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Lecture 4 Demand in Business Forecasting

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Title: Lecture 4 Demand in Business Forecasting


1
Lecture 4Demand in Business Forecasting
  • Application of the law of demand is not simple or
    we would not be here.
  • In a highly competitive world, successful
    application of the law of demand can have a
    significant impact on profits.

2
Why Demand Is Not Easy to Measure
  • Changes in the design of products and entry of
    new products mean limited lifecycles. Such
    changes make forecasting demand more difficult
    because you use data from previous products and
    time periods.
  • Expanding business to new markets means new
    demographics (customer base), facing new
    competitors, different seasonal factors,
    packaging requirements, and distributional
    channels create mini-markets within a product
    market. Constant change in markets means changes
    in demand.

3
Accurate Measures Difficult
  • Difficulty in interpretation of historical data
    Sales, orders, shipments and invoices are
    historical data that can cause confusion.
  • This may be innocent evidence of theft evidence
    of bad record keeping. The numbers rarely match
    up. Besides trying to measure demand an
    opportunity to try to understand company data
    accuracy.

4
Measurement Difficulties
  • Sales at one time may not reflect future demand
    as it may be affected by substitutes or other
    factors that may not be relevant in the next time
    period.
  • Demand is often underestimated when based on
    sales data. Example were sales in a given time
    period actual demand or did the stock run out,
    thereby cutting sales (under-measuring real
    demand)?

5
Demand Forecasting
  • Demand forecasts are statistical estimates for
    the future. Forecasts can be improved by
    determining probability distributions for demand
    points by location and for specific times.
  • Try to measure the degree to which actual demand
    deviates from prior demand forecasts. Improve
    point estimates.
  • Based on experimenting with data, determine
    relevant time period. Example Anheuser-Busch
    uses five-year historical data to better
    understand product lifecycles and seasonal
    demand.

6
Improving Demand Measures
  • Detailed point-of-sale data (bar codes on
    products) allows better estimates. These can be
    compared to vendor inventory or other data
    sources to check accuracy.
  • Revision is a good idea as time passeswere the
    estimates made six months ago for next year still
    the best estimate?

7
Improving Demand Measures
  • More measures of possibly relevant factors
  • competitor prices, regional events,
    demographics, and weather. Some of this
    information is low cost. Computer time is low
    cost. Analysis is not.
  • Remember the better we forecast demand for
    output, the better we control inputs (cost).

8
Improving Measures
  • RFID (radio frequency identification devices)
    provide sellers and buyers better control of
    point-of-sale measures and inventory from
    production through distribution to the shelf
    level. Wal-Mart demands thiswhere are all goods
    at all times.

9
Improving Demand Visibility
  • Data collected more frequently provides better
    estimates of forecasts.
  • More detailed data provides chance for greater
    accuracy.
  • Data from different functional areas sales,
    marketing, finance, logistics - allow for cross
    checks and possible insights (theft?).

10
Benefits of Good Measures
  • Information and forecasting is not costless, but
    a 10 improvement in forecasting can increase
    profits by reducing number of lost sales costs
    of handling excess goods and the costs of
    insuring and storing excess inventory.
  • Firms that estimate demand can reduce costs, set
    prices more accurately, and increase profits.

11
Similar points from the Harvard Business Review
  • Studies of companies show many pricing errors due
    to lack of internal controls.
  • Common problems
  • Invoices do not match prices quoted.
  • Discounts granted by sales agents are larger
    than needed (difference between agents incentive
    and what is best for the firm).
  • Inconsistent pricing by different sales
    repssome give bigger discounts than others.

12
Practical Notes from HBR
  • Common pricing/sales problems
  • Sales reps do not properly assess or understand
    customers needs (their demand). More background
    needed prior to their visits. Know your
    customers.
  • Sales reps insist on quick response from pricing
    analysts to finalize sale, leading to snap
    decisions (more mistakes). Sales reps also
    guaranteed prices to customers, forcing
    management to accept without review.
  • Solutions Better review communications.
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