1 11-1 McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc., All Rights Reserved.

1 11-1

McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc., All Rights Reserved.

2 11-2

CHAPTER ELEVEN

SALES FORECASTING AND FINANCIAL

ANALYSIS

3 11-3 Why Financial Analysis for New Products is Difficult

• Target users don’t know.

• If they know they might not tell us.

• Poor execution of market research.

• Market dynamics.• Uncertainties about

marketing support.

• Biased internal attitudes.

• Poor accounting.• Rushing products to

market.• Basing forecasts on

history.• Technology revolutions.

4 11-4

Forecasters Are Often Right

In 1967 they said we would have:

• Artificial organs in humans by 1982.

• Human organ transplants by 1987.

• Credit cards almost eliminating currency by 1986.

• Automation throughout industry including some managerial decision making by 1987.

• Landing on moon by 1970.

• Three of four Americans living in cities or towns by 1986.

• Expenditures for recreation and entertainment doubled by 1986.

Figure 11.1

5 11-5

Forecasters Can Be Very Wrong

They also said we would have:

• Permanent base on moon by 1987.

• Manned planetary landings by 1980.

• Most urbanites living in high-rises by 1986.

• Private cars barred from city cores by 1986.

• Primitive life forms created in laboratory by 1989.

• Full color 3D TV globally available.

Source: a 1967 forecast by The Futurist journal.

Note: about two-thirds of the forecasts were correct!

Figure 11.1(cont’d.)

6 11-6

Commonly Used Forecasting Techniques

Technique Time Horizon* Cost CommentsSimple Regression Short Low Easy to learnMultiple Regression Short-medium Moderate More difficult to

learn and interpretEconometricAnalysis

Short-medium Moderate to high Complex

Simple time series Short Very low Easy to learnAdvanced timeseries (e.g.,smoothing)

Short-medium Low to high,depending onmethod

Can be difficult tolearn but results areeasy to interpret

Jury of executiveopinion

Medium Low Interpret withcaution

Scenario writing Medium-long Moderately high Can be complexDelphi probe Long Moderately high Difficult to learn

and interpret

Figure 11.2

7 11-7

Handling Problems in Financial Analysis

• Improve your existing new products process.• Use the life cycle concept of financial analysis.• Reduce dependence on poor forecasts.

– Forecast what you know.

– Approve situations, not numbers (recall Campbell Soup example)

– Commit to low-cost development and marketing.

– Be prepared to handle the risks.

– Don’t use one standard format for financial analysis.

– Improve current financial forecasting methods.

8 11-8

0.9

0.603

0.0965 0.0614

0%10%20%30%40%50%60%70%80%90%100%

Aware Available Trial Repeat

A-T-A-R Model Results:Bar Chart Format Figure 11.3

9 11-9 Bass Model Forecast ofProduct Diffusion Figure 11.4

10 11-10

The Life Cycle of AssessmentFigure 11.5

11 11-11 Calculating New Product’s Required Rate of Return

Risk

% ReturnReqd. Rateof Return

Cost ofCapital

Avg. Riskof Firm

Risk on Proposed Product

Figure 11.6

12 11-12 Hurdle Rates on Returns and Other Measures Figure 11.8

Hurdle Rate Product Strategic Role or Purpose Sales Return on

Investment Market Share

Increase A Combat competitive entry $3,000,000 10% 0 Points B Establish foothold in new

market $2,000,000 17% 15 Points

C Capitalize on existing markets

$1,000,000 12% 1 Point

Explanation: the hurdles should reflect a product’s purpose,or assignment. Example: we might accept a very lowshare increase for an item that simply capitalized on ourexisting market position.

13 11-13

Hoechst-U.S. Scoring Model

Key Factors Rating Scale (from 1 - 10)1 ………. 4 ………. 7 ………. 10

Probability of TechnicalSuccess

<20% probability >90% probability

Probability of CommercialSuccess

<25% probability >90% probability

Reward Small Payback < 3 yearsBusiness-Strategy Fit R&D independent of R&D strongly supports

business strategy business strategyStrategic Leverage "One-of-a-kind"/ Many proprietary

dead end opportunities

Source: Adapted from Robert G. Cooper, Scott J. Edgett, and Elko J. Kleinschmidt. Portfolio Managementfor New Products, McMaster University, Hamilton, Ontario, Canada, 1997, pp. 24-28.

Figure 11.9