Economic and statistical analyses of labor productivity growth at russian industrial enterprises: Key factors

Increasing labor productivity (LP) is an actual task of the Russian economy and management of enterprises. Today, the country has a growing productivity gap between the most efficient and lagging companies. The aim of the study is to identify the key factors which determine the magnitude and growth rate of this indicator in the interests of revealing promising areas and ways of managing its growth. The paper describes the analysis of financial and economic indicators that are factors of sustainable growth in LP at domestic industrial enterprises, leading in this indicator in the period 2017–2019. The methodological basis has been the provisions of the production factors and productivity theories. The research method is based on the theorem of statistical hypotheses. The object of this research has been 94 Russian leading companies in terms of LP growth under reviewing period. An economic and statistical model of LP growth factors has been developed and the conditional probabilities of hypotheses have been calculated that characterize the ranges of growth of this indicator upon the occurrence of events corresponding to an increase in the values of financial and economic indicators. The key factors and the ranges of their change are highlighted for four ranges of the productivity rate: small, moderate, high and record. It is shown that the determining factors of a low rate are a revenue growth in the range from –23 to 57%, a decrease in the duration of an operating cycle to –7% and a growth in asset turnover up to 37%. The factors of the record rate of LP growth are revenue gain in the range 97–297%; operating cycle reduction in the range from –42 to –88% and the turnover of assets gain in the range 114–342%. The capital-labor ratio gain is considered with low probability as a factor of the moderate or high LP gain in combination with an increase in revenue and asset turnover. High correlation of the operating cycle reduction and increase the asset turnover can serve as an indicator of LP increase programs success. The proposed approach allowed to identify significant factors of LP growth at leading companies that had not been obvious during applying a regression analysis.

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