -2/99 - 6

7. Source: Robert G. Cooper (1993) Kodak -2/99 - 7

8. Conjoint Analysis - 8 Value of Good Design 80% of a product’s manufacturing costs are incurred during the first 20% of its design (varies with product category). Conjoint Analysis is a systematic approach for matching product design with the needs and wants of customers, especially in the early stages of the New Product Development process.

9. Conjoint Analysis - 9 A way to understand and incorporate the structure of customer preferences into the new product design process. In particular, it enables one to evaluate how customers make tradeoffs between various product attributes. The basic output of conjoint analysis are: A numerical assessment of the relative importance that customers attach to attributes of a product category The value (utility) provided to customers by each potential feature of a product What is Conjoint Analysis?

10. Conjoint Analysis - 10 Customer Value Assessment Procedures Customer Value Attitude-Based Direct Questions Unconstrained uFocus groups uDirect survey questions uImportance and attitude ratings urule-based system/AI/expert systems Constrained/Compositional Methods uMultiattribute value analysis uBenchmarking Indirect/(Decompositional Methods) uConjoint analysis uPreference Regression Behavior-Based uChoice models uNeural networks uDiscriminant analysis Inferential/Value-Based uInternal engineering assessment uIndirect survey questions uField value-in-use assessment

11. Conjoint Analysis - 11 Why is Conjoint Analysis Useful? G Designing new products that enhance customer value G Forecasting sales/market share/profit of alternative product concepts G Identifying market segments for which a given concept offers high value G Identifying the “best” concept for a target segment G Exploring impact of alternative pricing and service strategies G Demand forecasting/production planning with flexible manufacturing systems

12. Conjoint Analysis - 12 Measuring Importance of Attributes When ordering a computer, how important is… Circle one Not Very Important Price 1 2 3 4 5 6 7 8 9 Performance 1 2 3 4 5 6 7 8 9 Reliability 1 2 3 4 5 6 7 8 9 Delivery time 1 2 3 4 5 6 7 8 9

13. Conjoint Analysis - 13 Should we offer our business travelers more room space or a fax machine in their room? Should we offer a shower or a bath in a hotel room? Given a target cost for a product, should we enhance product reliability or its performance? Should we use a steel or aluminum casing to increase customer preference for the new equipment? How Do We Resolve These “Design” Questions?

14. Conjoint Analysis - 14 Measuring Importance Using Conjoint Analysis Restaurant Type Distance Formal? 1ItalianNearYes___ 2ItalianNearNo___ 3ItalianFarYes___ 4ItalianFarNo___ 5ChineseNearYes___ 6ChineseNearNo___ 7ChineseFarYes___ 8ChineseFarNo___

15. Conjoint Analysis - 15 Attributes Price (4 options) Delivery_terms (4 options) Perf. specs Delivery timePrice Exceed by 20% 6 months$600k Exceed by 5% 9 months$700k Meet specs 12 months$800k Short by 5% 15 months$900k Delivery terms Installed, 2-year guarantee Installed, 1-year guarantee Installed, service contract FOB seller, service contract A total of 256 (4x4x4x4) different offerings can be designed from these options! An Example Conjoint Study: Air Pollution Control Equipment Performance specs (4 options) Delivery time (4 options)

16. Conjoint Analysis - 16 Data for Conjoint Analysis: Paired Comparisons DeluxeMid-levelmodel Performance specsExceed by 20%Exceed by 5% Delivery time12 months6 months Price700k700k Delivery termsInstalled, 1 yearInstalled, service contract Which do you prefer? Which one would you buy?

17. Conjoint Analysis - 17 Example of a Sophisticated Data Gathering Instrument

18. Conjoint Analysis - 18 Data for Conjoint Analysis: Full-Profile Ratings or Ranks ProductPerf_spec Del_time Price Del_terms Example bundle Preference number score 1Exceed_20% 6_months $600k Inst_2yr 100 2Exceed_20% 9_months $700k Inst_ser 80 3Exceed_20% 12_months $800k FOB_ser 40 4 Exceed_20% 15_months $900k Inst_1yr 20 5 Exceed_5% 6_months $700k Inst_1yr 70 6 Exceed_5% 9_months $600k FOB_ser 75 7Exceed_5% 12_months $900k Inst_ser 65 8Exceed_5% 15_months $800k Inst_2yr 70 9Meet_specs 6_months $700k Inst_ser 50 10Meet_specs 9_months $900k Inst_2yr 20 11Meet_specs 12_months $600k Inst_1yr 40 12Meet_specs 15_months $700k FOB_ser 30 13Short_5% 6_months $900k FOB_ser 5 14Short_5% 9_months $800k Inst_1yr 10 15Short_5% 12_months $700k Inst_2yr 10 16Short_5% 15_months $600k Inst_ser 0

