Classification of Digital Recruiting Characteristics and Assessment of the Economic Effect for Recruiting Companies in Industrial Sectors of the Central Federal District

The purpose of the article is to develop a conceptual classification of digital recruiting characteristics and to quantitatively assess the economic effect of their implementation for recruiting companies working with industrial enterprises of the Central Federal District (CFD) of Russia. A four-level classification of digital recruiting configurations (K0 - K3) is presented, grouping tools into three functional blocks: sourcing, onboarding and analytical support of personnel. The configurations are interpreted as successive stages in the development of a digital recruiting ecosystem, ranging from manual recruiting and basic automation to an integrated platform with an analytics block. Based on data from 36 industrial enterprises of the CFD that are clients of a recruiting company which implemented a digital HR management ecosystem, an integral digital maturity index (I_dig) was developed, aggregating the components of integration, automation, analyticity and adaptability. It is shown that, when moving from configuration K1 to K3, the value of I_dig increases from 0.529 to 0.955 (+80%; p = 0.001). Improvements in key client indicators are recorded: the share of vacancies closed on time increases by 6.8 percentage points (p = 0.002), HR managers’ satisfaction rises from 3.69 to 4.29 points (p < 0.001), and the average duration of production downtime decreases by 1.49 days. The average time-to-fill remains virtually unchanged, confirming the influence of structural labour shortages. Calculations of the total economic effect show 17 -70 million rubles per year with an average ROI of 250 - 1100% for configuration K3. The analytics block accounts for 37.9% of the I_dig increase and acts as the main source of nonlinear ROI growth, which justifies prioritizing investments by recruiting companies in advanced analytical configurations of digital recruiting when working with industrial clients.