111-1
PERTEMUAN 5-6
SALES FORECASTING AND
FINANCIAL ANALYSIS
(Perkiraan Penjualan dan
Analisis Keuangan)
211-2
Tujuan Instruksional Khusus
• Mahasiswa mampu memperkirakan penjualan
produk baru
311-3
Proses Pengambilan Keputusan yang Rasional
• Mengenali Problem Keputusan
• Mendifinisikan ‘goal’ atau
obyektif
• Mengumpulkan semua Informasi
yang Relevan
• Mengindentifikasikan satu set
alternatif keputusan yang layak
• Memilih Kriteria Keputusan
yang digunakan
• Memilih alternatif yang paling
baik?
411-4
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.
511-5
Forecasters Are Often Right
Figure 11.1
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.
611-6
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.)
711-7
Commonly Used Forecasting Techniques
Figure 11.2
Technique
Simple Regression
Multiple Regression
Time Horizon*
Short
Short-medium
Cost
Low
Moderate
Econometric
Analysis
Simple time series
Advanced time
series (e.g.,
smoothing)
Jury of executive
opinion
Scenario writing
Delphi probe
Short-medium
Moderate to high
Short
Short-medium
Medium
Very low
Low to high,
depending on
method
Low
Medium-long
Long
Moderately high
Moderately high
Comments
Easy to learn
More difficult to
learn and interpret
Complex
Easy to learn
Can be difficult to
learn but results are
easy to interpret
Interpret with
caution
Can be complex
Difficult to learn
and interpret
811-8
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.
911-9
A-T-A-R Model Results:
Bar Chart Format
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Figure 11.3
0.9
0.603
Aware
Available
0.0965
0.0614
Trial
Repeat
11-10
10
Bass Model Forecast of
Product Diffusion
Figure 11.4
11-11
11
The Life Cycle of Assessment
Figure 11.5
Calculating New Product’s
Required Rate of Return
11-12
12
Figure 11.6
% Return
Reqd. Rate
of Return
Cost of
Capital
Risk
Avg. Risk
of Firm
Risk on
Proposed
Product
11-13
13
Hurdle Rates on Returns and Other
Measures
Product
A
B
C
Strategic Role or Purpose
Sales
Combat competitive entry
Establish foothold in new
market
Capitalize on existing
markets
$3,000,000
$2,000,000
Hurdle Rate
Return on
Investment
10%
17%
$1,000,000
12%
Figure 11.8
Market Share
Increase
0 Points
15 Points
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.
11-14
14
Return to the PIC
• Seven-point scoring model:
- Management interest
- Customer interest
- Sustainability of competitive advantage
- Technical feasibility
- Business case strength
- Fit with core competencies
- Profitability and impact
11-15
15
Hoechst-U.S. Scoring Model
Key Factors
Probability of Technical
Success
Probability of Commercial
Success
Reward
Business-Strategy Fit
Strategic Leverage
1
……….
<20% probability
<25% probability
Small
R&D independent of
business strategy
"One-of-a-kind"/
dead end
4
Rating Scale (from 1 - 10)
……….
7
Figure 11.9
……….
10
>90% probability
>90% probability
Payback < 3 years
R&D strongly supports
business strategy
Many proprietary
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.
11-16
16
Summary
…