IS Impacts on Business Forecasting

Technology management is assuming greater importance in contemporary business organizations (Cyert & Kumar, 1994, p. 333). Among other organizational benefits of the application of technological innovations in information science (IS) is an enhanced capability to perform business forecasts. This research examines the impacts of advances in IS on business forecasting.

A forecast is an estimate of the future value, or future values, of a variable (Webster, 1994, p. 6). To be meaningful, forecasts must project values of a variable in measurable units of the variable. A number of procedures exist by which forecasts may be developed. The best forecasts are those developed through the application of statistical procedures. Among the major statistical forecasting procedures are the following:

2. Cyclic demand projections, which consider random variations, and which require the use of multiple regression equations.

3. Curvilinear regression projections, which consider multiple relationships among many variables.

The simplest of the quantitative techniques which may be used in forecasting is the fitting of a trend line. The major problem with this methodology is that it relies almost entirely on past performance. The fitting of a curve through regression analysis is methodologically similar to trend analysis. The curve fitting regression eq

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A is a $750 million Houston-based company that operates a chain of nursing homes across 10 states in the South and Midwest. The company also operates acute care facilities and provides rehabilitation therapy services. The company's pharmaceutical supplies division sells nationally. LCA, thus, is heavily dependent on effective and efficient business forecasting. LCA's forecasting efforts center on trying to quantify trends that affect nursing homes (The, 1995, p. 67). As an example, baby-boomers will eventually swell the company's customer base. Thus, LCA needs to know what new facilities will be needed and when these facilities will be needed and where such facilities will be needed. One way to make the forecasting process more accurate is by distributing the process. LCA wanted all layers of management in the business forecasting loop·down to and including the people running the company's 250 nursing facilities. Meeting this objective meant that the company's existing forecasting technology would either have to be revamped or replaced. LCA's existing forecasting technology was coded in COBOL, supported 50 users, ran on an AS/400 D70 off a flat file database, and had a user interface that was characterized by a primitive
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Some common words found in the essay are:
Outcomes Advances, Impacts Process, AS/400 D70, Data Warehouse, South Midwest, Conclusion Unfortunately, Peters Armstrong, IRI Express, Centers America, Cyert Kumar, business forecasting, contingency approach, approach management, strategic planning, data warehouse, regression analysis, contingency approach management, exponential smoothing, business organizations, moving average, multiple regression, process business forecasting, exponential smoothing approach, multiple regression analysis, data exponential smoothing,
Approximate Word count = 2447
Approximate Pages = 10 (250 words per page)

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