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Sem 5 Prep
← OperationsMoving averages and smoothing

Formulas for this chapter

Simple moving average

MA = SUM(Di) / n

A stable series with no trend or seasonality. Larger n means more smoothing and less responsiveness.

n
Number of periods in the moving average
Di
Actual demand in period i, the n most recent periods

Weighted moving average

WMA = SUM(Wi x Di), with SUM(Wi) = 1.00

When recent periods deserve more weight than older ones. Check the weights sum to 1.00 and that the largest is on the most recent period.

Wi
Weight for period i, between 0 and 1
Di
Demand in period i

Exponential smoothing

F(t) = F(t-1) + alpha ( D(t-1) - F(t-1) ) = alpha x D(t-1) + (1 - alpha) x F(t-1)

When only the last forecast and last actual are available, and the level moves but does not trend. State the starting forecast you assume.

alpha
Smoothing constant between 0 and 1; the fraction of the last error fed back
F(t-1)
Previous period's forecast
D(t-1)
Previous period's actual demand

Alpha and moving-average length

alpha = 2 / (n + 1)

To justify a chosen alpha, or to convert a familiar moving-average length into a smoothing constant.

n
Equivalent number of periods in a moving average
alpha
Smoothing constant with roughly the same behaviour
Step 2 of 21
The real wordsTheory

Simple moving average

Simple moving averageA technique that averages a number of recent actual values, updated as new values become available.
MA = SUM(Di) / n where n = number of periods in the moving average Di = demand in period i

It takes the average demand over a defined number of past periods. The forecast will lag behind trends and behind seasonality or other cyclicality.

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