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• W307833554 abstract "Productivity is a buzzword in business. Everything is judged by it. Forecasting is no exception. forecasting function is more likely to become an important part of the organization if it can be shown to be productive. But measuring the productivity of a forecasting function is less straightforward than measuring the productivity of a widget manufacturing plant. Is a forecaster who generates 100 forecasts a month more productive than one who generates 50 forecasts a month? Does reducing the MAPE, achieving an R-squared of .99999, or producing a model with residuals that aren't correlated with anything in the world mean we have achieved fantastic productivity? answer to these questions is no. Business executives tend to judge functions in terms of dollars. key to measuring forecast productivity is to show how the use of forecasts has either decreased costs or increased revenue. Forecasts are used as inputs to decisions. Decisions have economic consequences for the organization. To relate a forecast to productivity, one must focus on the relationship between the forecast and the change to the corporate bottom line that accrues from using the forecast. forecaster who can say, My forecasts saved the company $300,000 this his/her forecasts are more likely to be accepted and supported than the forecaster who says, I reduced the MAPE from 3.5% to 2.%. Forecast productivity measurements are often imprecise, but reasonable approximations can usually be made. ESTIMATING PRODUCTIVITY This paper will discuss the measurement of forecast productivity in three applications. To facilitate the discussion, we will define the terms forecast and forecast. A forecast can be defined as one that is generated through a formal forecasting process by a trained forecaster using some sort of statistical model. model may range on very simple to extraordinarily complex. A forecast can be defined as one prepared without using any formalized forecasting process or without the help of a trained forecaster. An example of a naive forecast might be The forecast for this month is the same as last month's actual. Forecast productivity can be measured in terms of dollars saved (or lost) by implementing a decision based on a sophisticated forecast instead of a naive one. A sophisticated forecast includes (1) a point forecast and (2) a range forecast--a confidence interval that quantifies the uncertainty around a forecast. In some cases a forecaster may be able to establish relationships between the organization's sales and endogenous factors (such as product price and advertising level) or exogenous factors (such as state of the economy). Each of these aspects of a forecast can be used in the measurement of forecast productivity. We will give an example of each. PRODUCTIVITY FROM THE POINT FORECAST Decision: Should the company spend an additional $100,000 to buy the raw materials needed to produce product XYZ? Suppose the sophisticated forecast states that we will sell 1500 units of product XYZ next month while the naive forecast says 2000 units will be sold. If we use the naive forecast, we may conclude that we must order now. sophisticated forecast tells us we can delay the action for a month. If delaying action turns out to be the correct decision, the company has avoided the expenditure of $100,000 for one month. If the cost of carrying the inventory is 15% per year, then the productivity of the sophisticated forecast is $1,250 ($100,000) x (.15/12)!. If delaying action turns out to be an incorrect decision, the sophisticated forecast has cost us money. cost would be either the lost profit (estimated lost unit sales times profit per-unit) or the cost of any extraordinary actions taken to avert lost sales. (An extraordinary action might be something like paring a premium for a rush delivery of raw materials.) productivity of a forecast in function per year (with respect to the inventory control application) is then found by analyzing all such decisions over the year. …" @default.
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• W307833554 date "1992-07-01" @default.
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• W307833554 title "Measuring Forecast Productivity" @default.
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