READINESS INDEX FOR IT CAREER RESKILLING: CONSTRUCTION BASED ON FACTOR ANALYSIS OF SURVEY DATA

This article introduces an index-based model for assessing the readiness of adults to undergo professional reskilling into the IT sector. The model was developed based on survey data collected from 127 individuals across various regions of Ukraine who expressed an interest in transitioning into IT-related occupations. The methodological framework relies on Principal Component Analysis (PCA), a statistical technique that enables the extraction of key latent components from a multidimensional dataset without requiring subjective expert weighting. This ensures that the evaluation process remains data-driven and objective, which is especially important in applied management research. The survey included 22 items covering motivational, behavioral, and infrastructural factors such as access to digital tools, previous online learning experience, self-discipline, available time for study, English proficiency, and declared interest in different IT domains. Binary responses were numerically encoded, and all variables were standardized prior to analysis. PCA revealed three principal components that together explain the majority of the dataset’s variance: (1) resource readiness, including time, internet access, and personal devices; (2) motivational and psychological orientation, encompassing the desire for change, internal barriers, and learning confidence; and (3) educational and career orientation, which includes English language skills, exposure to online learning, and clarity of IT specialization preferences. A composite readiness index was constructed by combining these components with weights derived from their explained variance and then normalized to a 0–100 scale. Respondents were categorized into three groups: low, medium, and high readiness. The findings show that 52% of respondents fall into the medium category, 29.9% into the low category, and only 18.1% into the high category. These results highlight significant differences in personal and contextual factors that influence the success of reskilling trajectories. The index offers a practical tool for HR managers, educational providers, and policymakers seeking to design adaptive training programs, improve candidate targeting, and forecast reskilling outcomes. It contributes to the management field by offering a replicable framework for human capital assessment in the context of digital transformation.