*Intended learning outcomes: Propose a forecasting technique for different products to apply to forecast future demand.*

Figure 10.8.1.1 shows historical demand curves for four different products. What forecasting technique for each product do you propose to apply to forecast future demand?

**Fig. 10.8.1.1** Historical demand curves for four products.

Solution:

- Product 1: demand with linear trend —> linear regression
- Product2: constant demand without trend —> moving average forecasting or first-order exponential smoothing
- Product 3: seasonal fluctuations with trend —> linear regression or second-order exponential smoothing with seasonality
- Product 4: constant demand with seasonal fluctuation —> moving average forecasting, or first-order exponential smoothing, with seasonality

## Course section 10.8: Subsections and their intended learning outcomes

##### 10.8.1 Exercise: Choice of Appropriate Forecasting Techniques

Intended learning outcomes: Propose a forecasting technique for different products to apply to forecast future demand.

##### 10.8.2 Exercise: Moving Average Forecasting Technique

Intended learning outcomes: Calculate forecasts with moving average forecasting technique.

##### 10.8.3 Exercise: First-Order Exponential Smoothing

Intended learning outcomes: Calculate forecasts using first-order exponential smoothing technique.

##### 10.8.4 Scenario: Moving Average Forecast versus First-Order Exponential Smoothing Forecast

Intended learning outcomes: Differentiate between moving average forecast and first-order exponential smoothing using different numbers of observed values or smoothing constants α.

##### 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.