Forecasting With Indices Essay

1227 words - 5 pages

Dr. Julianne Manchester
August 22, 2010

Forecasting With Indices
According to Business: The Ultimate Resource (2009), “forecasting is the prediction of outcomes, trends, or expected future behavior of a business, industry sector, or the economy through the use of statistics. Forecasting is an operational research technique used as a basis for management planning and decision making. Common types of forecasting include trend analysis, regression analysis, Delphi technique, time series analysis, correlation, exponential smoothing, and input-output analysis.” Simply stated, forecasting is a way of predicting future results or expectations based on assumptions or historical ...view middle of the document...

Time series forecasting models try to predict the future based on past data. For example, sales figures collected for the past six weeks can be used to forecast sales for the seventh week (Chase, Jacobs, & Aquilano, 2005, p. 518).
Seasonal variation refers to the patterns of change in a time series within a year (Lind et al., 2008). These patterns tend to repeat themselves each year (Lind et al., 2008, p. 605). A seasonal factor is the amount of correction needed in a time series to adjust for the season of the year (Chase et al., 2005, p. 532). Table 1 indicates a significant increase in demand during April, May, June, July, and August. By contrast, it indicates a decrease in demand during September through March. Therefore, late spring through summer appears to be the peak period of unit demand for products sold by Company XYZ. The data from Table 1 is used to create an inventory demand index which provides the basis for the summer seasonal demand forecast (See Index 1). Meanwhile, Table 2 illustrates the forecast for year five. The forecast for year five will assist Company XYZ in determining material and production needs and help to manage costs appropriately.
Seasonal forecasting prepares a company for market demands. Forecasting methods assist companies in planning for industry demands throughout the year. Although a perfect forecast is unlikely, planning is an important aspect of meeting industry supply and demand.

Index 1 –Seasonal Demand – Summer
Summer Demand Index
Month Base Year Year 2 Year 3 Year 4 Index Y2 Index Y3 Index Y4 Index Y5
1 18,000 45,100 59,800 35,500 2.51 3.32 1.97 2.60
2 19,800 46,530 30,740 51,250 2.35 1.55 2.59 2.16
3 15,700 22,100 47,800 34,400 1.41 3.04 2.19 2.21
4 53,600 41,350 73,890 68,000 0.77 1.38 1.27 1.14
5 83,200 46,000 60,200 68,100 0.55 0.72 0.82 0.70
6 72,900 41,800 55,200 61,100 0.57 0.76 0.84 0.72
7 55,200 39,800 32,180 62,300 0.72 0.58 1.13 0.81
8 57,350 64,100 38,600 66,500 1.12 0.67 1.16 0.98
9 15,400 47,600 25,020 31,400 3.09 1.62 2.04 2.25
10 27,700 43,050 51,300 36,500 1.55 1.85 1.32 1.57
11 21,400 39,300 31,790 16,800 1.84 1.49 0.79 1.37
12 17,100 10,300 31,100 18,900 0.60 1.82 1.11 1.18...

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