Transcript 8 Forecasting - Bob McDonald

Sales Management 8
Estimating Demand
Sales
Market Potential
Industry Forecast
(Industry Forecast ≤ Market Potential)
(Company Forecast ≤ Company Potential)
Company Potential
Company Forecast
0
Time
Key Terms
• Market Potential: All possible ______
• Industry Forecast: Likely _________,
all companies
• Company Potential: All possible
_________for one company
• Company Sales Forecast: Likely
company _________
NB: All figures are expressed for a period of ___.
So how do you estimate demand?
• Determine WHO will use the product.
– Which segment(s)?; Size?
• Determine their RATE of use.
– New/Replacement; Frequency.
• WHO buys product?
– Purchasing agent, parent, lover, uncle
• WHAT is their motivation to purchase?
– Life event, new business, new market, fun
Why Forecast Sales?
•
•
•
•
•
•
•
Allocate _________
Control _________
Project Cash Flow (Important!)
Capital/operating budgets
Production schedules & _________control
Hiring; collective _________
Planning marketing and sales plans
Methods of Forecasting
• Subjective
– Users’ Expectations
– Sales Force Composite
– Jury of Executive Opinion
• Delphi Technique
Users’ Expectations
•
•
•
•
Also called Buyers’ _________method
__________________
_________
Intention ≠ Behavior, but does
correlate
Sales Force Composite
•
•
•
•
Salespeople are _________
Close to customers, competitors
Fingers on the pulse of the market
Survey sales force, and add up
estimates
• Good starting point; need adjustment
Jury of Executive Opinion
• Top/key _________, perhaps outside
consultants, give best estimate
• Not boundary spanners, but see “Big
Picture”
• May need discussion to reach an
estimate that everyone can agree on
Delphi Technique
• Similar to Executive Opinion
• _________Process
• _________
Methods of Forecasting
• Objective
– Market Test
– Time Series Analysis
• Moving Averages
• Exponential Smoothing
• Decomposition
– Statistical Demand Analysis
Test Market
• Pick “_________” city
• Full marketing effort
• _________results to rest of nation
Disadvantages:
• _________
• _________
• _________
• _________
Time Series Analysis
• Use historical (not hysterical) data to
predict future
• Like driving by looking in the rear-view
mirror
• Estimate starts in “ballpark” (not the franks)
Moving Averages
• Average last n (=2,4, whatever) years
sales to predict the coming year
2000: 5,000 units
2001: 8,000 units
2002: 6,500 units estimated
Decomposition
• Apply to monthly or quarterly data
• Account for:
–
–
–
–
_________
_________
_________
_________
Statistical Demand Analysis
• Use regression or other techniques to
determine relationship between sales and
predictor factors.
• Need good data and analytical skills.
• Example:
– Home heating oil demand = Function of
temperature, sun, last fill, tank size, & history.
What do companies use?
• They tend to rely more heavily on
qualitative than quantitative.
• Especially sales force composite and
jury of executive opinion.
• Easier, quicker, perhaps accurate
enough
Sales Territories
• Design territories
– Need a market index to compare
• Industrial Goods
– Standard Industrial Classification
– North American Industrial Classification
System
• Consumer goods
– Buying Power Index = (5I + 2P + 3R)/10
• % disposable personal Income
• % US Population
• % total Retail sales