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Semelhante a 453 new product_decisions
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453 new product_decisions
- 1. New Product Decisions MGT 453
- 5. Overview of “Stage-Gate” New Product Development Process Design Identifying customer needs Sales forecasting Product positioning Engineering Marketing mix assessment Segmentation Go No Go No Go No Reposition Harvest Opportunity Identification Market definition Idea generation Testing Advertising & product testing Pretest & prelaunch forecasting Test marketing Introduction Launch planning Tracking the launch Life-Cycle Management Market response analysis & fine tuning the marketing mix; Competitor monitoring & defense Innovation at maturity Go No
- 7. Graphical Representation of The Bass Model (Cell Phone Adoption) Time Non-cumulative Adoptions, n(t) pN Adoptions due to external influence Adoptions due to internal influence
- 8. million Source: eBay/SEC filings Number of Registered Users eBay (by Quarter) 1997
- 11. Representation as an Equation N(t) : Cumulative number of adopters until time t.
- 12. Parameters of the Bass Model in Several Product Categories Innovation Imitation Product/ parameter parameter Technology ( p ) ( q ) B&W TV 0.108 0.231 Color TV 0.059 0.146 Room Air conditioner 0.006 0.185 Clothes dryers 0.009 0.143 Ultrasound Imaging 0.000 0.534 CD Player 0.055 0.378 Cellular telephones 0.008 0.421 Steam iron 0.031 0.128 Oxygen Steel Furnace (US) 0.002 0.435 Microwave Oven 0.002 0.357 Hybrid corn 0.000 0.797 Home PC 0.121 0.281 A study by Sultan, Farley, and Lehmann in 1990 suggests an average value of 0.03 for p and an average value of 0.38 for q .
- 14. Forecasting Using the Bass Model—Room Temperature Control Unit Cumulative Quarter Sales Sales Market Size = 16,000 (At Start Price) 0 0 0 1 160 160 Innovation Rate = 0.01 4 425 1,118 (Parameter p ) 8 1,234 4,678 12 1,646 11,166 Imitation Rate = 0.41 16 555 15,106 (Parameter q ) 20 78 15,890 24 9 15,987 Initial Price = $400 28 1 15,999 32 0 16,000 Final Price = $400 36 0 16,000 Example computations Sales in Quarter 1 = 0.01 ´ 16,000 + (0.41–0.01) ´ 0 – (0.41/16,000) ´ (0) 2 = 160 Sales in Quarter 2 = 0.01 ´ 16,000 + (0.40) ´ 160 – (0.41/16,000) ´ (160) 2 = 223.35
- 17. Effects of Network Structure (Household Products) Distant links = 0 Distant links > 0 Average Density of Links q – Degree of Influence
- 21. Adjusting Stated Intentions to Get Actual Purchase Behavior ME New Product Forecasting 2006 - Some Who Say They Won’t, Do! Some Who Say They Will, Don’t Probability of Purchase Increases with Stated Intention
- 22. Multi-Year Forecast and Actual 9.4 Million TV homes forecast for June 99; Actual = 9.9 Million Forecast based on p and q of Cable TV (other alternative considered was Color TV) and maximum penetration set to 16% of population (half that in the stated intent survey).
- 26. ME New Product Forecasting 2006 - Population (billions) Gross World Product ($ trillions) 1990 10 5 20 250 Comparative Trajectories of Population/GDP From Global Scenario Group Great Transition Conventional Worlds Barbarization Fortress World Breakdown Policy Reform Reference Eco-communalism New sustainability paradigm
- 28. Preference Model: Purchase Probabilities Before New Product Use where : V ij = Preference rating from product j by participant i L ij = Probability that participant i will purchase product j R i = Products that participant i will consider for purchase (Relevant set) b = An index which determines how strongly preference for a product will translate to choice of that product (typical range: 1.5–3.0) ( V ij ) b L ij = –––––––– R i å ( V ik ) b k =1
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- People getting used to the idea of buying in auctions. Auctions help determine the correct price for products. Many antique dealers now use eBay to gauge the price of their inventory and products.
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- Explain logic of projecting trends – at the end of the 20 th century, trends would indicate that by 1980, we would have trains traveling at 500 miles per hour! It happened, but with different technology (airplane).
- Group your knowledge into two areas: (1) things you believe you know something about, and (2) elements you consider uncertain or unknowable. The first component casts the past forward, recognizing that our world possesses considerable momentum and continuity. For example, we can safely make assumptions about demographic shifts (such as increases in the average age) and substitution effects of new technologies (e.g., digital recording will eventually replace analog recording). Your challenge is to separate aspects you are very confident about (and willing to bet the farm on) from those that are largely uncertain. There are at least three tests of internal consistency: trends, outcome combinations, and reactions of major stakeholders. First, are the trends compatible within the chosen time frame? If not, remove the trends that don't fit. Second, do the scenarios combine outcomes of uncertainties that indeed go together? Japanese analog standards and evolution of digital technologies are not compatible with each other; so eliminate that possible pairing or scenario. Third, are the major stakeholders (e.g., TV studios) see themselves placedin positions they do not like, and can change?
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