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
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.
10.5.2b Managing Discontinuous Demand, or Lumpy Demand
Intended learning outcomes: 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.
10.5.4 Safety Demand Calculation for Various Planning Periods
Intended learning outcomes: Identify variables for safety demand calculations. Explain expected value and standard deviation with continuous demand. Describe expected value and standard deviation over n statistical periods.
10.5.5 Translation of Forecast into Quasi-Deterministic Demand and Administration of the Production or Purchase Schedule
Intended learning outcomes: Identify safety demand. Explain independent demand as total demand including safety demand, taken as a function of the planning period to be covered.

Course 5: Sections and their intended learning outcomes

Course 10 – Demand Planning and Demand Forecasting
Intended learning outcomes: Produce an overview of forecasting techniques. Explain history-oriented techniques for constant demand in detail. Identify history-oriented techniques with trend-shaped behavior. Describe three future-oriented techniques. Disclose how to use forecasts in planning.
10.1 Overview of Demand Planning and Forecasting Techniques
Intended learning outcomes: Produce an overview on the problem of demand planning. Present the subdivision of forecasting techniques. Disclose principles of forecasting techniques with extrapolation of time series and the definition of variables.
10.2 Historically Oriented Techniques for Constant Demand
Intended learning outcomes: Describe the moving average forecast. Explain the first-order exponential smoothing forecast. Differentiate between the moving average forecast and the first-order exponential smoothing forecast.

10.3 Historically Oriented Techniques with Trend-Shaped Behavior
Intended learning outcomes: Explain the regression analysis forecast and the second-order exponential smoothing forecast. Describe the Trigg and Leach adaptive smoothing technique. Produce an overview on seasonality.
10.4 Future-Oriented Techniques
Intended learning outcomes: Explain the trend extrapolation forecast and the Delphi method. Describe scenario forecasts.
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.

10.6 Summary
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10.7 Keywords
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10.8 Scenarios and Exercises
Intended learning outcomes: Choose an appropriate forecasting technique. Calculate an example for the moving average forecasting technique and for the first-order exponential smoothing technique. Differentiate between the moving average forecast and the first-order exponential smoothing forecast.