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Check out this episode of the #1 people analytics podcast with special guest, Madeline Laurano, Founder and Chief Analyst at Aptitude Research!
Host Cole Napper sits down with Madeline to unpack the real ROI of people analytics, drawing from Aptitude Research’s findings that only about 18 percent of HR leaders even track it while talent acquisition leaders lag further behind. They explore the critical gap between traditional HR metrics like time-to-fill that business executives largely ignore and the outcomes that actually matter at the C-suite level—retention, productivity, revenue impact, and cost. The conversation digs into how the pandemic-era technology buying spree left many organizations with underused systems whose data makes little sense, creating barriers that people analytics teams must now navigate by collaborating more closely with CFOs rather than operating in silos. Madeline and Cole contrast how HR leaders and analytics practitioners define ROI, emphasizing costs, benefits to the business and employees, and realistic payback periods that can shrink to months with AI rather than the multi-year horizons once common in HR tech. They discuss the need for ongoing measurement instead of once-a-year calculations, the value of distinguishing direct from indirect returns, and the simple power of “journaling” executive priorities to build credibility. Strategic workforce planning emerges as both a long-standing passion and source of frustration for Madeline—too often treated as a start-and-stop exercise triggered by layoffs or relocations—yet newly urgent amid AI-driven restructuring of how work and tasks get done. Cole outlines the extensive data required to assess AI’s true workforce impact: third-party skills and task information, actual usage from tools like Gemini or Claude, internal productivity metrics, non-employee labor contributions, and full cost comparisons including human labor versus AI tokens. Vendors claiming to have solved this, they agree, simply do not yet possess that complete picture. The pair also examine what it means to be an independent HR industry analyst: conducting quantitative surveys, qualitative interviews, and endless vendor demos to deliver market clarity and informed forecasts, while relying on hard-won judgment and discernment that years of experience—and even newly minted sharp analysts—can cultivate. Side conversations at small dinners and informal gatherings often reveal more about real buying decisions, organizational politics, and vendor positioning than formal research alone. Looking ahead, they explore the shift from people analytics toward people intelligence, where human judgment, context, and gut feel complement AI rather than being replaced by it, and why positioning AI as a tool serving people rather than an equal collaborator remains essential. Practical AI agent use cases that already work—highly focused, low-risk, end-to-end tasks such as candidate sourcing or frontline shift scheduling—demonstrate how technology can restore autonomy and meaningfully improve workers’ lives. Additional threads cover the declining relevance of college rankings beyond the top twenty for early-career hiring, the salary-equivalent value of well-designed jobs that offer variety, learning, and initiative, the underappreciated strategic role of organization design, and a proposed AI-era HR operating model built around workforce intelligence, capability architecture, and strategy. Throughout, Madeline shares insights from her role as MC and product judge at the HR Technology Conference and the messy current state of agentic AI that demands better governance and orchestration if the industry is to move beyond chaos. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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