Under conditions of limited opportunities for extensive infrastructure renewal, the impor-tance of labor productivity in contemporary service-industrial and manufacturing enterprises that ensure the functioning of a geographically distributed network of engineering facilities is increasing. The system of business processes of the economic activities of such enterprises constitutes the object of the present study. For such enterprises, labor productivity depends not only on the number of employees and the total volume of work performed, but also on the structure of tasks, planning density, intensity of site visits, and personnel travel time. This determines the need to search for models for improving labor productivity that take into account measurable characteristics of business processes. The aim of the study is to develop an operational model of labor productivity for these enterprises that represents this indicator as an analytically interpretable dependence on measurable characteristics of business processes, as well as to formulate and substantiate directions for optimizing economic activity. The research methodology is based on the operationalization of labor productivity through parameters that reflect the organization of work and working time costs. The empirical basis of the study is a cross-section of operational data from a large Russian service-industrial enterprise, Russian Television and Radio Broadcasting Network, for 2025, including indicators for engineering facilities, maintenance units, and territorial branches, as well as derived indicators calculated on their basis. The study identifies controllable factors and diagnostic indicators that characterize the structure of work, frequency and intensity of site visits, planning density, and personnel travel time. The scientific novelty of the study lies in transforming labor productivity from an aggregated reporting indicator into an operationally decomposable value linked to observable process characteristics. The results of the empirical testing show that the parameters of the proposed model are represented in operational data, can be calculated, and make it possible to interpret differences in labor productivity between comparable facilities and units. The practical value of the study lies in the possibility of using the model to identify organizational reasons for differences in labor costs and to justify directions for increasing labor productivity without reducing the analysis to universal standards. The study concludes that the proposed model is applicable for the analytical description of labor productivity using data from a large enterprise. The limitation of the study is related to the use of cross-sectional data for a single period. Further research should focus on the use of panel data, testing the stability of the identified relationships over time, and clarifying the boundaries of applicability of the model for different types of enterprises.