Regression and correlation models in an automated system for supporting managerial personnel decision making

The paper solves the problem of constructing a regression model in the form of a power-law two-factor form and a correlation model of staffing performance in the form of transfer functions. The input indicators for the models are the number of employees and the ratio of the average monthly salary in PJSC NK Rosneft to the average salary in Russia, and the output parameter of work efficiency is the volume of oil and gas condensate production.