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Tutorial Question: Moving Average: Exercise

1. Weekly sales of ten-grain bread at the local organic food market are in the table below. Based on this data, forecast week 9 using a five-week moving average.

Week Sales

1 415

2 389

3 420

4 382

5 410

6 432

7 405

8 421

2. Given the following data, calculate the three-year moving averages for years 4 through 10.

Year	Demand
1	74
2	90
3	59
4	91
5	140
6	98
7	110
8	123
9	99

Exponential Smoothing: Exercise

1. A management analyst is using exponential smoothing to predict merchandise returns at an upscale branch of a department store chain. Given an actual number of returns of 154 items in the most recent period completed, a forecast of 172 items for that period, and a smoothing constant of 0.3, what is the forecast for the next period? How would the forecast be changed if the smoothing constant were 0.6? Explain the difference in terms of alpha and responsiveness.

2. Jim's department at a local department store has tracked the sales of a product over the last ten weeks. Forecast demand using exponential smoothing with an alpha of 0.4, and an initial forecast of 28.0 for period 1.

Period	Demand
1	24
2	23
3	26
4	36
5	26
6	30
7	32
8	26
9	25
10	28

MAD: Exercise

The department manager using a combination of methods has forecast sales of toasters at a local department store. Calculate the MAD for the manager's forecast. Compare the manager's forecast against a naive forecast. Which is better?

Month	Unit Sales	Manager's Forecast
January	52
February	61
March	73
April	79
May	66
June	51
July	47	50
August	44	55
September	30	52
October	55	42
November	74	60
December	125	75

Exercise on MAD, Nave, exponential and moving average

Linda, a demand planner for Cheeznaz Snack Food need to provide top management with a forecast of next year demand. She knows how important an accurate demand forecast is to the supply chain. On the downstream side of the chain, the local stores expect that their shelves are stocked with fresh puffed cheese balls, while on the upstream side Cheenazs suppliers need the forecast to plan their overall production levels of raw ingredient and packaging materials. Within the Cheeznaz manufacturing, forecast data are needed to plan production. Linda looks at the sales figure for the past 9 years shown in the following table and is trying to decide on several forecasting methods, which include nave method, exponential smoothing (=0.8 forecast time 1 =150) and 4-year moving average. Using data given below, forecast for year 2008 to 2016 using the three methods, and decide which method would be suitable.

Year	Actual demand
2007	110
2008	130
2009	150
2010	170
2011	160
2012	180
2013	140
2014	130
2015	140