Forecasting is one of the skills you need to learn in almost any business position as these reports can help you design processes for supply chain management, marketing campaigns and even hiring practices. Knowing which data sets to analyze for your forecasting is a good place to start, but you also need to know how to apply the different methods to produce the best result.
Invest in Machine Learning
One of the newest technologies to be used in forecasting is machine learning software. This tool is able to analyze large data sets in various ways without explicit instructions from you and then learn from these forecasts to build better ones as time goes on. Some companies offering machine learning solutions will help you set your system up, provide data sets to teach the computers how to make the best analysis of the information, which is a great investment idea.
Understand Traditional Methods
One of the reasons why machine learning solutions are so quick to run forecasts is because they are able to shift through the traditional methods much faster than a human can to find the model to best fit the data and particulars of your brand. There are many different methods for forecasting including the straight-line, moving average and simple or multiple linear regression models.
In both the straight-line and moving average methods, historical data is used to forecast the future with the first model finding a constant growth rate in the data to predict future growth, and the second one using the average revenue from several months and projecting that average into the future. Linear regression models use a sample of observations relevant to the calculation to analyze variables, the more variables you have, the more regressions you need to perform.
Know How To Combine Models
The more you understand the various methods used in forecasting, the better you can combine them with machine learning solutions and create the best reports possible. This means using the machine learning to produce each type of model and then presenting the average of these as an ensemble. Using hybrid reports can give you the best historical forecast which also examines the relationships between variables such as seasonality of products and marketing promotions.
Building the right business forecast depends on what type of thing you are trying to predict, such as sales, costs and hiring. There are many different methods that you can use either separately or as an ensemble and machine learning solutions can help you get there faster.