# 10.5 Using Forecasts in Planning

## 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.

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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.

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