The nature of industrial markets, like the power tool one, consisting as they do of a small number of large customers or potential customers, makes industrial market surveys much simpler and less expensive than similar surveys of potential markets for nationally distributed consumer staples. Because judgment plays such an important role in forecasting, there is an obvious advantage in checking one's own estimate against the estimates of other forecasters (Makridakis, 1998).
Another industry is a home repairs and improvement industry. In this sphere, it is difficult to forecast customer demand in sufficient detail and with sufficient accuracy for the purposes of planning more than a few months in advance. A special attention should be given to new building materials and repair-improvement processes which create a demand for new products and innovative solutions (Schwolsky, 2004).
Raw materials and suppliers relations also affect the power tool industry and influence product cost and price level. Changes in steel industry and chemical industry affect price level and can influence production facilities of the power tool industry. ...
The main factors in statistics and forecasting are internal and external factors. They include field of research (narrow or broad), the seasonal fluctuations of demand and sales, direct and indirect competition, population changes and consumer earning. Internal changes are product changes (innovations), production capability of competitors, raw materials price changes, credit policy changes and labor relations (Brockwell, Davis 2003).
Statistics for the power tool industry show that rank shifts based on net income involved about one-half of the possible uncertainty, and that shifts based on operating revenue are somewhat more uncertain than those based on assets. Where industry statistics are available, many corporations keep records of the pertinent industry statistics and of their own sales in each such industry. The industry history can be projected to obtain a forecast of total industry sales. One advantage inherent in the use of industry statistics is that many different forecasters are attempting to forecast the same aggregate figure. Other companies interested in the same industry are making forecasts of the same aggregate; these forecasts will be compared and a consensus will usually be reached. The major use of industry statistics, however, is to compare currently released industry sales with the corporation's own sales for the same period in order to determine (Makridakis, 1998).
Total sales of an industry can be forecast by using a known correlation or relationship of such sales with National Disposable Income and the forecast of Disposable Income. On the industry side the national statistics published by the Department of Commerce provide a wealth of information for forecasting in the field of consumer