Publication Details
Abstract
The rise of digital transformation and the spread of Industry 4.0 technologies have significantly transformed production processes and management systems, such that traditional methods of measuring labor productivity and value added may be insufficient. Although labor productivity is a fundamental measure of economic efficiency and competitiveness, traditional quantitative measures do not account for the qualitative and intangible benefits that are produced by digital management technologies, such as ERP, CRM, artificial intelligence and big data analytics. Ultimately, this misalignment has led to the empirically observed productivity paradox which states that despite these enormous investments into digital technologies we simply do not see commensurate productivity growth in the statistics.
The paper fills an important methodological gap related to the assessment of labor productivity in the conditions of digital management by proposing a hybrid evaluation framework. It draws on comparative analysis, abstract logical reasoning, and mathematical modeling, with a conditional enterprise implementing digital management systems as the analytic object. Combining traditional indicators with contemporary, including KPI, multifactor productivity, and digital asset efficiency metrics.
The results confirm that the use of digital management systems not only markedly alleviate labor intensity and improve algorithmic efficiency, but employee digital skills are crucial for achieving productivity outcomes. But time savings do not always lead to value generation, suggesting that companies need to develop sophisticated measurement techniques.
Not surprisingly, the findings show that hybrid productivity models reflect real performance more accurately. Implications of the study assist in enterprise level digital strategy design and help advance the discipline of productivity assessment at the level of national economics.