Employee Productivity Modeling Using Competencies, Burnout, and Performance: A Fuzzy Logic and Econometric Analysis

In this study, we investigated the factors influencing the development of organizational human capital that directly or indirectly affect employee productivity.These factors include indicators of competency development and the level of individual burnout.We developed a two-stage economic-mathematical model to quantitatively describe the influence of employee competencies on key performance indicators (KPIs), considering burnout, which is determined by the values of loyalty, engagement, and satisfaction.The initial data for this study, obtained from self-assessments of competencies and burnout from employees in the information technology (IT) and human resources (HR) sectors within seven major Russian companies, were calibrated by the supervisors of the respondents.Additionally, the initial data included the actual KPI values of the employees.First, we constructed a fuzzy model based on a weighted integral competency indicator with optimal weight coefficients, which divided the integral indicator values into unevenly sized categories.These categories were used to predict KPI achievements.Second, using a weighted least squares method, an econometric model of the dependence of the KPI on employee burnout indicators was constructed to explain the dispersion of the KPI values (among employees in specific competence categories in the fuzzy model) around the expected KPI.This model predicts employee KPI achievements depending on the input competencies and burnout levels.This model was applied to create an optimal portfolio of well-being activities to improve employee competencies, reduce burnout, and achieve target KPI values.