Forecasting is the process of making predictions of the future based on past and present data. It involves a detailed analysis of past and present trends or events to predict future events.
In forecasting, we gather data on past trends and present conditions and then extrapolate the future values according to expectations, fears, and possible opportunities. While backcasting is almost the opposite of forecasting. It is starting with the point where we want to be in the future and then trying to adjust everything in the present according to the target we want to achieve.
For us to understand what will happen in the future, we need to understand what has happened in the past.
Forecasting financial performance is integral to a variety of business decisions ranging from investing to managing a company effectively.
Why do we forecast
There are several reasons why we forecast. Below are some of them:
- Forecasting gives the ability to make informed business decisions and develop data-driven strategies.
- It allows businesses set reasonable and measurable goals based on current and historical data.
- Gives visibility into potential trends and changes and helps businesses to know where to allocate their budget and time
- Having insight into not only current data but projections of what could happen in the future helps businesses to adjust business strategy and alter current operations in order to change their outcome.
- Helps to track sales and be able to find where sales are lost and possible reasons for the loss
Objectives of forecasting
The quality of our forecast is only as good as the quality of the information on which it is based. Our objective is not to be overly optimistic or overly conservative. The objective of forecasting is accuracy. The shorter the accuracy period, the more accurate the forecast will be while the longer the time of your forecast, the less accurate it will be.
We have several types of forecasting methods. However, the three tops of demand forecasting are Survey methods, Opinion poll methods, and Statistical methods. The Survey and Opinion poll methods are good for short-term forecasting. The survey method which is also a consumer survey involves direct interviews with potential customers while Opinion poll methods include Expert Opinion, Delphi Method, Surveys of Managerial Plans, and Market Experiments.
The Statistical Methods are appropriate for long-term demand forecasting. They include Trend Projection Methods, Barometric Methods, and Econometric Methods.
Basic Forecasting techniques may be classified as Qualitative and Quantitative. Some of the qualitative techniques are the Market Research Techniques, Past Performance Technique, Internal Forecast, Deductive Method, Direct vs. Indirect Methods, Jury of Executive Opinion, and so on. While some of the quantitative techniques are Business Barometers Method, Executive Opinion, Trend Analysis Method, Extrapolation Method, Regression Analysis Method, Economic Input-Output Model Method, and so on.
In addition to the qualitative and quantitative techniques of forecasting, we also have groups like the Time Series techniques of forecasting, Causal Modelling, and Technological Forecasting. Times series techniques are sub-divided into Trend Projection, Moving Average, and Exponential Smoothing. The Casual Modelling techniques of forecasting include Regression Analysis, Econometric Models, and Economic Indicators while Technological forecasting includes Cross-Impact Analysis, Morphological Analysis, and the Substitution Effect.