Implementation of "Process Mining" Technology for a Logistics Company Using Machine Learning

The degree of digitalization and technological equipment of organizations, the presence in them of a digital approach to the analysis of the company's business processes through the use of innovative software analytical tools is currently a strong competitive advantage and an essential necessity for further business development. The work investigates the business processes of a small business logistics company specializing in small-sized transportation. The study of the degree of digitalization of the company's business processes was carried out, and methods and software products were proposed for digitizing the actions of company employees when performing their tasks. On the basis of the proposed software products and service of the Process Mining - Celonis business process analysis technology, analytical "maps" of the processes have been compiled. Further, based on the results obtained, an analysis of business processes was carried out and methods for their optimization were proposed. In addition, for continuous analysis, the proposed architecture of software products has been modernized. For constant monitoring of the processes, four metrics have been compiled and algorithms for their formation have been worked out, which use the company's statistical data to classify and predict the speed of employees, perform a specific stage of the business process, or generally meet the time expectations of the speed of the entire order.