Sales Management 8

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Sales Management 8

• Estimating Demand

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Market Potential
Sales
Industry Forecast
(Industry Forecast Market Potential)
(Company Forecast Company Potential)
Company Potential
Company Forecast
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Time
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Key Terms

• Market Potential All possible sales
• Industry Forecast Likely sales, all companies
• Company Potential All possible sales for one
  company
• Company Sales Forecast Likely company sales
• NB All figures are expressed for a period of
  TIME.

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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

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Why Forecast Sales?

• Allocate resources
• Control operations
• Project Cash Flow (Important!)
• Capital/operating budgets
• Production schedules Inventory control
• Hiring collective bargaining
• Planning marketing and sales plans

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Methods of Forecasting

• Subjective
• Users Expectations
• Sales Force Composite
• Jury of Executive Opinion
• Delphi Technique

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Users Expectations

• Also called Buyers Intentions method
• Focus Groups
• Surveys
• Intention ? Behavior, but does correlate

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Sales Force Composite

• Salespeople are boundary-spanners
• Close to customers, competitors
• Fingers on the pulse of the market
• Survey sales force, and add up estimates
• Good starting point need adjustment

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Jury of Executive Opinion

• Top/key executives, 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

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Group Think
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Delphi Technique

• Similar to Executive Opinion
• Iterative/Secret Process
• Convergence

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Methods of Forecasting

• Objective
• Market Test
• Time Series Analysis
• Moving Averages
• Exponential Smoothing
• Decomposition
• Statistical Demand Analysis

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Test Market

• Pick representative city
• Full marketing effort
• Extrapolate results to rest of nation
• Expensive
• Takes time
• Tip your hand
• Competitors can skew results

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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)

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Moving Averages

• Average last n (2,4, whatever) years sales to
  predict the coming year
• 2005 5,000 units
• 2006 8,000 units
• 2007 8,000 units
• 2008 7,000 units estimated

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Decomposition

• Apply to monthly or quarterly data
• Account for
• Trends
• Cycles
• Seasons
• Random occurrences

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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.

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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

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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

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