The purpose of the financial forecast is to evaluate current and future fiscal conditions to guide policy and programmatic decisions. A financial forecast is a fiscal management tool that presents estimated information based on past, current, and projected financial conditions. This will help identify future revenue and expenditure trends that may have an immediate or long-term influence on government policies, strategic goals, or community services. The forecast is an integral part of the annual budget process.
Some are based on subjective criteria and often amount to little more than wild guesses or wishful thinking. Others are based on measurable, historical quantitative data and are given more credence by outside parties, such as analysts and potential investors.
While no forecasting tool can predict the future with complete certainty, they remain essential in estimating an organization's future prospects. Using this technique, a group of field experts responds to a series of questionnaires. The experts are kept apart and unaware of each other. The results of the first questionnaire are compiled, and a second questionnaire based on the results of the first is presented to the experts, who are then asked to reevaluate their responses to the first questionnaire.
This questioning, compilation and re-questioning continues until the researchers have a narrow range of opinions. Scenario Writing In scenario writing, the forecaster generates different outcomes based on different starting criteria.
The decision-maker then decides on the most likely outcome from the numerous scenarios presented. Scenario writing typically yields best, worst and middle options. Subjective Approach Subjective forecasting allows forecasters to predict outcomes based on their subjective thoughts and feelings.
Subjective forecasting uses brainstorming sessions to generate ideas and to solve problems casually, free from criticism and peer pressure. These sessions are often used when time constraints prohibit objective forecasts. Subjective forecasts are subject to biases and should be viewed skeptically by decision-makers.
Time-Series Forecasting Time-series forecasting is a quantitative forecasting technique. It measures data gathered over time to identify trends. The data may be taken over any interval: Trend, cyclical, seasonal and irregular components make up the time series.
The trend component refers to the data's gradual shifting over time. It is often shown as an upward- or downward-sloping line to represent increasing or decreasing trends, respectively. Cyclical components lie above or below the trend line and repeat for a year or longer.
The business cycle illustrates a cyclical component. Seasonal components are similar to cyclicals in their repetitive nature, but they occur in one-year periods. The annual increase in gas prices during the summer driving season and the corresponding decrease during the winter months is an example of a seasonal event.
Irregular components happen randomly and cannot be predicted.Scenario planning, also called scenario thinking or scenario analysis, is a strategic planning method that some organizations use to make flexible long-term leslutinsduphoenix.com is in large part an adaptation and generalization of classic methods used by military intelligence..
The original method was that a group of analysts would generate simulation games for policy makers. Good forecasting is the reverse: It is a process of strong opinions, weakly held.
If you must forecast, then forecast often—and be the first one to prove yourself wrong. Good forecasting is the reverse: It is a process of strong opinions, weakly held.
If you must forecast, then forecast often—and be the first one to prove yourself wrong. The way to do this is to form a forecast as quickly as possible . Forecasting: Roles, Steps and Techniques | Management Function. Article shared by: On the basis of the definition, the following features of forecasting can be identified: 1.
Forecasting relates to future events. 2. Forecasting is needed for planning process because it devises the future course of action. Review of the Forecasting Process.
The common feature of these mathematical models is that historical data is the only criteria for producing a forecast.
multiple regression models look at the relationship between the variable being forecast and two or more other variables. Involving these people in the forecasting process, gives them the power to become co-creators in.
Cyclical patterns that repeat any two or three years or more.
Probabilistic models will be used frequently in the forecasting process. With an understanding of the basic features and.