Digital system for controlling regional costs in a large company

The problem of digital control of regional costs in a large company under conditions of uncertainty, using artificial procedures and taking into account the human intelligence factor, are analyzed. The undesirable activity of managers of the middle (regional) and lower (production) level of the company, associated with the presence of their own goals, was revealed. Such undesirable activity can lead to overestimation of regional costs. In order to minimize these costs, a digital control model is proposed that uses digital learning procedures at the regional and production levels. As a result of research, a mechanism has been developed to reduce regional costs in each period of time. This mechanism includes, firstly, a digital self-learning procedure for a top manager of a company, as well as a procedure for stimulating a middle manager by him to reduce regional costs. Secondly, this mechanism includes a procedure for digitally supervised training of a middle manager, as well as a procedure for stimulating a lower-level manager for reducing production costs. The statement and solution of the problem is illustrated by the example of the application in the maintenance of rolling stock.