Measuring Innovation: Why Learning is the Real Engine of Innovation Funds

Innovation funds are specialized financing mechanisms designed to back bold ideas and emerging technologies. Unlike traditional grants or loans, these funds typically provide patient capital—funding that doesn’t demand immediate returns—to entrepreneurs and organizations tackling complex challenges like financial inclusion, climate adaptation, or digital identity. They bridge the gap between initial research and market-ready solutions, providing not just funding but also mentorship, technical assistance, and connections to potential partners and customers.

However, the reality is that the user and community impacts that funders and innovators care about often emerge late —if they emerge at all. In the meantime, what matters most for funders is the pivots, the lessons, and the intelligence generated along the way.

For innovation portfolios to succeed—for founders, investors, and users—the innovation ecosystem needs measurement systems that treat learning as a central outcome. Done right, measurement becomes a catalyst, supporting innovators in navigating uncertainty, generating early intelligence for investors, and building the connections that enable solutions to scale.

Imagine two innovation funds.

In the first, measurement is static. Funders and rigid milestones lock teams into quarterly reports that track activities instead of learning. They judge success by predictable milestones that don’t fit breakthrough ventures. The system penalizes adaptations, sidelines learning, and nothing useful is shared with the wider ecosystem. Instead of catalyzing progress, the measurement system holds innovations back, trapping promising solutions in reporting straightjackets.

In the second, funders encourage a dynamic where measurement is agile and responsive. They support dedicated time for portfolio teams to reflect, make sense of results, and learn. They treat pivots as intelligence, not failure. They connect founders to the right support at the right time, and insights are shared across the ecosystem, giving investors, policymakers, and peers a clearer view of what’s working and why. The portfolio builds both innovation and market intelligence.

Both funds invest the same money. But only one creates the conditions for innovation to survive uncertainty and grow to scale.

Using light-touch tools, such as collaborative templates, to track adaptation can open a window into the innovation process. That’s a powerful driver for three reasons:

By paying attention to how innovation unfolds, innovation-centered Measurement, Evaluation, and Learning (MEL) is equipping investors and innovators with the knowledge to make better decisions in the face of uncertainty.

In the Mastercard Strive EU program, Caribou’s Measurement & Impact (M&I) team collaborated with our partners at the Center for Inclusive Growth to reimagine measurement and impact evaluation to be more adaptive, innovative, and forward-looking. Together, we shifted measurement from a compliance exercise into an innovation support service. We designed it to do two things: 1) enable innovators to adapt in real time, and 2) connect their learning to the broader ecosystem. In line with this, we encouraged innovators to participate in the insights process, co-create learning, and increase visibility of innovation.

We took familiar M&I processes (quarterly reports, check-ins, MEL plans) and repurposed them to be lighter, more adaptive, and more valuable to innovators. We also introduced new tools that offered rare visibility into how innovations evolve.

Measurement, Evaluation, and Learning (MEL) canvases: Starting from a founder-first perspective, we knew that our innovators were developing solutions that use rapidly evolving technologies, and our M&I tools needed to mirror that. Instead of static MEL plans, we co-created “working canvases” in Miro. Innovators updated these as their value propositions or business models changed. For them, it reduced reporting burden; for us, it provided a living snapshot of where each solution stood, what had shifted, and why. We could then identify support services, such as mentoring, access to experts, or strategic business introductions that accelerate our innovators’ work. 

Adaptation and insights trackers: In these simple tables, embedded in the canvases, founders logged a critical insight, its source, and the resulting action. This made space for reflection without adding heavy reporting requirements. For the M&I team, it created a record of how innovations adapt, which we could then analyse across the portfolio.

These trackers enabled us to identify distinct patterns in how ventures learn, pivot, and adapt. That insight allowed us to shape tailored support and helped investors identify early on which approaches were gaining traction.

As one founder put it:

We also positioned Impact Measurement and Management (IMM) as a way to connect innovators with the wider ecosystem—from policymakers and funders to accelerators and peers. We sought to engage this innovation community with solutions, experiences, and perspectives that shape conversations, using evidence synthesized from our portfolio. Aggregating insights and evidence to close gaps has allowed us to forge connections between innovation community actors at events.

Learning questions as milestones: Every grant agreement included draft learning questions. Learning-centred milestones (e.g., research or test reports)  reinforced a culture of learning. Quarterly reports were designed to provide a regular point of reflection, focusing on adaptation and insights into users and strategy—the evidence and assessment needed to adapt and take next steps.

Mapped learning agendas: Founders charted their key research and testing opportunities on a timeline tied to those learning questions. This provided clarity on when the right insights would emerge—and allowed program teams or investors to engage at the right moments.

Making learning visible: Insights were aggregated into blogs, reports, events, and demonstrations. We transformed raw learning into sector-facing outputs, giving founders visibility, shaping investor narratives, and feeding evidence back into the ecosystem. 

In the Strive EU midterm evaluation, founders rated profiling, endorsements, and visibility (through events, social media, and press) as pivotal innovation support services. M&I, in collaboration with the Insights team, recorded and transformed innovation activities and insights into market intelligence and evidence for the wider innovation community discourse, including sector reports, co-created blogs, position papers, demonstrations, events, and workshops.

A critical outcome of these sector engagement activities was the growth of a learning community centered around the founders. Mapping introductions and new connections, as well as the nature of these interactions, was crucial to tracking the growing network. This exercise enabled the program to learn about the value of different types of connections, focusing specifically on innovation and sustainability, and identify relevant audiences throughout the program. This shifted our lens from long-term outcomes, such as “follow-on investment secured,” to the enabling infrastructure —relationships, networks, and visibility — that make those outcomes possible.

From Strive EU, four clear lessons for innovation measurement emerge:

Caribou’s approach is part of a growing movement to rethink how we measure innovation. We use experimental learning to design and test M&I frameworks, and we learn alongside others in the field—such as UNICEF’s Office of Innovation and their MEL for Innovation toolbox, and UNDP’s MEL Sandbox. These initiatives are pushing our sector to treat measurement as a dynamic tool for learning and system change.

The innovation landscape is constantly evolving. Robust, learning-oriented measurement isn’t a “nice-to-have”—it’s a competitive differentiator that directly impacts portfolio performance.

So the question for everyone in the innovation ecosystem is this: Does your organization treat measurement as accountability and compliance, or as an innovation catalyst?

Because high-quality, founder-focused, adaptive measurement isn’t about proving impact later,  it’s about creating the conditions for impact to happen at all.