Date of Conferral

10-26-2026

Date of Award

October 2026

Degree

Doctor of Business Administration (D.B.A.)

School

Management

Advisor

Meridith Wentz

Abstract

Some information technology (IT) leaders lack strategies for interpreting predictive analytics, limiting the use of workforce data in retention decisions. Grounded in the technology acceptance model, the purpose of this qualitative pragmatic inquiry was to explore how IT leaders perceive and interpret predictive analytics when making adoption decisions to reduce employee attrition. The participants were nine IT leaders with at least 5 years of IT leadership experience and recent predictive analytics decision-making experience. Primary data were collected through individual, semistructured, audio-recorded telephone interviews. A subsequent review of five federal reports contextualized the findings. Data were analyzed using thematic analysis, resulting in five overarching themes and four subthemes. The five overarching themes were: (a) adoption of predictive analytics is an organizational process, not a technical purchase; (b) the usefulness of predictive analytics depends on actionable information embedded in workflow; (c) trust requires explanation, human judgment, and safeguards; (d) governance involves both friction and infrastructure; and (e) affected-population perception is an adoption condition. Adoption depends on organizational capacity and a feasible managerial response. A fundamental recommendation is for IT and human resources leaders to pilot predictive analytics within a distinct retention workflow, assigning responsibility for reviewing predictions and documenting actions. The implications for positive social change include the potential for fairer workforce decisions, protection of employee self-worth, and greater employment steadiness for employees and their families.

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