New Products Management- CHAPTER 11 SALES FORECASTING AND FINANCIAL ANALYSIS doc

CHAPTER 11
CHAPTER 11
SALES FORECASTING
SALES FORECASTING
AND FINANCIAL ANALYSIS
AND FINANCIAL ANALYSIS
McGraw-Hill/Irwin
Copyright ©2006 The McGraw-Hill Companies, Inc. All right reserved.
Why Financial Analysis for New
Why Financial Analysis for New
Products is Difficult
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.
Forecasters Are Often Right
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
Forecasters Can Be Very Wrong
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.
Figure 11.1
(cont’d.)
Source: a 1967 forecast by
The Futurist
journal.
Note: about two-thirds of the forecasts were correct!
Commonly Used Forecasting
Commonly Used Forecasting
Techniques
Techniques
Figure 11.2
Handling Problems in Financial Analysis
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.
Forecasting Sales Using Purchase
Forecasting Sales Using Purchase
Intentions
Intentions

Use top-two-boxes scores obtained in concept
testing, appropriately adjusted or calibrated.

Example: Recall for hand cleanser from Chapter 9:

Definitely buy = 5%


Probably buy = 36%

Based on history, calibrate as follows:

80% of “definitelies” actually buy

33% of “probablies” actually buy

Forecasted market share = (0.8)(5%) + (0.33)
(36%) = 16%.
Forecasting Sales Using Purchase
Forecasting Sales Using Purchase
Intentions (continued)
Intentions (continued)

The 16% forecast assumes 100% awareness
and availability.

Adjust downwards to account for incomplete
awareness and availability.

If 60% of the market is aware of the product
and has it available, market share is
recalculated to (0.6) (16%) = 9.6%.
Forecasting Sales Using A-T-A-R Model
Forecasting Sales Using A-T-A-R Model

Assume awareness = 90% and availability =67%.


Trial rate = 16% (16% of the market that is aware of
the product and has it available tries it at least once).

R
S
= proportion who switch to new product = 70%.

R
r
= proportion who repeat purchase the new product
= 60%.

R
t
= Long-run repeat purchase = R
S
/(1+R
s
-R
r
)
= 63.6%.

Market Share = T x R
t
x Awareness x Availability
= 16% x 63.6% x 90% x 67% = 6.14%.
The following bar chart shows this procedure
graphically.
A-T-A-R Model Results: Bar Chart

A-T-A-R Model Results: Bar Chart
Format
Format
Figure 11.3
Bass Model Forecast of
Bass Model Forecast of
Product Diffusion
Product Diffusion
Figure 11.4
The Life Cycle of Assessment
The Life Cycle of Assessment
Figure 11.5
Calculating New Product’s Required
Calculating New Product’s Required
Rate of Return
Rate of Return
Risk
% Return
Reqd. Rate
of Return
Cost of
Capital
Avg. Risk
of Firm
Risk on
Proposed
Product
Figure 11.6
Hurdle Rates on Returns and Other
Hurdle Rates on Returns and Other

Measures
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 low
share increase for an item that simply capitalized on our
existing market position.
Hoechst-U.S. Scoring Model
Hoechst-U.S. Scoring Model
Key Factors Rating Scale (from 1 - 10)
1 ………. 4 ………. 7 ………. 10
Probability of Technical
Success
<20% probability >90% probability
Probability of Commercial
Success
<25% probability >90% probability
Reward Small Payback < 3 years

Business-Strategy Fit R&D independent of R&D strongly supports
business strategy business strategy
Strategic Leverage "One-of-a-kind"/ Many proprietary
dead end opportunities
Source: Adapted from Robert G. Cooper, Scott J. Edgett, and Elko J. Kleinschmidt. Portfolio Management
for New Products, McMaster University, Hamilton, Ontario, Canada, 1997, pp. 24-28.
Figure 11.9
Specialty Minerals Scoring Model
Specialty Minerals Scoring Model

Management interest

Customer interest

Sustainability of competitive advantage

Technical feasibility

Business case strength

Fit with core competencies

Profitability and impact
Manufacturing Firm Scoring Model
Manufacturing Firm Scoring Model
(disguised)
(disguised)

Net Present Value


Internal Rate of Return

Strategic Importance of Project (how
well it aligns with business strategy)

Probability of Technical Success
Note: how in each of these examples, the
model contains financial as well as
strategic criteria.