Daas Cool Episode 1 with Alexis Fink

As enterprises increasingly hire data scientists and engineers to work directly with workforce data, the conversation around people analytics has shifted from simple reporting to strategic decision-making. Alexis Fink, who has held senior roles at Microsoft, Meta, and Intel, and now leads organizational transformation through Propeller Insights, offers a masterclass in how to turn workforce data into measurable business impact.

For outsiders, the terminology can be confusing. Workforce strategy, talent intelligence, and people analytics often seem interchangeable. According to Fink, while these functions share a common goal of using data to make better workforce decisions, each serves a distinct purpose:

Talent Intelligence focuses on the external workforce, analyzing where talent exists in the market and how to access it.

Workforce Strategy takes an internal, aggregate view, addressing questions like:

People Analytics operates at a more granular level, examining:

The most powerful implementations connect these three islands of insight. As Fink notes, "The ability to tie those islands together has offered a chance to make the whole worth more than the sum of its parts."

Reporting structures for these functions vary widely. Recent benchmark data shows only about 30% of people analytics leaders report directly to the Chief Human Resources Officer. Others report to operations leaders, talent leaders, or even heads of benefits.

More surprisingly, these functions sometimes sit outside HR entirely. Fink has seen workforce strategy in finance functions, talent intelligence in real estate departments, and analytics in centralized data teams. One customer even houses their talent intelligence function within corporate development, using external talent data to identify acquisition targets based on where high-quality talent clusters exist.

The key takeaway? If you're trying to build these capabilities, look beyond HR. Someone in finance, real estate, operations, or strategy is likely already doing related work. Joining forces and combining datasets can dramatically amplify your impact.

One of the biggest mistakes data teams make is falling in love with their insights without connecting them to action. Fink, trained as a scientist, recognizes this trap: "That's kind of what you do in your discussion section. This is brilliant. I'm smart. Go other people. Be interesting."

The places where she's had the biggest impact are where insights tied directly to operational business processes. Whether that's planning cycles, acquisition strategy, or product roadmaps, the connection to what the business actually does transforms data from interesting to indispensable.

Every talent leader Fink speaks with is grappling with AI, but not just in the obvious ways. The conversation extends across a spectrum:

Operational HR: How can automation improve recruiting, performance management, and benefits deployment?

Capability Development: What new skills are required? How will jobs change? How do we build strategies that deploy these technologies effectively?

Risk and Ethics: How do we protect employee privacy? What are the legal risks across different countries? How do we equip managers to operate in this new world?

Interestingly, HR may be better positioned to lead these conversations than many realize. Recruiting has been using AI-powered tools like resume recommenders and applicant tracking systems for over a decade. HR teams have been dealing with questions of privacy, confidentiality, accuracy, and bias for years. This experience makes them well-suited to advise the rest of the organization on AI investments.

One area where Fink sees tremendous opportunity is internal mobility. The challenge is finding the sweet spot between three competing factors:

Someone who knows less about the content of work but deeply understands the organization can often be more effective than an external expert. Yet as organizations grow beyond several thousand people, making these connections becomes increasingly difficult without technology.

Fink has built three different systems to address this challenge, using different strategies each time based on the moment and available resources. The common thread? Some combination of buy versus build has always been part of the strategy.

The principle is straightforward: buy commodities, build competitive advantages.

Anything you can get from an external vendor, anyone else who can write a check can also get. It's not unique to you by definition. Vendors optimize for "good enough fit" across many customers, not perfect fit for your specific needs.

Fink advises companies to think about where they need an A grade versus where a B is acceptable. For the B-grade needs, buying is almost always more cost-efficient. But where you need an A, where something is a pillar of your competitive advantage, you need a perfect fit optimized for your strategy.

As one analogy suggests, data providers are like flour for a bakery. Everyone can buy the same flour, but what makes it magical is the skill of the baker. The flour alone won't even be a B grade. It takes significant time, refinement, and expertise to turn raw data into organization-shifting insights.

