Decision Making Based on Machine Learning

Machine Learning (ML) helps managers to get actionable insights from their diverse data and the benefits include e.g automated processes, enhanced quality control and predictive maintenance. ML is therefore the driving force behind AI (Artificial Intelligence) and its impactful applications throughout many industries and scientific research.

This whitepaper aims to explain the general concept of ML-based decisions and what it takes to make ML work for the benefit of businesses. It also introduces the approach of “Democratizing ML” which offers ML-asa-Service for almost any organization in an affordable and secure manner. The author, Dr. Reza Bakhtiari, a leading data scientist at A1 Digital, sheds light to decision making processes and the productive force of algorithms in different industries.

Decision making, either in personal life or in business, is a complicated task; therefore, a timely, right decision leads to the rise of people and organizations. Let’s look at this process in a more abstract way:

For most situations like “Should I Stay or Should I Go”, there are different pieces of information which act collectively. The non-trivial task is to find and focus on the most relevant aspects which then would lead to an optimal decision. That is why some people postpone their decisions to seek for more information or ask others for their opinions. There are several problems that can prevent transparent decision-making, e.g. not enough information which indeed leads to a biased decision. In contrast, too much information such as many factors influencing the outcome, causes large variance between conflicting information that makes it impossible to construct a reliable and applicable story which would fit to each of those pieces.


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