1. Development: Product Design

2. The NPD Process Phase 1: Opportunity Identification and Selection Phase 2: Concept Generation/ Ideation Phase 3: Concept Evaluation & Screening Phase 4: Development Phase 5: Testing & Launch “Fuzzy” Front End

4. What Is Design? Has been defined as “the synthesis of technology and human needs into manufacturable products.” In practice, design can mean many things, ranging from styling to ergonomics to setting final product specifications. Design has been successfully used in a variety of ways to help achieve new product objectives. One thing it is not: “prettying up” a product that is about to manufactured!

5. Aesthetic Evaluations of Consumer Products Balance Movement Rhythm Contrast Emphasis Pattern Unity

6. Contributions of Design to the New Products Process

7. Range of Leading Design Applications Purpose of Design Aesthetics Ergonomics Function Manufacturability Servicing Disassembly Item Being Designed Goods Services Architecture Graphic arts Offices Packages

8. Assessment Factors for an Industrial Design

9. Consumer Response to Product Form (Adapted from Bloch 1995) Product Form Psychological Responses to Product Form Cognitive Evaluations Categorization Beliefs Aesthetic Evaluations Behavioral Responses

10. What is Product Form? Objective Physical Properties of a Product Form Structure Texture Color

11. Psychological Responses to Consumer Products Context Category Membership Functionality What happens in the absence of context? Design communicates, but does it do so effectively? How does the design and its context influence: Consumers’ reactions to the new products Consumers’ communication strategies

12. What Does the Design Tell You?

17. New Product Development Sales Forecasting & Financial Analysis

18. Estimating Sales Potential

19. Sales Potential Estimation Often used to interpret concept test results

20. The Concept Statement

21. Sales Potential Estimation Often used from concept test results Assumes awareness and availability Translating “Intent” into sales potential: Develop the “norms” carefully for a specific market and for specific launch practices Examples: Services: 45% chance that the “definitely would buys” actually will buy; 15% for the “probably will”s Consumer Packaged Goods: 70-80% chance that the “definites” will buy; 33% chance for the “probably will”s

22. Sales Potential Estimation

23. Translating Intent into Sales Potential Example: Aerosol Hand Cleaner After examining norms for comparable existing products, you determine that: 90% of the “definites” 40% of the “probables” 10% of the “mights” 0% of the “probably nots” and “definitely nots” will actually purchase the product Apply those %age to Concept Test results:

24. Sales Potential Estimation Translating Intent into Sales Potential Apply those %age to Concept Test results: 90% of the “definites” (5% of sample) =.045 40% of the “probables” (36%) =.144 10% of the “mights” (33%) =.033 0% of the last 2 categories =.000 Sum them to determine the %age who would actually buy:.045+.144+.033=.22 Thus, 22% of sample population would buy (remember: this % is conditioned on awareness & availability)

25. From Potential to Forecast With Sales Potential Estimates: To remove the conditions of awareness and availability, multiply by the appropriate percentages: If 60% of the sample will be aware (via advertising, etc.) and the product will be available in 80% of the outlets, then: (.22) X (.60) X (.80) =.11 11% of the sample is likely to buy

26. Sales Forecasts With Sales Potential Estimates A-T-A-R Models Best used with incremental innovations Based on diffusion theory: Awareness, Trial, Availability, Repeat

27. ATAR

28. An A-T-A-R Model of Innovation Diffusion Profits = Units Sold x Profit Per Unit Units Sold = Number of buying units x % aware of product x % who would try product if they can get it x % to whom product is available x % of triers who become repeat purchasers x Number of units repeaters buy in a year Profit Per Unit = Revenue per unit - cost per unit Figure 8.5

29. The A-T-A-R Model: Definitions Buying Unit: Purchase point (person or department/buying center). Aware: Has heard about the new product with some characteristic that differentiates it. Available: If the buyer wants to try the product, the effort to find it will be successful (expressed as a percentage). Trial: Usually means a purchase or consumption of the product. Repeat: The product is bought at least once more, or (for durables) recommended to others. Figure 8.6

30. A-T-A-R Model Application 10 million Number of owners of Walkman-like CD players x 40% Percent awareness after one year x 20% Percent of "aware" owners who will try product x 70% Percent availability at electronics retailers x 20% Percent of triers who will buy a second unit x $50 Price per unit minus trade margins and discounts ($100) minus unit cost at the intended volume ($50) = $5,600,000 Profits

31. Points to Note About A-T-A-R Model 1. Each factor is subject to estimation. Estimates improve with each step in the development phase. 2. Inadequate profit forecast can be improved by changing factors. If profit forecast is inadequate, look at each factor and see which can be improved, and at what cost.

