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

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Development product design

Development: Product Design


The npd process

The NPD Process

“Fuzzy” Front End

Phase 1:

Opportunity

Identification

and Selection

Phase 2:

Concept

Generation/

Ideation

Phase 3:

Concept

Evaluation &

Screening

Phase 4:

Development

Phase 5:

Testing &

Launch


What is design

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!


Aesthetic evaluations of consumer products

Aesthetic Evaluations of Consumer Products

  • Balance

  • Movement

  • Rhythm

  • Contrast

  • Emphasis

  • Pattern

  • Unity


Contributions of design to the new products process

Contributions of Design to the New Products Process


Range of leading design applications

Purpose of Design

Aesthetics

Ergonomics

Function

Manufacturability

Servicing

Disassembly

Item Being Designed

Goods

Services

Architecture

Graphic arts

Offices

Packages

Range of Leading Design Applications


Assessment factors for an industrial design

Assessment Factors for an Industrial Design


Consumer response to product form adapted from bloch 1995

Psychological

Responses

to Product Form

Product

Form

Behavioral

Responses

  • Cognitive

  • Evaluations

  • Categorization

  • Beliefs

Aesthetic

Evaluations

Consumer Response to Product Form (Adapted from Bloch 1995)


What is product form

What is Product Form?

  • Objective Physical Properties of a Product

    • Form

    • Structure

    • Texture

    • Color


Psychological responses to consumer products

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


What does the design tell you

What Does the Design Tell You?


What does the design tell you1

What Does the Design Tell You?


New product development

New Product Development

Sales Forecasting & Financial Analysis


Estimating sales potential

Estimating Sales Potential


Sales potential estimation

Sales Potential Estimation

  • Often used to interpret concept test results


The concept statement

The Concept Statement


Sales potential estimation1

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


Sales potential estimation2

Sales Potential Estimation


Sales potential estimation3

Sales Potential Estimation

  • Translating Intent into Sales Potential

    • Example: Aerosol Hand CleanerAfter 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:


Sales potential estimation4

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)


From potential to forecast

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


Sales forecasts

Sales Forecasts

  • With Sales Potential Estimates

  • A-T-A-R Models

    • Best used with incremental innovations

    • Based on diffusion theory:

      • Awareness, Trial, Availability, Repeat


Development product design

ATAR


An a t a r model of innovation diffusion

An A-T-A-R Model of Innovation Diffusion

Figure 8.5

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


The a t a r model definitions

The A-T-A-R Model: Definitions

Figure 8.6

  • 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.


A t a r model application

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


Points to note about a t a r model

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.


Getting the estimates for a t a r model

Getting the Estimates for A-T-A-R Model

Figure 8.7

xx: Best source for that item.

x: Some knowledge gained.


Sales forecasts1

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


Bass model forecast of product diffusion

Bass Model Forecast ofProduct Diffusion

Figure 11.4


The bass model

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)]2Wherep = the “coefficient of innovation” [Average value=.04]q = the “coefficient of imitation” [Average value =.30]m= the total number of potential buyersY(t) = the total number of purchases by time t


The bass model1

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


Financial analysis

Financial Analysis


Financial analysis1

Financial Analysis

  • 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 launchedmargin = 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.)


Financial analysis later stages

Financial Analysis: Later Stages

  • Payback and Break-Even Times

    • Cycle Time

    • Payback Period

    • Break-Even Time (BET) = Cycle Time + Payback Pd.


Financial analysis later stages1

Financial Analysis: Later Stages

  • Payback and Break-Even Times


Financial analysis later stages2

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)


Financial analysis later stages3

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


Using opt to find the ecv

Using OPT to find the ECV

Commercial

Success

$PVI

Pcs

Technical Success

Yes

Launch

$C

Pts

Yes

No

Development

$D

Commercial

Failure

$ECV

No

Technical Failure

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


Using opt to find the ecv1

Using OPT to find the ECV

ECV = [ [(PVI * Pcs) - C] * Pts] - 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


Npv vs opt an example

NPV vs. OPT: An Example

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%

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


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