![]() Determine the quantitative and/or qualitative forecasting methods that will be used. Are there important relationships between variables that could aid in forecasting? Does the data contain any extreme values that need to be explained? It could be that these represent highly anomalous events that don't add to the predictive power of the data set. Are population changes affecting service demands and/or revenues? Does the revenue (or expenditure) tend to vary with the level of economic activity in the community or are they independent of cycles? How do broader market forces impact key expenditures, such as pension contributions affected by investment returns? ![]() In particular, the forecaster should look for evidence related to: The forecaster is looking for consistent patterns or trends. This improves the quality of the forecast both by giving the forecaster better insight into when and what quantitative techniques might be appropriate and also is useful for supplementing forecasting methods. The analysis should include an examination of historical data and relevant economic conditions. Such plans might include comprehensive development and/or capital improvement programs. Also, become familiar with other longer-term planning efforts of the organization or other organizations that impact financial decisions and the fiscal environment. Assumptions should be documented for future reference, so the financial forecasting process has some basis to start from at the beginning of each cycle. Both are important for forecasting because they allow the forecaster to more intelligently build quantitative models and to make a forecast using his or her own judgment. This would also include events that could cause a disruption in the operating environment and in prevailing trends. This step is designed to increase the forecaster's expert knowledge about the forces impacting revenues and expenditures. For instance, department heads may have an insight into activities within their own section. To support the forecasting process, use statistical data as well as the accumulated judgment and expertise of individuals inside and perhaps also outside the organization. ![]()
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