AUTOMATION OF PROJECT MANAGEMENT BUSINESS PROCESSES BASED ON THE KNOWLEDGE SPACE PLATFORM
The article explores the enhancement of consulting firm efficiency through the automation of project management business processes. In today’s competitive environment, consulting companies face the challenge of managing complex projects with precision and agility. By automating key elements of project management, organizations can not only streamline their workflows but also ensure better coordination, reduce human errors, and enhance overall project outcomes. The research highlights the development of a project lifecycle model, which allows for a detailed examination of the stages of project execution, from initiation to completion. Additionally, a target architecture model for the software solution is proposed, aimed at optimizing the structure and functionality of the business processes involved. The study focuses on the implementation of a project management information system built on the Knowledge Space platform, a low-code solution that provides flexible tools for modeling, analyzing, and optimizing both the structural and operational components of a company. The platform’s architecture supports the integration of various enterprise functions, offering a holistic view of performance metrics, workflows, and resource allocation. This comprehensive approach enables consulting firms to make more informed, data-driven strategic decisions. The automation provided by the Knowledge Space platform not only enhances operational efficiency but also empowers managers to respond dynamically to project challenges, ensuring timely delivery and customer satisfaction. Overall, the article emphasizes that the integration of automated business process management tools, such as those available through Knowledge Space, plays a critical role in modernizing project management practices, which is vital for the long-term success and competitiveness of consulting companies.
Authors
- L.Y. Sharabaeva
- Yu. A. Moseeva
Publication Details
- Journal
- Vestnik komp iuternykh i informatsionnykh tekhnologii
- Published
- 2024-12-01
- DOI
- https://doi.org/10.14489/vkit.2024.12.pp.053-059
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00