Ep 299 – Jessica Zwaan (VP People Strategy and Operations, Leapsome)

1. Don’t start with a reorg — start with a mindset shift

One of the biggest misconceptions: you need to blow up your org chart to adopt People Ops as a product.

You don’t.

Jessica emphasized that the real starting point is shifting how your team thinks — from tasks to outcomes, from activities to problem statements. Many teams successfully pilot this model without changing reporting lines at all, simply by running work in a more product-oriented way.

That might look like:

• Setting quarterly “roadmaps”
• Letting team members opt into projects
• Running retrospectives on what worked

“I don’t think you need to restructure your entire team… it’s an operating principles shift.”

The takeaway: you can MVP this model before making any big structural bets.

2. HR teams need to stop shipping tasks — and start solving problems

Traditional HR work often looks like a relay race:
One person writes the policy → another uploads it → another communicates it.

But no one actually owns the outcome.

In a product model, that changes. Work is organized around problem statements, not deliverables — and cross-functional “squads” own the solution end-to-end.

Instead of:
“Let’s update the probation policy”

It becomes:

• Why are employees failing probation late?
• Where is confusion happening?
• What’s the actual cost to the business?

“That’s a problem statement that a group of people can come and work on.”

The shift is subtle but powerful: you’re no longer shipping HR artifacts — you’re improving business outcomes.

3. The ideal People team looks more like a product team than HR

At the core of this model are small, cross-functional squads — typically around 5–6 people — working together on a shared goal.

Each squad might include:

• A “product owner” (problem lead)
• Someone focused on user research (talking to employees/managers)
• Someone designing the experience (comms, workflows)
• Someone technical (HRIS, automation, integrations)

“You’ll have people that come together in a squad to solve a problem… and then you launch it, measure it, and move on.”

As you scale:

• Early stage → one squad doing everything
• Mid stage → squads aligned to funnel stages (e.g. hiring, performance, retention)
• Enterprise → multiple “products” with multiple squads underneath

The takeaway: structure follows problems, not functions.

4. The hardest buy-in isn’t your CEO — it’s your team

Counterintuitively, Jessica shared that most CEOs actually get this model quickly.

Why? Because it speaks their language:

• Efficiency
• ROI
• Output
• Business impact

The real friction often comes from within HR.

Why?

• It flattens traditional specializations (no more “just L&D” or “just TA”)
• It introduces ambiguity
• It raises questions about career paths

“It represents a couple of scary things… the work becomes less about tasks and more about owning an ecosystem.”

If you’re leading this change, your job isn’t just designing a new model — it’s helping your team see themselves in it.

5. Your metrics should connect people work to business outcomes

If you can’t measure it, it won’t stick.

But most HR metrics are too isolated — engagement scores, attrition rates, etc. Jessica pushes for cross-functional metrics that tell a deeper story.

Three standout examples:

• Internal Promotion Retention Rate​
  Do your best people stay after they grow?
• Employee Lifetime Value (ELTV)​
  What value does an employee generate over time vs. cost?
• Regrettable Attrition (redefined)​
  Not just “who left,” but:
  • Would we fight to keep them?
  • Would we rehire them?
  • Do we regret how it ended?

“Of the people we think are great… how long do they stay after their first year? That’s a really good metric.”

The takeaway: measure what actually reflects organizational health — not just what’s easy to track.

6. AI will amplify this model — but it won’t replace the human work

AI makes it easier than ever to build, automate, and ship solutions quickly.

Which makes this model even more relevant.

But Jessica pushed back on the idea that smaller, AI-powered teams should eliminate human interaction altogether.

“There’s a really high risk of a feature-output disconnect… where things feel less human.”

Her recommendation:

• Keep ~50% of time focused on “human operations”
• Talk to employees directly
• Validate what you’re building in real conversations

“Not everything is a survey… you miss so much fidelity when you reduce everything to that.”

The takeaway: AI should enhance your ability to build — not replace your ability to understand.

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