The forecast is essential to most decisions taken by executives and CEOs nowadays. They can’t make decisions without taking into consideration what are the customers’ possible needs and wants. Of course, no one can predict the future, but you can certainly make good forecasting with proper analysis and data. However, what is forecasting analysis? And how does it help companies?

  • What is forecasting analysis?

Forecasting is a technique of predicting the future based on historical data results, which means data on previous events, sales, etc. It can use several statistical tools and techniques to achieve a trustworthy result. Therefore, forecasting can also be known as statistical analysis.

As you can imagine, several problems can affect the results, so the process of forecasting is quite complex. To make it more efficient, several forecasting techniques have been developed recently. Each one is proper for a certain situation, and the correct one must be used, or the results won’t be as efficient as they need to be. Let’s understand the forecasting methods and where you can use them.

  • What are the types of forecasting methods?

The two basic forecasting techniques, which are pillars for the others, are qualitative and quantitative methods. 

The qualitative techniques are quite subjective and based on experts’ and consumers’ judgments and opinions. They are usually used when past data aren’t available and can be applied to consider intermediate or long-range decisions in the company. Some qualitative techniques are historical life-cycle analogy, the Delphi method, and market research.

Quantitative techniques focus on analyzing historical data to predict or forecast future data. They are commonly used when past numerical data is available and when it is possible to assume that some patterns in past data are expected to continue into the future. Quantitative methods are usually used for short or mid-range decisions. There are many quantitative forecasting methods, such as simple exponential smoothing, last-period demand, simple and weighted N-Period moving averages, multiplicative seasonal indexes, and Poisson process model-based forecasting.

The use of multiple methods can lead to a different level of forecasting accuracy, so it is essential to understand the methods to see if they can be used together or not.

  • How can it help my company?

As stated earlier, predictions are essential to make important decisions for the company. You need to forecast what your clients may want in the future to understand which services or products you’ll stop producing, produce more, start selling in another region, etc.

Nowadays, demand planning and s&op software offer forecasting processes with high accuracy. One of the best available is the one offered by John Galt Solutions, a software company with various decades of experience. It combines many contemporary technologies, including the internet of things (IoT), artificial intelligence (A.I), machine learning, and more.