Abstract

Introduction. The article is focused on possibilities of measuring the efficiency of organizational culture, which is relevant when planning and justifying the expenditures for personnel management. The aim of the study is to formulate an algorithm of actions which makes it possible to move from assessing the existing organizational culture to assessing the expected economic effects from measures to maintain or develop it. Methods. In the course of the research, the methods of comparative analysis, system analysis, functional analysis, desk research were used. Scientific novelty. In works devoted to measuring organizational culture, the emphasis is made on diagnosing its state, its features in any specific organizations, recorded, as a rule, on the basis of a number of well-known author’s methods. Researches on HR analytics and practical recommendations are focused on building a system of HR metrics and identifying their correlation with an organization economic performance in order to see solutions - “insights” in human resource management. At the same time, there are no works reflecting the relationship between the characteristics of organizational culture and the expected economic effects of its functioning, which would justify the necessity of expenditures for managing organizational culture for each specific organization. The article describes the possibility of transition from measuring the culture characteristics to the indicator of return on investment in human capital. Conclusions. The practice of assessing the economic efficiency of decisions related to the expenditures for organizational culture is accompanied by a number of difficulties in justifying the expected results. In our opinion, the variant of measuring the effectiveness of organizational culture described in the article has the right to exist. It should be noted that the correlations between culture indicators, HR metrics and economic effects can vary for different organizations, which is established empirically by observing changes in all indicators and their relationships over time.