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New Product Development

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Q = Pot x T x Aw x Av x R x U. Pot=potential buyers. T=Trial rate (proportion ... Color TV 0.005 0.84. Air conditioners 0.010 0.42. Clothes dryers 0.017 0.36 ... – PowerPoint PPT presentation

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Title: New Product Development


1
New Product Development
  • Forecasting and Business Analysis

2
Overview
  • Sales forecast
  • Business analysis

3
Sales Forecasting
  • Stable/static market
  • Dynamic markets/innovations

4
Role of forecasts
  • Demonstration of feasibility/ROI
  • BEQ FC / (P-VC)
  • Is Q gt than BEQ?
  • ROI Q (P-VC) FC / I
  • Does ROI beat alternatives?
  • Planning
  • Production
  • Marketing
  • Future products

5
Challenges to forecasting
  • Consumer response
  • Attitude-behavior, PI-Beh. inconsistencies
  • External validity problems
  • Environmental uncertainties
  • Demand drivers
  • Segments
  • Marketing support

6
Stable/static markets
  • Market ratio model
  • Q Pot x T x Aw x Av x R x U
  • Potpotential buyers
  • TTrial rate (proportion who will try)
  • AwAwareness proportion
  • AvAvailability proportion
  • RRepeat rate
  • UUnits purchased on average

7
Dynamic/growth markets
  • Characteristics of innovations that affect
    diffusion
  • Diffusion of innovation growth modelsinnovators
    and imitators

8
Dynamic/growth markets
  • Diffusion of innovations
  • Willingness to adopt innovations
  • Relevant factors
  • Relative advantage
  • Communicability
  • Trialability
  • Complexity
  • Compatibility
  • Perceived risk

9
Adoption Probability over Time
10
Dynamic/growth markets
  • Bass Model (durables no repeat purchases)
  • Trial fn ( initial probability of adoption and
    effect of diffusion)
  • P(t)p(o) qY(t-1)/m
  • P(t)probability of trial
  • p(o)initial probability of adoption
  • Y(t-1)total number of people who have bought by
    the end of period t-1
  • mtotal number of potential buyers
  • qestimated diffusion factor

11
Bass Model
  • Sales fn (purchase probability and number of
    people who have not purchased)
  • S(t)m-Y(t-1)P(t)
  • Thus,
  • S(t)p(o)m q-p(o)Y(t-1) (q/m)Y(t-1)2
  • Or,
  • S(t)p(o) (m-Y(t-1) q Y(t-1)-Y(t-1) 2/m

Innovators plus imitators
12
Bass Model Example
13
Bass Model Estimates
14
Bass Model Estimates
  • Factors that affect the values of p and q
  • Diffusion factors, especially relative advantage
    for p
  • Complexity, communicability, and trialability for
    q
  • 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.
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