| Issue |
SHS Web Conf.
Volume 106, 2021
III International Scientific and Practical Conference “Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth” (MTDE 2021)
|
|
|---|---|---|
| Article Number | 01036 | |
| Number of page(s) | 7 | |
| Section | Digital Technologies in Socio-Economic Systems Management | |
| DOI | https://doi.org/10.1051/shsconf/202110601036 | |
| Published online | 18 May 2021 | |
Integration of the controlling mechanism into the Deming-Shewhart PDСA cycle in the context of digitalization
1
Tajik National University, 73402517 Dushanbe, Tajikistan
2
Moscow (Senkevich) State Institute of Physical Culture, Sports and Tourism, 125499 Moscow, Russia
3
Russian State University of Tourism and Service, 141221 Cherkizovo, Russia
* Corresponding author: munir-k@list.ru
Digitalization provides an increase in the efficiency of production management, and also opens up wide opportunities for the formation of models of management decisions using predictive technologies. Digital technologies systematize and combine information flows of different origins. Thus, a predictive model of strategic and tactical production management is created. A condition for the successful digital transformation of economic sectors is the development of a set of measures for the technical re-equipment of enterprises. This article proposes an integrated controlling model based on the concept of continuous improvement of PDCA processes. The PDCA cycle model is adapted to the process of technical re-equipment of the enterprise and is integrated with the controlling mechanism based on the process approach. Such integration will ensure an increase in the controllability of the technical re-equipment process, improve the coordination of personnel actions, and create effective feedback mechanisms. The proposed model will increase the validity and efficiency of management decisions.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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