Development: Product Design

The NPD Process

Phase 1:Opportunity

Identificationand Selection

Phase 2:Concept

Generation/Ideation

Phase 3:Concept

Evaluation &Screening

Phase 4:Development

Phase 5:Testing &

Launch

“Fuzzy” Front End

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

Balance Movement Rhythm Contrast Emphasis Pattern Unity

Contributions of Design to the New Products Process

Range of Leading Design Applications

Purpose of Design

AestheticsErgonomicsFunctionManufacturabilityServicingDisassembly

Item Being Designed

GoodsServicesArchitectureGraphic artsOfficesPackages

Assessment Factors for an Industrial Design

Consumer Response to Product Form (Adapted from Bloch 1995)

Product Form

PsychologicalResponses

to Product Form

CognitiveEvaluations

• Categorization• Beliefs

AestheticEvaluations

BehavioralResponses

What is Product Form?

Objective Physical Properties of a Product Form Structure Texture Color

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?

New Product Development

Sales Forecasting & Financial Analysis

Estimating Sales Potential

Sales Potential Estimation Often used to interpret concept

test results

The Concept Statement

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 Estimation

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 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 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 With Sales Potential Estimates A-T-A-R Models

Best used with incremental innovations

Based on diffusion theory: Awareness, Trial, Availability, Repeat

ATAR

An A-T-A-R Model of Innovation DiffusionProfits = 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

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

A-T-A-R Model Application

10 million Number of owners of Walkman-like CD playersx 40% Percent awareness after one yearx 20% Percent of "aware" owners who will try productx 70% Percent availability at electronics retailersx 20% Percent of triers who will buy a second unitx $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

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

xx: Best source for that item.x: Some knowledge gained.

Figure 8.7

Item MarketResearch

Concept Test Product UseTest

ComponentTesting

Market Test

Market Units XX X X XAwareness X X X XTrial XX X XAvailability X XXRepeat XX XConsumption X X X XXPrice/Unit X X X X XXCost/Unit X XX

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 ofProduct Diffusion

Figure 11.4

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

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 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.)

Financial Analysis: Later Stages Payback and Break-Even Times

Cycle Time Payback Period Break-Even Time (BET) = Cycle Time +

Payback Pd.

Financial Analysis: Later Stages Payback and Break-Even Times

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 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

Development$D

Pts

Pcs

Technical Success

Technical Failure

Launch$C

CommercialSuccess

Commercial Failure$ECV

Yes

No

Yes

No

KEY: Pts = Prob of tech success $D = Development costs remainingPcs= Prob of comm success $C = Commercialization/launch costs$ECV = Expected commercial value $PVI = Present value of future earnings

$PVI

Using OPT to find the ECV

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

KEY:

Pts = Prob of tech success $D = Development costs remainingPcs= Prob of comm success $C = Commercialization/launch costs$ECV = Expected commercial value $PVI = Present value of future earnings

NPV vs. OPT: An Example

TRADITIONAL NPV (no probabilities):40 - 5 - 5 = 30 Decision = 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 millionCommercialization costs (launch & captial) $ 5 millionDevelopment costs $ 5 millionProbability of commercial success 50%Probability of technical success 50%Overall probability of success 25%