Lhe algorithms rely on big data and artificial intelligence to predict and analyze the behavior of individuals. They have become essential, over the last decade, in the functioning of organizations: they can be used to know customers better, facilitate better decision-making, ensure smoother coordination or even improve organizational learning. They are also essential to the platform economy and Industry 4.0.
But algorithms do not only disrupt economic models or customer relations, they also modify management methods. Thus, in organizations, “algorithmic management” is increasingly practiced, a new form of management, which relies on algorithms to organize production and control methods. What’s new with algorithmic management?
According to the synthesis recently carried out by researchers from the Massachusetts Institute of Technology (MIT) and Stanford University (Cafifornia), the algorithms have, compared to traditional control systems, three characteristics which distinguish them.
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First of all, they make it possible to capture more aspects of human behavior: connected devices can now more accurately record bodily movements (even facial movements and biometric data) and the thoughts of employees (to through videos and audio recordings, but also the analysis of textual data).
This makes it possible to prescribe and frame the work in a new way, often in a much stricter way and in real time. For example, Uber analyzes acceleration and braking data to produce « nudges prompting drivers to take breaks. Some companies analyze the vocabulary used and the feelings expressed on the networks by employees; when others locate employees who frequently interact together or, conversely, those who isolate themselves. Others even use facial recognition to assess the morale of their employees.
Then, the algorithms are instantaneous and interactive: we can now calculate, save and communicate information in real time. This has important consequences on the methods of employee evaluation, which is done more and more instantaneously, in particular through the ratings given by consumers.
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