Design and Forecasting

8/4/2019 Design and Forecasting

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Development:Product Design



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





What Is Design? Has been defined as “the synthesis of technology

and human needs into manufacturable products.”

In practice, design can mean many things, rangingfrom styling to ergonomics to setting final productspecifications.

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 isabout to manufactured!



Aesthetic Evaluations of

Consumer Products Balance

Movement

Rhythm

Contrast

Emphasis Pattern

Unity



Contributions of Design to theNew Products Process



Range of Leading Design

ApplicationsPurpose of Design

AestheticsErgonomics

Function

Manufacturability

Servicing

Disassembly

Item BeingDesigned

Goods

Services

Architecture

Graphic arts

Offices

Packages



Assessment Factors for an

Industrial Design



Consumer Response to ProductForm (Adapted from Bloch 1995)

ProductForm

Psychological

Responses

to Product Form

Cognitive

Evaluations

• Categorization

• Beliefs

Aesthetic

Evaluations

Behavioral

Responses



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:



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 wouldbuys” actually will buy; 15% for the “probably will”s

Consumer Packaged Goods: 70-80% chance that the “definites” will buy; 33% chance for the “probablywill”s



Sales Potential Estimation



Sales Potential Estimation Translating Intent into Sales Potential

Example: Aerosol Hand Cleaner After examining norms for comparable existingproducts, 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 wouldactually 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 appropriatepercentages: 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 unitsx % 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 purchasersx 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

Buy i ng Un i t: Purchase point (person ordepartment/buying center).

Awa re : Has heard about the new product with somecharacteristic that differentiates it.

Ava i l ab l e : If the buyer wants to try the product, theeffort to find it will be successful (expressed as apercentage).

Tr i a l : Usually means a purchase or consumption of the product.

Repea t : 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 players

x 40% Percent awareness after one year

x 20% Percent of "aware" owners who will try productx 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

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 Market

Research

Concept Test Product Use

Test

Component

Testing

Market Test

Market Units XX X X X

Awareness X X X X

Trial XX X X

Availability X XX

Repeat X X X

Consumption X X X XX

Price/Unit X X X X XX

Cost/Unit X XX



Sales Forecasts With Sales Potential Estimates

Diffusion of Innovations The Bass Model:

Predicts pattern of trial (doesn’t include repeatpurchases) at the category level

Works for all types of products, and can be usedwith discontinuous innovations



Bass Model Forecast of

Product 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





Financial Analysis



Financial Analysis How Sophisticated?

Depends on the quality/reliability of the data andthe 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 discountsfuture)

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.




Payback and Break-Even Times




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 theGo/Kill options along the way(option values not accounted for in traditional NPV)




Payback and Break-Even Times Discounted Cash Flows (DCF, NPV, or IRR)

Options Pricing Theory (OPT) Recognizes that management can kill a project after anincremental 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 theproject -- 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

CommercialFailure$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%

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Design and Forecasting

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