Framework for Balancing Short-Term Wins with Long-Term Product Goals

Strategy Is the Easy Part, Execution Is the Test

Michelle opens with a familiar scene. You build a product strategy. You map it to outcomes. You create a roadmap. You line up a cross-functional team. Then reality hits. The strategy that looked crisp in a deck turns foggy once trade-offs, capacity, and competing priorities show up.

For Michelle, strategy is not the poster on the wall. It is the path from mission to measurable outcomes. It is shaped by data, a clear understanding of users, and a tight definition of what success looks like. The hard part is what happens next, when you have to turn that strategy into impact without losing the thread.

She has a blunt reminder for anyone who says, “I just want to do strategy.” If you do not know how to execute, your strategy is fragile. Outcomes do not arrive because the plan was clever. They arrive because the team can deliver learning quickly, align on what matters, and keep shipping toward the goal.

The Portfolio That Keeps You Honest

Michelle’s core idea is a portfolio approach that forces balance. Instead of treating the roadmap like a single queue, she breaks work into three categories: quick hits, small bets, and big bets.

Quick hits exist to unlock learning. They are not a way to look busy. They are designed to test a specific hypothesis fast and to reduce uncertainty around the larger direction.

Small bets are where teams harvest gains. They build on what is already working, improve what was shipped halfway, and protect trust with partners who have heard “we’ll come back to it” one too many times. Michelle talks about the practical benefit here. This is where you actually return to the V1.5 you promised, so your design partner believes you next time.

Big bets are the step changes. The company cis hanging moves. The ten to twenty percent leaps that teams want on their resumes and leaders want in their quarterly narratives. But big bets are also slow, expensive, and full of unknowns. They trigger the predictable reactions: Are we sure? What data proves this? What else could we do instead?

Michelle’s point is not that big bets are bad. It is that big bets need a runway. A team earns the right to make them by stacking fast learning and credible wins.

Netflix Kids: When the Team Does Not Exist Yet

Michelle built this framework at Netflix, leading the Kids and Family product area at a time when resources were constrained. Netflix knew it needed a strong kids experience, and it knew Disney+ was coming. But the kids' product was not the center of the universe. It was the thing people agreed was important, right up until they had to fund it.

Michelle arrived and asked the obvious question: where is my team? The answer was equally obvious: define your strategy, then advocate for the resources.

So she did what strong product leaders do when the org is skeptical. She anchored the work in a vision that was specific enough to guide decisions, and emotionally clear enough to rally people.

Her team’s vision was to make Netflix the number one trusted service that empowers kids to effortlessly engage with their favorite characters and delightfully discover new ones.

Michelle insists every word mattered. “Kids” had to be the primary user. “Trust” mattered because parents are part of the customer system, even if they are not holding the remote every time. “Favorites” mattered because kids show up differently than adults. Kids do not open Netflix thinking, “I’d like to browse.” Kids open Netflix thinking, “I want Pikachu.”

That insight set up the strategic tension. Netflix needed kids to discover new shows, not only replay the familiar ones. But discovery would not work unless Netflix first won on favorites, and won the trust of parents who ultimately control access.

The Big Bet Everyone Wanted, and Why It Was Too Risky First

With a clear vision, Michelle’s team built a three-part strategy. Start with a foundation of trust with parents. Then empower kids to engage with their favorites effortlessly. Then build bridges to discovery so kids can delightfully find new characters and new stories.

On paper, it was compelling. Michelle presented it with a metaphorical “castle” strategy that made it easier for leaders to visualize. And then she hit the wall that every product leader recognizes. The question was not, “Is this inspiring?” It was, “How do we know?”

The first big bet was to put the favorites directly on the kids' homepage. The idea was simple. Replace a discovery-heavy adult-style interface with character-led entry points, made for kids, with less friction and more delight. But the implementation was anything but simple.

Michelle lists the dependencies: a new kids algorithm, a favorites algorithm, new character art, a UI overhaul, and a click-to-play experience. Multiple teams, high investment, long lead time, and still no proof that it would work.

So she did not argue harder. She stepped back, returned to the portfolio, and asked the question that de risks everything: what is the core hypothesis, and where can we test it fast using what we already have?

The Quick Hit That Changed the Conversation

The core hypothesis was clear. Kids want to interact with their favorites, and making that easier will increase watch time.

When Michelle’s team dug into the data, they found an early signal. Fifty-seven percent of hours on kids' profiles came from rewatch. Kids were already telling Netflix what they loved by watching it again and again.

Then came the statistic that reframed the whole problem. Thirty-seven percent of kids' watch hours were coming from search. Kids, or more realistically, their parents, were navigating to search and typing titles just to rewatch favorites.

Michelle’s reaction is almost physical. Kids struggle with remotes. Kids cannot reliably spell. Parents are likely frustrated too, acting as interpreters for “the show with the character” while the child repeats the request louder. Netflix was creating friction in the exact moment that should feel effortless.

The team looked at what they could change quickly. Kids were already visiting the search canvas. The search page already showed popular searches, built for adults. Netflix also had a “watch again” algorithm.

So they ran a quick hit experiment. Replace popular titles with the watch again algorithm for kids profiles, and move the default cursor from the search field to the first title, making play easier.

The result was a fifteen percent increase in watch time for kids, with measurable impact beyond the kids segment because of Netflix’s scale. It was not just a lift. It was credibility. It was proof that the hypothesis was real and that the team knew how to pull levers that mattered.

Now the conversation changed. If a quick hit in search could do this, what happens when favorites sit on the homepage, supported by an algorithm tuned for kids and wrapped in character art that speaks their language?

That is how Michelle earned the right to build the big bet. The bigger homepage favorites experience took months, required new systems, and moved metrics more significantly. But it only happened because the team de-risked it first.

Discovery Still Matters, So Test That Too

Michelle is candid about the trade-off. Favorites create engagement, but they do not automatically create discovery. Kids replaying the familiar does not magically push them toward new shows, and Netflix needed discovery for business reasons and for long-term customer relationships.

So the portfolio kept working. Instead of pretending one win solved everything, the team tested another hypothesis quickly.

They borrowed a behavior from kids' culture: unboxing. If you have seen kids watch Ryan’s World on YouTube, you know the pattern. The anticipation and reveal are part of the entertainment.

Michelle’s team applied that idea to discovery by inserting a new title among favorites. Positioned between beloved shows, the new content gained “validation” through proximity. When the kid reached it, it opened like a surprise, lowering the unfamiliarity barrier. The concept helped drive engagement with new titles and created another milestone of learning the team could build on.

The point is not that every team should copy unboxing. It is that teams should treat discovery as a hypothesis with tests, not as a slogan with a roadmap.

The Takeaway: Build Trust With Learning

Michelle is asked how she ensures teams actually return to small bets when priorities shift. Her answer is simple and hard. Trust is built with action. If you say you will come back, you have to come back.

The portfolio helps because it makes space for that commitment. It also reframes quick hits. They are not filler. They are hypothesis-driven learning designed to support the big bet and to help the team make smarter trade-offs with tech debt, design quality, and engineering stability.

If there is one lasting message from Michelle’s talk, it is this. Big bets are not de-risked by more debate. They are de-risked by sharper hypotheses, faster tests, and a roadmap that treats learning as a first-class output.

The next time your team asks, “Are we sure?”, do not answer with confidence. Answer with a test. Then let the results earn you the right to go bigger.

Want to watch the full talk?

You can find it here on UXDX: https://uxdx.com/session/framework-for-balancing-short-term-wins-with-long-term-product-goals/

Or explore all the insights in the UXDX USA 2025 Post Show Report: https://uxdx.com/post-show-report