Integral Logistics Management — Operations Management and Supply Chain Management Within and Across Companies

10.5.1 Comparison of Techniques and Choice of Suitable Forecasting Technique

Intended learning outcomes: Differentiate between various areas of applicability of forecasting techniques.



In Figure 10.5.1.1, the techniques discussed in the Section 10.2, Section 10.3, and Section 10.4 are compared according to a number of criteria.


Fig. 10.5.1.1    Areas of applicability of forecasting techniques.

When choosing a forecasting technique, it is crucial to find that technique (reasonable in use) that will provide the greatest accuracy of alignment to the demand structure.[note 1008] The following criteria also play a role:

  • Adaptability to demand performance
  • Possibility of forecast errors
  • Aids required
  • Expense for data collection and preparation for analysis
  • Ascertainability of parameters that describe the performance of the system to be forecast
  • The purpose of the forecast and the importance of one material position
  • Forecast time frame
  • Transparency for the user



Course section 10.5: Subsections and their intended learning outcomes

  • 10.5 Using Forecasts in Planning

    Intended learning outcomes: Produce an overview on the choice of suitable forecasting technique. Describe consumption distributions and their limits, continuous and discontinuous demand. Explain demand forecasting of variants of a product family. Present safety demand calculation for various planning periods. Disclose the translation of forecast into quasi-deterministic demand.

  • 10.5.1 Comparison of Techniques and Choice of Suitable Forecasting Technique

    Intended learning outcomes: Differentiate between various areas of applicability of forecasting techniques.

  • 10.5.2 Consumption Distributions and Their Limits, Continuous Demand and Discontinuous Demand

    Intended learning outcomes: Identify variables for a consumption distribution. Present expected value and variance of the consumption distribution. Explain distribution function, expected value, and variance of the consumption distribution under the assumption of a Poisson distribution for the frequency of events. Describe the demand filter to handle a discontinuous demand due to infrequent large issues. Disclose effects of length of statistical period on demand fluctuations.

  • 10.5.3 Demand Forecasting of Variants of a Product Family

    Intended learning outcomes: Describe the option percentage. Explain the formulas for forecasting demand for variants.