The VP Who Still Pulls Her Own Data
May 27, 2026
The VP Who Still Pulls Her Own Data
When you manage a $300M portfolio, you don’t file a ticket every time you have a hunch.
Jessica Matthews is a VP of Global Product Management at Gartner. She holds a Masters in Data Science from UC Berkeley. She manages a subscription portfolio worth more than $300 million.
And she still pulls her own data.
Not because her analytics team can’t do it. Not because she doesn’t trust them. Because sometimes you have a hunch at 2pm on a Tuesday, and the choice is: write a ticket, wait for it to land in a sprint, and get an answer in two weeks. Or open the data yourself and know in twenty minutes.
Jessica chooses twenty minutes.
“I certainly found it handy every once in a while to pull my own data sometimes if you’re just like I have a hunch but I don’t know if this is something I’m really going to write a ticket to a team to put in a sprint.”
This is one of the quietest, most powerful moves a senior leader can make. And it’s exactly the kind of move most leadership advice tells you to stop making.
Why VPs stop getting their hands dirty
There’s a script that kicks in around the Director level. You’re supposed to delegate everything technical. You’re supposed to “trust your team” and “focus on strategy.” The implication: if you’re still pulling data yourself, you haven’t really grown into the role.
I’ve heard this from dozens of leaders on the podcast. The pressure to let go of the work, completely, as proof that you belong at the table.
The problem is that letting go of ALL the work creates a gap. You lose the speed of your own judgment. You start depending entirely on other people’s framing of the data, other people’s priorities for what gets investigated, other people’s timelines for when you get answers. Your hunches die in the queue.
Jessica didn’t let that happen. She kept her technical skills sharp enough to act on her own instincts when the moment called for it.
The bridge, not the authority
What struck me most about Jessica’s approach is what her technical background gives her beyond speed. It changes how she works with her engineering and data teams. She doesn’t pull her own data to go around them. She does it to meet them where they are.
“I feel like I better understand where those teams are coming from and why they might not have seen a gap that I see — I just understand like oh you have this view and I have this view so here are the things that we need to connect on.”
That sentence is the whole AI player-coach thesis in miniature. She’s not using her data science background to override her team’s judgment. She’s using it to understand why they see the world differently than she does, and to close that gap in real conversation instead of through escalation or mandates.
A leader who has never touched the data can only say “I need this analyzed.” A leader who has pulled it herself can say “I ran a quick regression and here’s what I’m seeing. Does that match what you’re tracking? What am I missing?”
The second version starts a conversation. The first version starts a task.
The speed that compounds
At the VP level, the speed of insight compounds in ways that are hard to see from the outside. Jessica’s twenty-minute data pull doesn’t just answer one question. It changes which questions she asks next. It shapes the strategy conversation she walks into the following morning. It means she shows up with a point of view grounded in data she actually looked at, not a summary someone else prepared.
That kind of grounded intuition is what separates leaders who set the direction from leaders who approve the direction someone else set. When you maintain enough technical fluency to act on your own hunches, you stay in the driver’s seat of your own product strategy.
This is especially true now, when AI tools have collapsed the distance between “I wonder if…” and “here’s what the data says.” The leaders who are staying hands-on with AI are building this same muscle Jessica has always had with data. They’re keeping the gap between their questions and their answers small enough to move fast.
What this means for you
If you’re a senior leader reading this and feeling a pang of recognition because you used to be the person who could pull their own data, build their own prototype, or test their own hypothesis, and somewhere along the way you stopped: you don’t have to stay stuck.
You don’t need to become a data scientist. You don’t need to take over your analytics team’s sprint. You need to keep enough hands-on capability that when you have a hunch, you can act on it yourself before the moment passes.
Jessica manages a $300M portfolio and she still does it. That’s not a failure to delegate. That’s a leader who refuses to let her own judgment get bottlenecked by a ticket queue.
Polly Allen is the founder of AI Career Boost and host of The AI Product Leader podcast. She spent years leading AI at Amazon Alexa before building the AI Career Boost Blueprint, an 8-week program for Director+ product leaders becoming indispensable AI player-coaches. Subscribe to The AI Player-Coach newsletter →
