Business forecasting is essential for making business plans, so that your management can make informed decisions regarding the company’s future, to ensure that you have sustainability. It gives you a better understanding of the market and current climate, so that you can adjust your products, services and sales accordingly to stay ahead or to keep up with your competitors.
So, what are the best ways and methods to forecast successfully and efficiently? We’ve taken a look at this to bring you some of the best and most commonly used practises.
They are generally split into two main categories; qualitative and quantitative, and they can be used separately as individual methods or can be combined in some instances.
Qualitative methods
Qualitative methods generally rely on expert decisions and assistance, as they rely heavily on management and risk assurance workers (read more on that here) to make informed decisions by evaluating the market, the industry leaders/competitors and your previous business income. These methods are best used when you don’t have a lot of data to go by, and instead will need to use expert judgement and opinion.
Main qualitative methods include market research and the Delphi Method.
Quantitative methods
On the other hand, quantitative methods are very different as they aim to take the ‘human’ aspect out of forecasting; instead of relying on opinions and individual judgement, they make use of data and statistics in order to determine and predict trends for the market. If you have access to a lot of data (especially if it goes back a significant amount of time) you are able to make more long term decisions and predictions.
Quantitative methods include the Indicator approach, Econometric modelling and time series methods.
So, how does business forecasting work?
Now we’ve looked at the main methods used for business forecasting, it’s a good idea to evaluate how they actually work, so that you can choose the best options for your business.
- A problem, question or significant piece of data is chosen as a starting point for the process. This could be something you want to learn about your customer’s spending habits, or a question regarding your sales for the next quarter, for example.
- This is when an ideal data set or theoretical variables are chosen; the forecaster begins to identify the relevant variables that will be considered, and they will make decisions regarding how to collect the necessary data.
- To simplify the process at this stage, the forecaster will make some educated assumptions, which will cut down the time and data required.
- This is when a model is chosen which best fits the data set, selected variables and predictions.
- Using the chosen model, the data is analysed which will lead to a forecast being made from the analysis.
- Finally comes the verification. The forecaster will compare the forecast set to what actually happened, which in turn will enable them to tweak the process and identify any problems.