32. Getting the Estimates for A-T-A-R Model xx: Best source for that item. x: Some knowledge gained. Figure 8.7

33. Sales Forecasts With Sales Potential Estimates Diffusion of Innovations The Bass Model: Predicts pattern of trial (doesn’t include repeat purchases) at the category level Works for all types of products, and can be used with discontinuous innovations

34. Bass Model Forecast of Product Diffusion Figure 11.4

35. The Bass Model Estimates s(t) = sales of the product class at some future time t: s(t) = pm + [q-p] Y(t) - (q/m) [Y(t)] 2 Where p = the “coefficient of innovation” [Average value=.04] q = the “coefficient of imitation” [Average value =.30] m= the total number of potential buyers Y(t) = the total number of purchases by time t

36. The Bass Model Important Feature Once p and q have been estimated, you can determine the time required to hit peak sales (t*) and the peak sales level at that time (s*): t* = (1/(p+q)) ln (q/p) s* = (m)(p+q) 2 /4q

37. Financial Analysis

38. How Sophisticated? Depends on the quality/reliability of the data and the stage you’re in Early Stages: Simple cost/benefit analysis or “Sanity Check” as 3M uses: attractiveness index = (sales X margin X (life).5 ) / cost sales= likely sales for “typical year” once launched margin = likely margin (in percentage terms) life = expected life of the product in years (sq root discounts future) cost = cost of getting to market (dev., launch, cap.ex.)

39. Financial Analysis: Later Stages Payback and Break-Even Times Cycle Time Payback Period Break-Even Time (BET) = Cycle Time + Payback Pd.

40. Financial Analysis: Later Stages Payback and Break-Even Times

41. Financial Analysis: Later Stages Payback and Break-Even Times Discounted Cash Flows (DCF, NPV, or IRR) The most rigorous analysis for new products: year-by-year cash flow projections discounted to the present the discounted cash flows are summed if the sum of the dcf’s > initial outlays, the project passes The “Dark Side” of NPV (for NPD) Unfairly penalizes certain projects by ignoring the Go/Kill options along the way (option values not accounted for in traditional NPV)

42. Financial Analysis: Later Stages Payback and Break-Even Times Discounted Cash Flows (DCF, NPV, or IRR) Options Pricing Theory (OPT) Recognizes that management can kill a project after an incremental investment is made At each phase of the NPD process, management is effectively “buying an option” on the project These options cost considerably less than the full cost of the project -- so they are effective in reducing risk Kodak uses a decision tree and uses OPT to compute the Expected Commercial Value (ECV) of a given project

43. Using OPT to find the ECV Development $D P ts P cs Technical Success Technical Failure Launch $C Commercial Success Commercial Failure $ECV Yes No Yes No KEY: Pts = Prob of tech success $D = Development costs remaining Pcs= Prob of comm success $C = Commercialization/launch costs $ECV = Expected commercial value $PVI = Present value of future earnings $PVI

44. Using OPT to find the ECV ECV = [ [(PVI * P cs ) - C] * P ts ] - D KEY: Pts = Prob of tech success $D = Development costs remaining Pcs= Prob of comm success $C = Commercialization/launch costs $ECV = Expected commercial value $PVI = Present value of future earnings

45. NPV vs. OPT: An Example TRADITIONAL NPV (no probabilities): 40 - 5 - 5 = 30Decision = Go NPV with probabilities: (.25 X 30) - (.75 X 10) = 0 Decision = Kill ECV or OPT: { [(40 x.5) - 5] *.5} - 5 = 2.5 Decision = Go Income stream, PVI (present valued) $40 million Commercialization costs (launch & captial)$ 5 million Development costs $ 5 million Probability of commercial success 50% Probability of technical success 50% Overall probability of success 25%