Early in her career, Fink made what she thought was a smart decision. Building an attrition model, she forecasted on the higher end to make sure HR could hit all its goals and look good at year end. It worked. HR came out smelling like a rose.

Then the head of engineering called and dressed her down.

Because her attrition estimate was wrong, engineering didn't launch projects they thought they wouldn't have headcount to support. That extra 2-3% of people translated to additional teams, which translated to additional projects, which translated to significant revenue. Her attempt to make HR look good cost the company "wheelbarrows full of money."

This experience taught her a crucial lesson: engineering roadmaps were being gated by her headcount forecasts. The real ROI wasn't in HR metrics. It was in the business outcomes those metrics enabled or constrained.

Fink has never found a CFO who accepts the traditional HR math of converting saved hours into full-time equivalent costs. What CFOs do accept:

Committed budget you won't spend: Specific line items like intern conversions you'll skip or entire sites you'll close (which captures real estate and ancillary costs, not just payroll).

Increased output and quality: Delivering at higher than nameplate capacity. Fink has used people data to increase customer renewals by 20% in specific regions, tying directly to revenue.

Real cost avoidance in budgeted line items: In one role, she nearly tripled the rate at which employees from wound-down projects were rehomed internally. The financial impact was enormous. Exit costs ran about $70,000 per person, and about a third of exited employees returned within three years, requiring new hiring bonuses and recruiting costs. The company was effectively giving people one-year paid sabbaticals while traumatizing teams. Changing this process saved real budget dollars that the CFO recognized.

Traditional HR metrics like time to fill, retention rates, and promotion metrics matter. But the transformational stories Fink shares go beyond these. They're about:

These aren't transactional improvements. They're strategic discoveries that change how the business operates.

How do you identify these high-impact opportunities? Fink's approach:

Get outside the HR bubble: Talk to business leaders about what's hard for them, what they're trying to deliver from a business perspective, not an HR perspective.

Build relationships across functions: Her first five years were spent supporting operations, including a stint in supply chain. This gave her a fundamentally different perspective than if she'd started in HR.

Focus on what the business is trying to deliver: When working with country managers, she asked about their number one metric. Customer renewals emerged as critical. When working in factory operations, she learned that reducing waste had immediate bottom-line impact.

Look for high-frequency activities: As you get further from direct HR impact, your effect size gets smaller. But even 1-2% improvement on something done millions of times adds up to real money.

Think in terms of 3x to 10x returns: Junior HR people often think of ROI as break-even, but businesses need significant multiples to justify the attention and opportunity cost. You're more likely to get 3-10x returns by doing something markedly better, not just doing the same thing more cheaply.

The most interesting dataset Fink ever worked with came from an unusual reporting relationship: the company's chief medical officer reported to her. With fully anonymized, excellently protected data and careful privacy protocols, they were able to cut the heart attack rate of their population.

Interventions included on-site blood work at company medical clinics attached to cafeterias, paid personal trainers at on-site gyms, and other wellness investments. The payoff was both human (children who grew up with parents who didn't die from heart attacks) and financial (avoiding expensive medical bills and time away from work for a self-insured organization).

This required spending money upfront, but the return in terms of human well-being and avoided costs was substantial. It's a powerful example of how the right data, used appropriately and ethically, can drive investments that are both humane and financially sound.

Now in her post-corporate season after 30 years in leadership roles at major companies, Fink is focused on the intersection of technology and people. Her work helps organizations figure out what they need to do differently to take advantage of available technology, from technology strategy to practical org design.

As she puts it, "If you're lucky, you get to live through a transformational moment like this and get to be part of creating the future."

For workforce strategy and people analytics leaders, that future is about moving beyond reporting to become strategic partners who drive measurable business outcomes. It's about connecting the islands of talent intelligence, workforce strategy, and people analytics into a coherent whole. And it's about telling ROI stories that resonate not with HR metrics, but with the language of business impact that CFOs and business leaders understand.

The organizations that figure this out won't just have better HR functions. They'll have a genuine competitive advantage in how they deploy their most important asset: their people.