AUTOMATED DISTRIBUTION OF PROCESSES IN IT PROJECT MANAGEMENT

Abstract

In modern IT project management, the problem of effective task distribution between performers is of particular relevance. Automation of this process allows to significantly increase the productivity of teams, reduce the time for completing tasks and minimize the impact of the human factor. The article considers the information technology of automated process distribution in IT project management, which is based on the use of an information model of the management organization, a mathematical model of predicting the effectiveness of performers and a method of assessing their compliance with the given criteria.

The proposed information technology takes into account the level of competencies of employees, their professional experience, history of performing similar tasks and experience of interacting with other team members. The developed mathematical model allows to calculate the predicted efficiency of task performance by each performer, based on a system of weight coefficients that determine the impact of competence, experience and team interaction. The method of assessing efficiency is based on the analysis of input data and is used for optimal task distribution.

The algorithm of operation of the proposed technology includes four main stages: input data update, selection of an IT project with unallocated tasks, assignment of executors based on calculated performance indicators and formation of a production map of project execution. The output data is a personalized distribution of tasks between developers, which allows to increase the efficiency of project execution and reduce the risks of delays.

The result of the implementation of automated process distribution in IT project management is an increase in team productivity, optimization of resource use and reduction of the probability of ineffective assignment of executors. The proposed methodology can be used in organizations working on large-scale IT projects to improve the quality of management decisions and the efficiency of project implementation.