Measurement as infrastructure: why & how We measure our impact?

This was overdue, borderline problematic

Impact measurement is one of those sticky things: essential, but heavy. Most people in the field carry at least one war story about producing endless reports full of odd metrics that never informed a single decision. Others dismiss the whole enterprise as hand-waving (“where’s the data? how robust is it?”). On the other end, we’ve seen organizations hire full teams just to measure and report impact, only for the insights to gather dust.

That’s why it took us two years to land on our own approach. It’s not that we weren’t measuring. We’ve always had a clear North Star: incubating 25 ventures, impacting 50 million people, and mobilizing gazillion in private-sector capital toward big societal challenges. But a North Star is just direction, a compass. Measurement is the signposts along the way. It’s how we know if we’re on track, how we learn, and how we spend our time and money wisely.

Impact measurement as impact lever 

“Meh” organizations measure impact just to report it out. Reporting and communication are indeed important - but are only part of the story (and in my opinion, secondary in importance). Great organizations use it first to learn and make choices, and only then to communicate.

We realized we had a third reason: we’re doing it for impact itself. A solid approach, shared openly, becomes a lever.

For our ventures: the way we measure will shape who we back, the advice we give, and how they grow. For many, this framework will be their impact practice for years.

For the field: we’ve always built in the open. We publish discovery reports (Rebuilding Better, Turning Point), and even share our internal models when others ask. This is no different.

NGOs and foundations know measurement inside out, sometimes too well. They’ve got playbooks, best practices, even slick tools like the Impact Genome. But for mission-locked startups, funds, incubators, or blended models, the practice is less mature.

That’s why doing this decently and sharing it is impact in itself. And that’s why I’m writing this post.

The numbers we didn’t expect so soon

In true PollyLabs style, we moved fast. Kicked off in June. Brought in board member and impact strategy expert Kurt Dassel in July. By early August, the board had approved v1. The process was smooth and clarifying. Once again we saw the power of having the right people in the room: experts who push us to be rigorous, and a group dynamic that makes real deliberation and real progress possible.

We thought we were just laying the foundation. But as we pulled data, codified our logic, and spoke with our ventures, we realized we had already started.

One portfolio company reported that 80% of its customers increased their income by 20%. Another saw 70% of its users continued as monthly donors. Millions of dollars in loans have reached critical agribusinesses, and millions more in aid supplies have reached highly vulnerable communities, faster and with greater transparency. Some ventures had the same “wow” moment we did—the very act of structuring and codifying their impact gave them new clarity and appreciation for progress. They were grateful to have a tool that validated their work and helped them express it.

We also began to see early signs of system-level impact: thousands of people reading our work, global organizations and major platforms amplifying our message, and an incredible community that is engaged, excited, and eager to help build a movement around repurposing tech for good.

Designed for our needs, based on global standards, and built for portfolio value creation

Our approach matches our reality. Structured enough to give clarity. Light enough not to burden ventures. Anchored to our theory of change. Aligned with global standards. Designed to add value for ventures as much as for us.

Our metrics capture both the tangible and systemic layers of our work. We track lives changed and resources unlocked, but also ecosystem indicators, like the number of partners engaged or the amount of capital co-invested alongside us.

It’s appropriate for where we are today, and we know it will need to evolve. That’s why we’ve called it v1.0.

Repurposing frameworks for good

Below is our high-level measurement approach: imperative, principles, metrics, and evolution plan. There’s much more behind it: our theory of change, data collection mechanisms, impact profiles for each portfolio venture, and more. Ultimately, it all boils down to a set of metrics that serve as our signposts on this crazy journey.

This framework is not a cookie-cutter or copy-paste tool. We share it for inspiration, feedback, and reuse. If you adapt or borrow from it, let us know (we’ll measure that too 😉).

We’ll also host a PollyLabs Forum Briefing on this topic if there is interest. Let us know if you’d like to join the conversation.

In deep gratitude for everyone who helped shape this, and mostly to our board of directors who make it possible to get things done smartly and quickly.

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PollyLabs Impact Measurement & Management Framework - 1.0

Imperative

Impact measurement is a critical infrastructure at PollyLabs for three reasons:

1. Internal Compass – to know what we’re accomplishing and refine our approach.

2. External Communication – to build trust with donors, partners, and communities.

3. Raising the Standard – portfolio ventures and peers are already adopting our methods, so sharing openly helps set the bar for credible, systemic change.

Principles

1. Anchored in Theory of Change: every metric ties back to our impact thesis, giving line-of-sight from daily work to long-term mission.

2. Portfolio + Venture Levels: data comes both from PollyLabs’ direct work and from each venture, rolled up to show total portfolio impact.

3. Core vs. Total Impact: we report total portfolio impact, while internally distinguishing between ventures we built and those we backed

4. Direct + first degree Indirect Impact: we capture both immediate beneficiaries (e.g., farmer receiving a loan, reservist accessing mental health support) and secondary ones (e.g., family members, employees).

5. Aligned with IMP Framework: we use the five dimensions (What, Who, How Much, Contribution, Risk) to keep our data comparable and globally credible. Each venture has an “IMP snapshot” that rolls up into portfolio metrics.

6. Founder-Friendly: data collection is designed as a value-add for ventures. We extract what they already track, request only essentials, and make outputs usable for their own boards and funders.

Metrics

a. Portfolio Size & Composition Segmented into:

1. # Ventures Built – Incubated by PollyLabs

2. # Ventures Backed – Supported but not started by PollyLabs

b. Lives & Organizations Impacted

3. # of Individual Lives Improved – Tracked directly or estimated via service proxies

4. # of Organizations / Businesses Impacted – Where possible, translated into estimated lives reached for comparability

c. Depth of impact 

Value expressed in:

5. $ value or equivalents (e.g., cost of service accessed, productivity gain)

6. Other sector-specific units (e.g., hours saved, access rate, etc.)

d. Capital Mobilization (leverage and capital influence)

7. Co-Investment AUM – Total dollars invested alongside PollyLabs

8. Follow-On Capital Raised by Ventures – Segmented by type: philanthropic, catalytic, commercial

9. AUM Engagement – Capital managed by funders or investors directly engaging with our model or deals

e. Influence & Field-Building (system-level impact / field leadership)

10. # of Individuals & Organizations Engaged (e.g.,  downloads, participants, collaborators)

11. Mentions, Citations, and Media Hits