IDENTIFICATION OF BUSINESS PROCESSES IN PROJECT MANAGEMENT

Abstract

The article analyses modern approaches to management of business processes in project management and considers practical aspects of identification of business processes of a project. It is substantiated that modelling and identification of business processes allows analysing not only how the enterprise as a whole operates, how it interacts with external organisations, customers and suppliers, but also how the activities of individual business projects are organised. The advantages and disadvantages of the top-down and bottom-up approaches to identifying business processes are considered. It is determined that the advantages of the bottom-up approach are the following: creating an opportunity to obtain a detailed understanding of operations at the lowest level; practicality and ease of identifying minor deficiencies at the beginning of the process; disadvantages are the high time costs, the possibility of making mistakes due to excessive concentration on details and the difficulties arising from integrating the identified small processes into the overall one.

The advantages of the top-down approach are a systematic approach, quick identification of key processes, and the ability to easily integrate processes with the organisation's strategic goals. The disadvantages include a lack of detail and high planning costs.

The following key business processes have been identified and detailed on the example of Vinnytsia Food and Beverage Factory PJSC: raw material procurement; production; quality control; logistics and supply chain; marketing and sales; customer service; and financial management. For project management, it is important that the identified business processes are synchronised with each other in time and in terms of solving certain tasks.

Prospects for further scientific research in the field of business process identification and project management are substantiated, such as automation of business process identification using artificial intelligence technologies; integration of business processes with modern project management systems; modelling and simulation of business processes based on real data; use of big data.