The algorithm for applying the process maturity model to improve business processes in organization
https://doi.org/10.25206/2542-0488-2023-8-3-138-146
EDN: JMVSIA
Abstract
Business process management contributes to the effective operation of an organization with greater customer focus and a high level of productivity. These advantages have the potential to overcome the high level of competition; however, optimizing business processes in specific organizations is a challenge. Improving processes requires accounting for many aspects; therefore, many companies experience difficulties in managing business processes. Many practitioners and scholars work on developing business process maturity models to help organizations gradually implement business process management for specific processes and/ or for an entire portfolio of processes. The article considers the most popular maturity models. An algorithm for applying these models is developed. Theoretical principles for the development of the algorithm are represented. This algorithm allows for an ongoing maturity assessment. Based on the obtained results, the most appropriate maturity model for further optimization of business processes can be selected. Possibilities of subsequent application of the developed algorithm are considered.
About the Authors
S. I. ArtemyevaRussian Federation
ARTEMYEVA Svetlana Igorevna, Undergraduate
Student of Quality Management Direction
Moscow
G. S. Kublashvili
Russian Federation
KUBLASHVILI Georgiy Sergeyevich, Graduate
Student of Management Direction
Moscow
A. G. Zaitsev
Russian Federation
ZAITSEV Alexey Gennadievich, Doctor of Economics
Sciences, Associate Professor, Professor of Industrial
Economics Department ; Professor Faculty of Business,
Synergy University
Moscow
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Review
For citations:
Artemyeva S.I., Kublashvili G.S., Zaitsev A.G. The algorithm for applying the process maturity model to improve business processes in organization. Omsk Scientific Bulletin. Series Society. History. Modernity. 2023;8(3):138-146. (In Russ.) https://doi.org/10.25206/2542-0488-2023-8-3-138-146. EDN: JMVSIA
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