It is not unusual to hear leaders in a company talk about forecasts. Forecasting serves as a tool that supports business financial, operational, marketing sales and other related decisions. It allows business leaders to plan for future and analyze the effects of a particular situation. A forecasting model helps business managers to identify appropriate responses to the changes in demand, price-cutting by changes in economic conditions, competition, etc. in order to benefit more from forecasting, it is important that leaders understand finer details of different models and determine what a particular model can or cannot do in a certain situation.
Forecasting Models for Businesses
Naïve Forecasting Method
This forecasting method has a base for projecting for a future period upon the data recorded for previous periods. Naïve forecasting may be equal to the actuals of post periods or the average of actuals for a particular previous period. This forecasting model makes no adjustments to previous periods for seasonal variations or any cyclical trend for best estimating a forecast for some future period. Also, the user of a naive forecasting method is not concerned with casual factors that can result in the change within actuals. For this purpose, this method is used to develop forecasts which are used to tally with the results of a more sophisticated forecasting model.
Casual Forecasting Methods
Autoregressive moving average and regression analysis having exogenous inputs are rendered as causal forecasting methods which tend to predict a variable by using several underlying factors. This model assumes that a mathematical function making use of known variables can be used for forecasting the future value of that variable.
Qualitative and Quantitative Forecasting Methods
Qualitative forecasting model involves personal opinions of business leaders whereas; quantitative methods rely on previous numerical information for predicting the future. Informed opinions, The Delphi method and historical life-cycle analogy are some qualitative methods. Qualitative models are usually effective for making short-term predictions or where the scope of making a forecast is limited.it is useful for short-term success of products, services and companies, however, it has limitations as it relies on expert opinions than measurable data.
Quantitative models, on the other side, attempts to take out the human element outside the analysis. Predictions are based on measurable. Variables included in making forecasts include gross domestic product, sales, real estate prices and so on. These predictions are done for a longer time period and are measured in months or years. The indicator approach, econometric modeling, time series methods, multiplicative seasonal indexes, exponential smoothing, simple and weighted moving averages are some type of quantitative forecasting model.
Time Series Forecasting Method
This type of forecasting model like moving average, exponential smoothing and trend analysis, involves historical data for estimating future outcomes. Time series is a group of data which is recorded over a specified time period and which is used to make longer term forecasts. Making long term predictions are done for several reasons like allowing a company’s manufacturing, purchasing, finance and sales departments to make new plans regarding products and product lines.
Judgmental Forecasting Methods
The scenario building, Delphi method, composite forecasts and statistics survey are judgmental forecasting models and are based upon intuitive and subjective predictions. Through this method, forecasting is made on the basis of a collection of opinions that are given by business leaders, managers and panel of experts within an organization.
Forecasting allows businesses to plan ahead of their needs as they provide an insight of what trends will occur in near future. In this way, companies attempt to stay ahead and healthy through all markets. Forecasting is the way through which organizations plan their future actions and pave the way on which they can make their company, product and services a success. Selecting the right forecasting model is essential so accurate and effective predictions can be made. Accurate predictions also attract potential investors which lead towards the growth and success of the business.