Analytics Driven Strategies
Kiva is a nonprofit founded in 2005 with a mission to connect underbanked entrepreneurs with microloans. It achieves this through a technology platform that crowdsources funds for distribution. In 2011, Kiva launched Kiva Zip (now Kiva U.S.), a startup within the organization that was specifically focused on entrepreneurs in the U.S. and Kenya.
I led several analytics-driven strategy initiatives during my nonprofit fellowship from March 2015 through September 2015 as the Strategy & Analytics Fellow.
The goal / scope of the project had a few areas of focus:
- Model lending behavior and developed strategies to improve their engagement with Kiva
- Recruit new borrowers through digital and in person marketing and communications
- In Nairobi, educate potential borrowers on the ground, evaluate Kiva Zip’s holistic impact, and analyzed borrower delinquency
My experience with social entrepreneurship at Kiva gave me a new perspective on effective organizations and my own working styleSushil Raja, Consultant, Oliver Wyman
My experience with social entrepreneurship at Kiva gave me a new perspective on effective organizations and my own working style:
- The double bottom line: Kiva’s mission is evident in every fiber of the organization. Working at a company dually focused on profit and impact was intrinsically motivating. It reiterated that talented people are not only driven by profit, but by the opportunity to make an impact.
- The lean start up: The Kiva Zip team functioned like a start-up. They embraced Lean Startup principles, rooted in: moving quickly, failing fast, and iterating. Transplanting that agile methodology back in the consulting world has been transformative.
- Driving change: At Kiva, the impact of most projects could be tracked in real-time. It was a good reminder how efforts affected people around the world, similar to the projects that we engage in at Oliver Wyman.
Overall the nonprofit fellowship experience was a great opportunity to reflect on what I’ve learned in consulting and apply it in a vastly different context.