Forecasting can be an invaluable tool for creating an efficient, profitable business based on lean management principles. While predicting the success of future enterprises is an inexact science, it is possible to use forecasting tools to extrapolate the likely course of events based on previous data.

Tips for Project Forecasting

Preparations

The first step in the forecasting process is determining what data will be collected and how it will be utilized. It is essential to know, for example, whether the forecast is going to be used by a machine or if it needs to be converted into a readable format for examination by a specific person. It is also necessary to define the scope of the data so that the collection is useful. Having too narrow a subject will cause the data to become progressively more complex and difficult to parse, while too broad a collection will render it useless for predictive purposes.

 

Examining Data

Once you have determined what data you need and received it, it’s time to put it to practical use. When forecasting for an existing business, it is best to work off data collected about the previous years and predict from there. If there were any extenuating circumstances or special events taking place that are unlikely to reoccur in the period for which you are creating a forecast, be sure to adjust your calculations accordingly. If a business is new, rely on the data collection of the geographical area to determine how many people your business is likely to attract.

 

Utilizing the Forecast

The forecast can now be used in a predictive capacity to roughly estimate how much business you will have within the predictive period. This can help you determine how much you need to invest in manufacturing processes, whether you should hire new employees, and how to best spend your money in order to maximize your return on investment.

 

It is important to remember that as circumstances change, new forecasts will need to be created in order to make accurate assessments. If you find that your forecast is substantially inaccurate, begin again and adjust the process as needed.