ISSN 2587-814X (print), Russian version: ISSN 1998-0663 (print), |
Boris Slavin1Technologies of collective intelligence in the management of business processes of an organization
2022.
No. 2 Vol 16.
P. 36–48
[issue contents]
With the digitalization of the economy, the creative component of an organization’s activities increases. Standard business process management methods stop working due to the rise in uncertainty of the task solution time. Currently, there are no effective technologies for managing intellectual activity processes in organizations. The role of collective intelligence technologies for knowledge management in organizations has long been discussed in the literature, but there are still no concrete proposals on implementation. This work aims to show how collective technologies can solve the problems of managing business processes of intellectual activity. The possibility of collective intelligence technologies for increasing labor productivity is demonstrated. Models for distributing tasks by competencies and synergy from collaboration are proposed for this demonstration. The paper shows that competencies are the primary metric that can be used to measure work with knowledge in an organization. But they should also be considered when organizing group activities. A simple model example shows that the correct distribution of tasks by competencies allows you to increase the speed of solving tasks by a group by several times. In real cases, calculations using computing resources are necessary. A model is also proposed that demonstrates increasing the joint activity of a creative employee and an analyst. It is shown that business process management should be supplemented by mapping the competence model and group work options to the stages of business processes. This will allow you to manage the business processes of intellectual activity.
Citation:
Slavin B.B. (2022) Technologies of collective intelligence in the management of business processes of the organization. Business Informatics, vol. 16, no. 2, pp. 36–48. DOI: 10.17323/2587-814X.2022.2.36.48
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