IMPORT SUBSTITUTION OF SOFTWARE FOR INTELLIGENT PROCESS ANALYSIS IN RUSSIA
The article presents the findings of a study investigating the extent to which software for intelligent process analysis can be considered an import substitute. This section provides a concise overview of the evolution of the concept of identifying patterns of activity based on data analytics. This category of software has been the subject of investigation by Russian technology companies, who have developed solutions for organisations seeking to identify their current processes, analyse and evaluate their effectiveness, risks, errors and failures. The objective is to evaluate the capabilities of process mining systems and to assess the potential for their dissemination and integration within Russian organisations. The article presents a classification of tasks that can be solved by a Process Mining System. The infrastructural prerequisites for the successful implementation of a system of this nature are delineated. Primarily, these include the availability of digital services that accompany the organisation's processes and collect raw data about them for subsequent consolidation, preprocessing and transfer to the Process Mining System for analytical research. A review of the functionality of domestic solutions is conducted, and an evaluation of the competitiveness of Process Mining systems developed by Russian companies is provided. The findings of the analysis may be employed to encourage organisations to adopt domestic intelligent process analysis systems, as awareness of the efficacy and suitability of such systems in addressing pressing business issues grows. Furthermore, the research enables an evaluation of the preparedness to implement such systems in a business context and the necessity for Process Mining systems in accordance with the digital maturity level of the organisation.
Ryndina S.V. “Import substitution of software for intelligent process analysis in Russia”, Research Result. Economic Research, 10(4), 102-110, DOI: 10.18413/2409-1634-2024-10-4-0-9
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