Demand Forecasting Concepts

  • (Definition) Forecasting is the business function that attempts to predict sales and use of products so they can be purchased or manufactured in appropriate quantities in advance.
  • (Definition) Demand Forecasting is forecasting the demand for a particular good, component, or service.
  • Forecasts are subject to uncertainty, and this uncertainty is one potential contributor to the bullwhip effect.

Principles of Forecasting

  • Forecasts are (almost) always wrong
    • A forecast is at the best an estimate of what may happen in the future – if there are no surprises.
    • Circumstances and minds can change. For this reason, forecasts require regular review.
    • Forecasting techniques should be subject to alteration if forecast errors grow too large.
  • Forecasts should include an estimate of error
    • Demand forecasts should include an estimate of how large the forecast error is likely to be.
    • Statistical analysis of the variability of demand around the average demand provides the basis for this error estimate.
    • Error estimates should also be given in terms of the monetary value of the error so that the errors with the most dollars at risk can be addressed first.
  • Forecasts are more accurate for groups than for single items
    • Accuracy generally increases with the size of a product group, assuming that forecasts for each item in the group are as likely to be too high as too low. The low forecasts tend to balance out the high forecasts, at least in sizable groups.
    • (Definition) Mix Forecast is a forecast of the proportion of products that will be sold within a given product family, or the proportion of options offered within a product line, even though the appropriate level of units is forecasted for a given product line, an inaccurate mix forecast can create material shortages and inventory problems.
    • The general principle at work in these cases is risk pooling – taking individual risks and combining them into a pool. The overall risk for the pool tends to be less than the average of all the risks that flow into the pool.
  • Forecasts of near-term demand are more accurate than long-term forecasts
    • The further you extend your forecast into the future, the more likely that chance and change will derail your estimates.
    • Hence, the need for periodic review and update of demand forecasts in comparison to actual results.
    • Long-term forecasts are generally reviewed on an annual or quarterly basis.
    • Medium-term forecasts are generally reviewed on monthly basis.
    • Short-term forecasts are generally reviewed on a weekly basis.
    • In addition to regular reviews, taking steps to shorten the required lead time for items can shorten the forecasting period and thus improve the accuracy of the forecasts.

Components of Demand

The core components of demand include the following:

  • Trend
    • Demand can stay the same, or it can rise or fall.
    • (Definition) A Trend is general upward or downward movement of a variable over time (for example: demand, process attributes).
  • Seasonality
    • Demand may fluctuate depending on time of the year, for example holidays, weather, or other seasonal events.
    • (Definition) Seasonality, also known as seasonal variation, is a repetitive pattern of demand from year to year (or other repeating time interval) with some periods considerably higher than others.
  • Random Variation
    • Many factors affect demand during specific time periods and occur on a random basis.
    • The size of this variation can usually be measured.
    • (Definition) Random Variation is a fluctuation in data that is caused by uncertain or random occurrences. These random changes are generally very short-term, mere bumps and dips on the road up or down a trend line.
  • Cycle
    • Long-term upward and downward cyclical moves generally correlate with the business cycle, but the duration of these economic trends is difficult to predict and is therefore generally left to economists.
    • Publications such as the Purchasing Managers Index (PMI) can be used to predict economic trends.

The difference between seasonality and cycles can be clarified as follows:

  • Seasonality is a demand pattern that, based on history, will repeat itself on calendar basis such as month, week, day of the week, hour of the day, etc., and therefore can be predicted.
  • Cycles are demand patterns that repeat but follow a wavelike pattern that can span multiple years and therefore cannot be predicted easily.

Independent and Dependent Demand

  • Demand can be classified into two types:
    • Dependent
    • Independent
  • Demand for finished product is independent; demand for a component used in making the product is dependent.
  • (Definition) Dependent Demand that is directly related to or derived from the bill of material structure for other items or end products. Such demands are therefore calculated and need not and should not be forecast.
  • (Definition) Independent Demand is the demand for an item that is unrelated to the demand for other items. Demand for finished goods, parts required for destructive testing, and service parts requirements are examples of independent demand.
  • Forecasting should be done only for the independent demand; dependent demand can then be calculated from the forecast using material requirements planning.
  • A given item, however, may be subject to both types of demand. For example, the demand for automobile tires is dependent in relation to new cars but independent when considered as replacement item to be stocked in a repair shop.

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