In our daily business life, executives are always faced with situations at which a decision about the future should be taken now. There are lots of techniques that could be deployed to draw the decision about the future. One of these techniques is the Business Forecasting Process. It’s the process used to estimate or predict future patterns about an issue using raw business data. Some examples of business forecasting include sales forecast, product demand, inventory stock, supply-chain order level and much more. Accuracy in decision maker forecast is directly proportional to the accuracy of the future decision.
There are few tips when you plan to forecast:
· Expect the worse and then project the best possible scenario
· Always freshen your source data
· Keep the involved parties informed
· Know your business, environment and customer behaviors well
· Always remain attentive in order not to miss small events around you that might impact your forecast
There are many methods used to make the forecasting process ranging from simple to complex methods using models, however, we’d be mentioning only three of them due to their ease of application.
1. Pattern Analysis
There are methods that depend mainly upon the observation of arithmetic curves and their behavior over a period of time. The most commonly understanding method belonging to this category is trend analysis, which is the study of the shapes –patterns- made cumulatively by a set of data that are graphically represented. It’s commonly known that historic data tend to repeat itself over a period of time. Even the shape of these data tends to repeat over the same period of time. For example; a head-and-shoulders pattern of data representation of a stock would mean a reverse action in the opposite way of that stock, thus we could predict a down trend for this stock value. There are as many as patterns that we can see of data over time. This is not the real scope of it at the moment.
2. Analogy
This is a very simple and acceptable way to forecast an issue by comparing it to another existing issue that shares the same parameters and factors with each other. For example, launching a new product could be assisted with the observation of an existing product in the same product line.
3. Extremes or Scenarios
This method involves identifying the core issues, uncertainties and time of a case and then building positive and negative scenarios of the possible outcomes. This gives us two case scenarios. Upon these scenarios, one could place the possible outcome and consequently the possible forecast.
For more detailed information about the subject, please follow this link. But you got to bear in mind that Forecasting is NEVER PERFECT.
