The mean of at least two recent periods of demand data is the basis for the nextperiod’s demand forecast is the description of which quantitative…

The Simple Moving Average (SMA) method calculates a forecast by taking the unweighted arithmetic mean of demand from a specified number of the most recent time periods. The question's description of using the "mean of at least two recent periods of demand data" is the precise definition of the SMA technique. This method smooths out random fluctuations by averaging recent historical data, with each period in the average having equal importance.

A. Naive forecast: This method assumes the next period's demand will be identical to the single most recent period's actual demand, not an average of multiple periods.

C. Weighted moving average: This method applies different weights to each of the recent periods, typically giving more importance to the most recent data, rather than calculating a simple mean.

D. Exponential smoothing forecast: This is a weighted-averaging method that uses a smoothing constant (alpha) to weight the most recent actual demand and the most recent forecast.

1. Heizer

J.

Render

B.

& Munson

C. (2020). Operations Management: Sustainability and Supply Chain Management (13th ed.). Pearson. In Chapter 4

"Forecasting

" the Simple Moving Average is defined as a method that "uses an average of the n most recent periods of data to forecast the next period" (p. 119).

2. Stevenson

W. J. (2021). Operations Management (14th ed.). McGraw-Hill Education. Chapter 3

"Forecasting

" defines a moving average as a "technique that averages a number of the most recent actual values in generating a forecast" (p. 81). It explicitly contrasts this with the naive forecast

which uses only the previous value.

3. MIT OpenCourseWare. (2013). 15.762

Supply Chain Planning

Lecture 4: Forecasting. Massachusetts Institute of Technology. The lecture notes define the moving average forecast as Dt

t+τ = (dt + dt-1 + ... + dt-n+1) / n

which is the mathematical representation of the mean of the last 'n' periods of demand. (Slide 11). [Direct URL: https://ocw.mit.edu/courses/15-762-supply-chain-planning-spring-2013/resources/mit15762s13lec04/]