By default, the digital transformation of the economy is assumed to lead to an increase in the quality of management of all socio-economic systems. However, as any other economic process, digital transformation requires resources. Accordingly, a natural question arises about the efficiency of the use of these resources. At the same time, it should be taken into account that each process of digital transformation of management is based on information, i.e. quantitative and textual, primary, intermediate and result data on various aspects of the organization’s activities, its external and internal environment. It is extremely difficult to determine the economic efficiency of using data, since the same information is used many times in different management cycles. In addition, the lifetime (relevance) of data arrays can be very different. Therefore, it is necessary to develop an alternative approach to evaluating the effectiveness of data driven decision making, which, among other things, allows localizing the limiting coefficients for the use of information resources. The purpose of this study is to determine the range of limiting values of resource utilization factors based on the entropy-information balance equation. Achieving this goal is ensured by the implementation of the following stages: 1) mathematical definition of the entropy-information balance equation; 2) determining the ratio of the total cost of the resource used to the total cost of processing information in the information system; 3) determining the range of limit values for resource utilization factors, taking into account the use of digital technologies. The work is devoted to the issues of calculating limiting coefficients and represents the first stage in building an optimization model “data volume – information costs”. The development of system metrics is based on the entropy-information balance equation, which made it possible to establish the relationship between the probability of the state of production, the amount of information necessary for its purposeful change, and the performance indicator. The paper proves the systemic nature of this dependence, therefore, the numerical values of the limiting utilization coefficients can be used as standards in the feasibility study of digitalization projects.