Building Smarter Data Practices in Entrepreneurship Support Ecosystems: How Entrepreneurs, Investors and Other Stakeholders Can Drive Systemic Change

Entrepreneurship support ecosystems are made up of a diverse range of actors, including incubators, accelerators and venture builders (broadly classified as entrepreneur support organizations or ESOs); impact investors; and development finance institutions. These support organizations play a vital role in providing entrepreneurs with access to capital, mentorship, networks and capacity-building services that are often otherwise unavailable.

Policymakers also play an important role in these ecosystems: Along with developing appropriate regulations, they work to shape the enabling environment these actors operate within by allocating resources and incentives, building infrastructure and access, shaping education and workforce development, and ensuring inclusion and equity. As entrepreneurship is increasingly recognized as a driver of job creation, innovation and inclusive economic growth, strengthening entrepreneurship support ecosystems has become a growing priority within the innovation ecosystems in emerging markets.

However, monitoring, evaluation and learning remains a persistent challenge for these ecosystems, due in part to a lack of data sharing. The various entrepreneurial stakeholders — from entrepreneurs and ESOs to investors and other funders — do collect data, related to their business operations, their impact or both. But it typically remains siloed, non-standardized and underutilized, limiting both shared learning and effective impact measurement. And while detailed data is often shared within established partnerships, these insights are rarely distributed more widely to benefit the overall ecosystem. Yet enabling the open exchange of relevant information between entrepreneurs, ESOs and funders could support more informed decisions, improve services and increase their combined impact.

Below, we’ll explore the reasons various stakeholders in the entrepreneurship support ecosystem collect data, the reasons this data remains fragmented and underutilized, and the ways the ecosystem can better collect and use data. We’ll also highlight an opportunity to share your thoughts on these topics, through an upcoming webinar we’re co-hosting with ANDE on September 4, 12:00 pm – 1:30 pm EAT.

The Value of Data Collection to Entrepreneurship Support Ecosystems

As a first step, it is critical to understand the underlying drivers and motivators among different ecosystem stakeholders to collect data in the first place. While entrepreneurs, ESOs, investors, funders and policymakers often have multiple motivations, identifying each stakeholder’s primary reason for data collection can help uncover common ground and serve as a foundation for better alignment, coordination and ultimately, stronger outcomes across the ecosystem.

The table below outlines the core value of data collection to key ecosystem stakeholders, including entrepreneurs and their investors, ESOs and their funders, and policymakers:

What’s Preventing Open Data Sharing Among Entrepreneurship Support Stakeholders?

As underscored in USAID’s 2024 “Unlocking Africa’s Health Innovation Potential” report, fragmented data collection practices and insufficient transparency are key reasons for the lack of data sharing among the different stakeholders in entrepreneurship support ecosystems. Overcoming these barriers requires building trust, aligning incentives and fostering stronger collaboration to enable continuous, open and meaningful data exchange. It also requires a deeper understanding of the specific obstacles and concerns that prevent different stakeholders from gathering and sharing data. Below, we’ll discuss how some of those key challenges affect different sector stakeholders.

Challenge 1: Inconsistent or Low-Quality Data Collection

• For entrepreneurs, this challenge is driven by a lack of capacity, funds or tools to collect data; limited bandwidth to engage in data collection; and unclear benefits of data sharing.
• ESOs are limited by fragmented or siloed data systems, reliance on self-reported data from startups, and a lack of internal monitoring and evaluation expertise and capacity within their teams.
• Investors and other funders face difficulties in benchmarking the performance of entrepreneurs within their portfolio due to inconsistent data availability.
• Policymakers face a lack of access to reliable, disaggregated data from ESOs or startups, and have limited willingness to engage with ESOs and other private sector players to inform their decision making.

Challenge 2: Lack of Standardized Indicators and Metrics

• Entrepreneurs tend to focus on output-level metrics and traditional scale metrics (revenue, funding, etc.), and they often have limited resources or motivation to track impact/ESG metrics.
• ESOs adopt a programmatic approach to impact measurement with different indicators for different projects. This makes it difficult to track performance across cohorts.
• Investors and funders find it hard to compare impact across ventures, and often struggle to align with different limited partner mandates.
• Policymakers find it difficult to evaluate the effectiveness of ecosystem policies based on varying datasets.

Challenge 3: Misaligned Incentives for Data Sharing and Use

• Entrepreneurs lack trust in ESOs and have an inherent fear of data misuse. There are no clear incentives (besides mandates) that drive them to share critical data with ESOs and investors during and beyond the engagement.
• ESOs have no incentive to share failures, and often don’t consider data as a strategic lever for growth.
• Investors struggle to align the data their portfolio companies provide with the reporting expectations of their different limited partners, and often hesitate to fund data systems and initiatives aimed at strengthening the broader ecosystem.
• With limited communication with the entrepreneurial ecosystem, policymakers develop policies without sufficient real-time data.

Challenge 4: Poor Feedback Loops and Use of Data for Learning

• Entrepreneurs’ and ESOs’ impact data collection efforts are typically donor-driven, with limited use for program enhancements and adaptive learning opportunities.
• The existing ecosystem has limited structures for entrepreneurs, ESOs and investors to share real-time policy feedback with policymakers.

