Shortly after concluding her 10-year career with the U.S. Agency for International Development (USAID), diplomat and economist-turned-entrepreneur Lindsey Moore founded DevelopMetrics, a data science firm, to equip leaders in her field with better data to make more informed decisions.
This firm uses AI and predictive analytics to uncover statistical insights to achieve positive social development outcomes world-wide. While developing the algorithm behind these insights took years, it saves research teams countless hours by efficiently synthesizing thousands of evaluations and other data sources into curated dashboards to aid decision-making.
Through this process, the company aims to incentivize more informed policy and program decisions, level the playing field, and allow donors to fund projects based on hard evidence.
Moore is among 20 impressive tech founders awarded funding through the AccelerateHER Fund, a grant program sponsored by Tiger Global and administered through GEN’s Small Business Grants Program in partnership with Hello Alice. The program provides up to $50,000 to women entrepreneurs building breakthrough technologies or tech-enabled companies.
GEN spoke with Moore to learn how her company and its algorithm are changing the international development field.
*This interview has been edited for length and readability.
GEN: Let’s start with DevelopMetrics. What problem does it solve, and how?
Lindsey Moore: There needs to be a coherent evidence base from which people draw insights at a systems level. People have personal knowledge from their studies and experience, and there’s so much knowledge out there, but the sheer amount of information available is a challenge in itself.
We built Developmetrics out of this research at United Nations University. We developed a methodology and algorithm data training set that served as a foundation for the company’s machine learning algorithm. It enables the analysis of millions of documents and data sets.
It unlocks this evidence base of development data to enable decision-makers [government donors] to make better decisions.
GEN: You worked as a diplomat and for USAID before starting your company. How did those experiences influence your decision to startup?
Lindsey Moore: My experience at USAID allowed me to realize that the way to create this evidence base is not with universities and not with governments. It’s the mandate of a for-profit company because a company is not subject to five-year deadlines, projects ending or the funding challenges that universities and governments are.
Another insight I learned from working at USAID is that it’s not enough to provide the data. The data has to be used. From my personal experience working as a diplomat in USAID, I know how development practitioners use data, which is the real key. It’s not just about having the evidence or even curating the evidence. The hardest part is to go that last mile and get it in the hands of people when they need it.
GEN: How have you found the transition from employee to founder? What challenges have you had to overcome?
Lindsey Moore: As a diplomat, you’re given a framework and you hope it changes the world. In a startup, as a CEO, you are used to making the framework yourself, and the world has to change for your company to survive.
So quickly, I moved from one of the most risk-averse environments of diplomacy where I had to be very careful of everything I said because everything I said and did I was as a representative of the United States government. And then I moved into one of the riskiest environments, the startup world, where you feel like you’re building the plane while flying and just praying you don’t crash.
GEN: What has been your most memorable moment as a founder so far?
Lindsey Moore: My most memorable moment was sending out my first emails. Usually, at USAID, you’re giving money away, so people respond immediately. When you’re asking for money or selling something, you don’t get a quick email response.
The first ping in my email was from the director of Business Development at Mercy Corps, a large development organization nonprofit. He said ‘let’s give it a try’. That was my first realization that this would work. It turned into a supportive relationship with the development community.
GEN: Can you share an example of how the algorithm is applied to achieve social development objectives?
Lindsey Moore: I’m working with the Africa Bureau at USAID, and they want to know about their digital development programming over the past year in Africa — what have they done, their impact, and they want to ensure that malicious actors are not co-opting these investments for their own purposes.
So, we reviewed all the documents [using the machine learning algorithm] that USAID has in Africa. Each document is hundreds of pages long. Then, we extracted and normalized the critical text. We take the text most relevant to digital development out of the document. Then we can normalize it based on this data architecture we created with USAID and standardize it into a numeric database. This allows us to draw incredible insights out of millions of data points.
We mapped the constellation of outcomes and interventions that have historically made up USAID’s digital development landscape.
GEN: Can you share further success stories or anecdotes about the use of the algorithm in the international development sector?
Lindsey Moore: A long-standing challenge has been how we empower women economically in developing countries. We reviewed all academic articles, every project evaluation rewritten, and every data set for a client who is implementing a project in the Middle East. They wanted to empower women.
We found that training women and microfinance are the most common approaches. Still, these approaches historically have had a very low success rate in providing women with the economic empowerment they need to have control over the decisions they’re making in their lives.
We found that connecting women to markets has been most effective historically. It’s not that they need more skills. Instead, they need to engage with people willing to be in their network, support them and offer women the same business opportunities as men.
Now, the project is taking this innovative approach to helping women build networks and seeing an incredible rise in earnings for these women entrepreneurs. We’re currently growing and scaling their business.
GEN: You hire from the communities you serve, meaning many of your employees are from developing countries. How has that influenced your business?
Lindsey Moore: The core of our model is universality. We don’t want donors' outside influence on data. Our analysts and data scientists are from countries such as Sri Lanka, Nigeria, and Bangladesh. Since many of our staff are recipients of donor products, they have first-hand knowledge that helps us unbias our ideas and bring unparalleled technical skills and innovation.
GEN: What impact will the AccelerateHER grant have on you and your company? What will you do with the funding?
Lindsey Moore: The grant is transformational for us in investing in a technology platform that enables us to reach a wider group of people. For example, we can now offer our data to local organizations without having them contribute to the R&D costs. Allowing them to benefit from the data in their products aligns with our mission of increasing impact.
GEN: What’s next for you? For your company?
Lindsey Moore: We’re looking at Web3 technologies to enable local organizations to have a more significant role in the development process. We’re also looking into generative tech and what kind of applications that can have in the development field. Also, we’re continuing to collaborate with our partners, local and all the most prominent development organizations, to build and improve on this evidence base to reach the most people possible.
To learn more about Lindsey and Developmetrics, visit www.developmetrics.com.