19. Conjoint Analysis - 19 Example Part Worth for Attributes

20. Conjoint Analysis - 20 Example Part Worths for Attribute Options

21. Conjoint Analysis - 21 U(P) =  a ij x ij k i=1 m j=1 P:A particular product/concept of interest U(P):The utility associated with product P a ij :Utility associated with the jth level (j = 1, 2, 3...k j ) on the ith attribute k j :Number of levels of attribute i m:Number of attributes x ij :1 if the jth level of the ith attribute is present in product P, 0 otherwise Conjoint Utility Computations j

22. Conjoint Analysis - 22 G The relevant market consists of products P 1, P 2,...P N. Some of theses may be existing products and, others concepts being evaluated. G (Assume) Each consumer will prefer to buy the product with the highest utility among those available Then forecasted market share for products P i is given by: Where K is the number of consumers who participated in the study Market Share Forecasts

23. Conjoint Analysis - 23 G Market consists of three products and three customers Product Market Share Computation (Air Pollution Control Equipment) Waste watchThermatrixWahlco Performance specs Exceed 5% Exceed 20%Meet Specs Delivery time 9 months 9 months6 months Price $800k $900k$600k Delivery terms FOB_ser Inst_1YrInst_ser

24. Conjoint Analysis - 24 Market Share Computation: (Air Pollution Control Equipment) Sunoco Mattel ICI Base 0 0 0 Meet specs 5 10 10 Exceed 5% 35 0 40 Exceed 20% 40 0 50 12 months 20 5 3 9 months 30 20 8 6 months 40 10 10 $800k 5 20 2 $700K 8 35 5 $600K 10 50 10 Inst_ser 6 5 10 Inst_1Yr 8 10 20 Inst_2Yr 10 20 30 Customer’s Utility

25. Conjoint Analysis - 25 Computed Utility for Products Market Share Computation: (Air Pollution Control Equipment) Waste Watch ThermatrixWahlco Sunoco 70 78 61 Mattel 40 30 75 ICI 50 78 40 G Maximum Utility Rule: If we assume customers will only buy the product with the highest utility, the market share for Thermatrix is 2/3 and 1/3 for Wahlco. G Share of preference rule: If we assume that each customer will buy each product in proportion to its utility relative to the other products, then market shares for the three products are: Waste Watch: 30.3% Thermatrix: 34.8 Wahlco: 34.9

26. Conjoint Analysis - 26 Identifying Segments based on Conjoint Part Worths Part-worth means for each option in each cluster: OptionOverallCL1CL2 ------------------------------------------ Exceed_20% 17.9 4.0027.9 Exceed_5% 17.5 4.0827.2 Meet_specs13.914.813.3 Short_5% 3.42 5.54 1.89 6_months11.1 6.3814.4 9_months17.412.920.7 12_months18.510.224.4 15_months 5.39 1.92 7.89 60023.035.813.7 70016.526.2 9.50 800 6.3510.0 3.72 900 1.48 2.77 5.56 Inst_2yr16.826.210.1 Inst_1yr15.020.511.0 Inst_serv 6.06 5.15 6.72 FOB 2.65 1.08 3.78 Cluster Proportion.419.581

27. Conjoint Analysis - 27 Members in Each Segment G Segment 1 u Cummins, Illinois-Tool, Mattell, Nes_Resn, Ralston Purina, New_W-Tech, Baltimore Gas, Applied Coatings, Pharmasyn, Th_Electric, Ag_Power, Vencor, El_chem. G Segment 2 u ICI, Deere, Intel, Mobil, Maytag, Air Products, Sunoco, HP, Conagra, Kimberly Clark, Hershey, Texaco, Union Carbide, Westinghouse Electric, Dow Chemical, Boise Cascade, Kodak, El_Chem, 3M

28. Conjoint Analysis - 28 Kirin Case G Run traditional cluster analysis to do segmentation based on needs variables and targeting on bases variables. G Run conjoint analysis to identify segments and also the products best suited for those segments. G Interpret all your results in both strategic and tactical terms -- what should Kirin do to position itself better for the future, and with respect to the particular the current product.

29. Conjoint Analysis - 29 Situations Where Conjoint Analysis Might Be Valuable G The new concept involves important tradeoffs affecting design, production, marketing, or other operational variables. G Product/service is realistically decomposable into a set of basic attributes. G Product/service choice tends to be high involvement. G Factorial combinations of basic attribute levels are believable. G Desirable new-product alternatives can be synthesized from basic alternatives. G Product/service alternatives can be realistically described, either verbally or pictorially. (Otherwise, actual product formulations should be considered). G Perceptions of hypothetical combinations are reasonably homogeneous across members of the target group.