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Title: Demand and forecasting
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In the present economic environment, a company must better its ability to meet consumer demand and at the same time to decrease prices to prosper. A clear picture of the present market is necessary, but a view of the future is also essential. Sources of data, which may turn to be useful, contain expert opinions, published forecasts, demographics, forthcoming legislation, patents and economic information.
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In a demand-driven environment where the stress is made on meeting consumer expectations, careful demand forecasting is only reached when a collaborative process integrates different forecasting systems. Forecasting is a necessary addition to planning in business or government. Forecasts are very often conducted subjectively and at great price by group discussion. Statistical forecasting is the selection and use of the exact forecast methodology that has always been a significant planning and control issue for most firms and companies.
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When demand is justly stable, for instance, unchanging at a known fixed rate, making an exact forecast is less complex. In the case if the company has had an experience in up-and-down sales, then the complexity of the forecasting task is combined. There are two major approaches to forecasting. The first one: the estimate of future value is based on the analysis of factors, which are supposed to effect future values, for instance, the explanatory method. The second one: the prediction rests on an inferred study of past general information behavior over time, for instance, the extrapolation method.
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The jury of executive opinion is the technique that is useful in situations where past information do not exist, causal relationships have not been defined, or some major modification has taken place in the forecasting context which is not accounted for by other techniques (Kahn, Kenneth (2002), p.133-143). Evidence as to the validity of using these methods by themselves is mixed, although using them correctly can provide very good forecasts, especially in uncertain environments. The objective of these techniques is to provide logical, unbiased, and systematic quantitative estimates.
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If sales and marketing is separated, companies who have short-term instability will generally find that sales can produce the most accurate forecast with an input from marketing for the longer term. Where there are long term issues, marketing will generally be able to produce the most accurate forecast but will need an input from sales for the short term. The breakthrough comes with the realization that the fundamental reason for forecasting is to improve customer service by lining up all the resources to meet the best estimate of what our customers will want, when they want it.
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