How can I use machine learning to forecast sales?

Machine learning can be used to predict future sales in a defined time interval based on analysis of past data. This process takes account of all of the properties of a product: not only its price and date of sale, but also its official specification (such as the technical parameters of household electrical goods) and hidden features – contained, for instance, in published material about the product, in the images accompanying it, or in related audio and video files. The machine learning system identifies trends in sales and uses them to predict volumes of sales of individual products in a defined time frame.

Growth in the computing power used to process information, in combination with the development of machine learning methods, has made possible the instant analysis of vast quantities of data. Not just obvious information like the type of product, price, quantity, date, etc., but also data that appear unrelated to the analysed phenomena. Machine analysis is based on learning algorithms that perform huge numbers of calculations in an astoundingly short time. We can use them to discover entirely new relationships, on the basis of which we can make objective and accurate predictions.

Does this mean that human convictions and intuitions are becoming worthless? No, but we should be robustly supported by machine learning methods. We should make everyday use of the indications of a sales forecasting system, while retaining the right to make independent decisions. In doing this we should record both the suggestions of the “machine” and the “human” decision, which will enable us continuously to improve the decision-making process.

POLENG develops solutions that allow cooperation between human and machine. This practice enables constant improvement of the operation of the machine-based system, leading to an increase in the accuracy of the projections it generates. It is always possible to compare earlier human decisions with those suggested by the machine, to determine with hindsight who displayed the best “intuition”.

We strongly encourage you to take steps in this direction. Traditional ways of forecasting future events are gradually becoming anachronistic. A business that effectively implements new methods will obtain a competitive advantage, and this advantage will increase together with the continuous optimisation of the results achieved by the machine learning system. Let’s talk about it – because it’s worth paying attention to the competitiveness of your business, which determines your profits. Get in touch with us!