AI's Role in Decision Science

Check out this episode of the #1 people analytics podcast with special guest, Rob Dees, Senior Director of People Analytics & Insights at Target!

In this wide-ranging and deeply thoughtful conversation, Rob joins the show to explore what it truly means to bring decision science into people analytics, how a product-based operating model can transform HR, and why employee listening should be treated as an intelligence function—not just a sentiment survey.

Drawing on more than 20 years of military leadership experience and his academic background in decision science, Rob unpacks his “three-legged stool” framework for decision quality: alternatives, information, and preferences. He explains why organizations often over-invest in data while underinvesting in clarifying objectives, and how value-focused thinking can elevate workforce decisions from reactive to strategic. Whether discussing optimization models, AI-enabled decision support, or human capital investment, Rob consistently returns to one central principle: leaders must own the objective function.

The conversation dives into what it’s like to lead a 60-person people analytics team inside a complex enterprise. Rob shares how adopting a product operating model—with short sprints, user personas, rapid prototyping, and disciplined routines—helps teams move from slide decks to shipped insights. He outlines how a comprehensive and continuous listening strategy acts like a network of sensors on the battlefield, creating a common operating picture of the employee experience. By combining employee sentiment with operational human capital metrics, organizations move beyond awareness to real understanding.

One of the most compelling segments revisits Rob’s early work measuring the “whole soldier” at West Point, where he helped build a data-driven model around heart, body, and mind. That experience shaped his philosophy that performance models must integrate values, trade-offs, and measurable objectives. He connects those lessons to modern employee value propositions, showing how leaders can think in terms of optimization: if you had finite resources to invest in pay, flexibility, development, or belonging, where would you allocate them for maximum impact?

The episode also explores the intersection of AI and decision science. Rob explains how machines excel at processing information and generating alternatives, but humans must define preferences and constraints. In an era of generative AI and prompt engineering, the discipline of structuring objectives becomes more—not less—important. Without clarity on what you are optimizing for, even the most advanced models will miss the mark.

Finally, Rob reflects on leadership under pressure, including the powerful question: do your soldiers know your voice in the dark? From quarterly feedback rhythms in the military to continuous feedback cultures in business, he argues that clarity, proximity, and disciplined listening are foundational to performance.

If you care about the future of workforce intelligence, employee listening, AI-enabled decision-making, or building a high-impact people analytics function, this episode will challenge and sharpen your thinking.

If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.