When I transitioned from growth team at a startup to product management, I learned that one of the most valuable skills for a PM isn’t perfect planning, it’s relentless focus on outcomes over outputs.
My tech career began as a Growth Manager at Rupeek, a Series-A fintech startup in India. Growth teams live and die by metrics. Every morning started with checking dashboards and asking the same question: “Did we move the needle?”
This mindset shaped how I approached problems. One of my focus areas was improving our customer acquisition funnel. Since we didn’t have set initiatives, my manager challenged me to measure the entire funnel and identify where customers dropped off.
This was my first lesson in zooming out to outcomes instead of opting for task completion. I built an end-to-end funnel tracking system that revealed which activities actually moved our conversion metrics. In the end, we tripled our rates by focusing resources on the highest-impact levers.
This metrics-first approach served me well for most of my career. That is, until I moved to product management and joined Statsig. B2B products introduced a new complexity: outcome measurement became far less straightforward.
This revealed the true PM dilemma: It's easy to say 'focus on outcomes', but much harder to identify which outcomes matter.
When a customer buys a platform, they’re not purchasing a single feature - they’re buying the complete solution. If we shipped a new feature this quarter, we couldn’t directly tie that to a new sale. Enterprise deals involve multiple decision-makers, inputs, and timelines, making it difficult to attribute success to individual features.
The natural fallback for PMs, myself included, is to default to task-based goals when measuring outcomes feels too complex. It's daunting to stake your credibility on outcomes you can't fully control.
I’ve seen PMs default to celebrate shipping every feature on the roadmap because it mimics progress when direction is uncertain. I’ve fallen into that trap too.
Early in my PM journey, I struggled to define strong outcome metrics for my team’s work. Without clear success measures, I leaned heavily on detailed roadmaps as a stand-in for direction. But the roadmap became an end, not a means.
This created three key problems:
Loss of engineering buy-in: Without a compelling "why" behind each task, engineers felt like order-takers rather than problem-solvers. Engagement dropped as they were relegated to executors.
Missed bigger opportunities: At Rupeek, I once spent months optimizing sales conversions by a few percentage points, only to realize later that boosting sign-ups would have had a far greater impact. My focus on a specific roadmap item blinded me to the larger picture.
Misaligned incentives: Measuring success by task completion rather than outcome impact reinforced a culture of checking boxes rather than driving real business results.
My turning point came when I partnered with a deeply product-minded Engineering Manager. He ran user research with me, dug into the data, and co-developed hypotheses around problem-solving.
Instead of me dictating goals, we co-created metrics that could signal the business outcomes we aimed to drive. We debated the pros and cons of each metric and ultimately aligned on a shared north star. Soon, the team's conversations shifted from “Are we completing the tasks?” to “Given the desired outcomes, what’s the best path forward?”
Aligning on outcomes before building anything transformed how we worked. Engineers became more engaged, our solutions improved, and we built real momentum.
Following a roadmap exactly as planned can feel safe. However, the high-impact approach is having the courage to kill roadmap items when the data proves them wrong.
Effective PMs understand that success isn’t finishing the roadmap, it’s achieving the right outcomes. This requires:
Letting go of sunk costs: When the data shows an initiative isn’t working, cut it – no matter how much time you’ve invested.
Zooming out regularly: That metric you’ve been optimizing might not be the one that matters most. Don’t miss the forest for the trees.
When direct feature-to-revenue links are unclear, look for leading indicators (e.g., feature adoption, activation rates, etc.) as a proxy for success. It’s better to pursue imperfect direction than shy away from outcomes.
At Statsig, I’ve seen this same transformation play out with our customers. One of our customers is a leading sports-tech company. Their business is seasonal, with demand spiking in the summer. Previously, they’d ship dozens of features each summer, without tracking feature-level adoption or impact. The team felt good about their product velocity, but lacked insight into real results.
That changed when they started using Statsig’s feature gates to measure the impact of every software release. Last season, they learned that only 2 out of 12 features actually moved the needle, while 3 caused regressions.
This data radically changed their mindset. They embraced the outcomes-over-output philosophy, shifting their focus from “Did we ship it?” to “What did it do?”
This shift wasn’t just about tooling, it was about a deeper change in how they built products, measured success, and responded to data.
At Statsig, our team has worked on hundreds of products across industries. We’ve learned these lessons the hard way: through failed launches, misalignments, and metrics that missed the mark.
We’ve captured those lessons in a guide built on real-world experience: from our PM team and from our customers. It’s full of practical frameworks to help teams stay focused on outcomes over outputs, and avoid the roadmap traps we’ve already faced.
If these challenges resonate with you, our free guide offers tactical ways to shift your mindset and execution toward real impact.