Challenge 5: Lack of Data Privacy and Varying Ethical Considerations

• Entrepreneurs lack insights into how their data will be stored or shared by investors, ESOs and funders.
• ESOs lack robust data governance systems and frameworks due to limited resources and conflicting priorities.
• Many countries lack clear policies and data governance regulations to balance data privacy and use in a meaningful manner.

How Entrepreneurship Support Ecosystems Can Better Collect and Use Data

One way to conceptualize the challenges related to stakeholder data collection is by using the 4-box framing method, a strategic tool designed to organize and communicate complex ideas in a clear, comparative and compelling way. This method is particularly useful for surfacing insights, informing decisions, and aligning stakeholders around shared priorities or options.

In this context, the 4-box framing method helps deepen understanding of the goals, perspectives, needs and drivers of different stakeholders within the entrepreneurship support ecosystem, particularly as they relate to data collection and use. Using this tool, we examined the topic of data fragmentation across four key dimensions:

• Motivation: Why does the stakeholder want access to enterprise data? What are their underlying incentives or objectives?
• Expertise: What types of knowledge are required to effectively use this data? From what sources is this knowledge derived?
• Legitimacy: What values underpin the system? Whose perspectives are prioritized or seen as credible?
• Control: Who currently has the authority to make decisions about data collection, sharing and use? What would an ideal distribution of control look like?

By surfacing the norms and power dynamics embedded in each of these dimensions, the 4-box framing method provides a clearer picture of who is best positioned to implement meaningful changes to reduce data fragmentation across the ecosystem.

For example, in Africa’s entrepreneurship support ecosystem as it currently operates, investors’ and ESOs’ control over an enterprise’s access to funding gives them the upper hand in asking for data from entrepreneurs — a request that might go unanswered if it comes from other stakeholders, given the time and resources that data collection requires. Given this power dynamic, in the case of investors, an ideal approach might be to give entrepreneurs decision-making power over what data their company collects and shares, with any data requests that go beyond that paid for by the investor (even if they have already provided capital to these entrepreneurs). For ESOs, an ideal approach might involve working with funders to jointly create the frameworks and indicators entrepreneurs will be asked to measure, thereby defining how success looks from each of these stakeholders’ perspectives. These systems would support real-time learning and flexibility while still meeting accountability needs — and offering mutual respect for localized insights and adaptive strategies.

Other Stakeholders’ Perspectives on the Data Fragmentation Challenge

To expand our knowledge of the data fragmentation challenge by obtaining other stakeholders’ perspectives, we presented the 4-box framing for each stakeholder at the ANDE Metrics Conference in Nairobi in May of this year. The session audience was composed of ESOs (54%), entrepreneurs (12%), investors (4%) and other funders (4%), with the remaining 26% consisting of other stakeholders like evaluators, academics, etc. There were no policymakers in the room.

During the session we explored why data collection, analysis and sharing gaps exist, and asked the audience to share their thoughts on the obstacles they’ve faced. Key challenges raised by participants (based on mentimeter poll results) include:

• Exhaustion and fatigue among entrepreneurs from constant reporting;
• Struggles with aggregating and standardizing data among ESOs and investors, due to the range of monitoring, evaluation and learning practices and capabilities among the businesses and organizations they support;
• Difficulties building trust between ecosystem stakeholders to support data transparency and sharing;
• Challenges related to incentivizing customers to participate in data collection and sharing processes, and to capturing accurate data;
• A lack of dedicated impact measurement talent within the organization due to budget limitations.

We also discussed several underlying norms and tensions during the session. For example, entrepreneurs may avoid rigorous data collection to shield themselves from hard truths, or they might view operational data as proprietary. Many consider additional data collection efforts that go beyond what the company is already collecting for its own purposes to be outside their scope, and expect to be compensated for them. Audience members reiterated the importance of establishing trusting relationships between stakeholders when sharing data, and noted that project cycles of six to 12 months do not allow enough time to create this trust.

Despite these issues, we left the session feeling optimistic, as we observed that some attendees have challenged the status quo and found common ground with other ecosystem stakeholders due to having time and space for multi-stakeholder discussion. This kind of engagement is the first step toward systemic change, and a key part of building an ecosystem that supports smarter, more inclusive data practices.

We’re now entering a deeper research phase, and we invite your input. You can share your views by attending a webinar we are co-hosting with ANDE on September 4, 12:00 pm – 1:30 pm EAT. We will capture and incorporate additional perspectives from this discussion into our working document, so your insights will help us shape our next phase. Based on this combined input, we will move into the advocacy stage of ecosystem building, highlighting solutions to address data fragmentation within the entrepreneurial ecosystem.

NOTE: This article is based on a joint conference session organized by Villgro Africa, Swisscontact Kosovo and WDI. We would like to acknowledge the Swisscontact Team, Blerina Batusha Xërxa and Elion Gerguri, along with Rajat Chabba, WDI’s Senior Director of Innovation and Partnerships, for their valuable contributions.

Heather Esper is Director of Performance Measurement and Impact at the William Davidson Institute at the University of Michigan (WDI); Keith Obade is a Data Analyst and Moses Waweru is a Senior Program Manager at Villgro Africa.

Photo credit: Yan Krukau