Identification of Labor Productivity Factors Based on Big Data Analysis on the Level of Key Performance Indicators Implementation of Employees and Managers of the Company in the Modern Conditions

Abstract

The article analyzes factors that potentially determine the dynamics of changes in labor productivity of employees in a large outsourcing company as their length of service in the company increases based on big data analysis (10,651 observations). Key performance indicators (KPIs) of employees hired by the company for the period from 2020 to 2023 were selected as indicators of the level of employees’ labor productivity. Based on the results of the analysis, we can conclude that the monthly increase in the level of KPI implementation is associated with two factors: the average level of KPIs of colleagues and length of service in the company. The results obtained allow the authors to propose an approach to increasing the labor productivity of new employees and creating high-performance teams, as well as to calculate the potential economic effect of implementing such an approach. The results obtained in the study will be of interest to practitioners and employees in the scientific field. Specialists in human resource management (HRM) departments can use in their work the proposed approach to increasing the productivity of new employees, while the qualitative and quantitative assessments obtained from the analysis may be of interest to current scientific employees.

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