What does success look like?
News from the Funding Innovation Lab: October 9, 2024, Edition 16
There are two kinds of success for the Funding Innovation Lab: success at the individual sprint level and success across a portfolio of experiment results. This week, I want to talk about the success of an individual sprint or experiment.
One of the challenges of developing data-driven recommendations for the venture industry is that each experiment is run with such small sample sizes, it is hard to imagine achieving statistical significance within a single sprint. For example, in an example I previously shared of a behavioral economics experiment conducted within team leadership dynamics, the experiment included 1,000 teams comprised of 7,000 individuals within a single company. In the venture funding and startup industry, sample sizes like that are unlikely.
In lieu of running experiments with large sample sizes, we are taking a tiny, fast experiment approach. We want to run these experiments in real-world settings, embedded in the typical events and activities already happening in the venture funding space.
Success, in these cases, looks like promising early results that we can build on over time.
In a recent meeting with one of our sprint teams, we discussed three possible outcomes for the experiment we ran:
Option 1- Promising Results: The intervention is promising, and we build a recommendation to share with the Funding Innovation Lab community.
Option 2 - Inconclusive Results: The intervention has inconclusive results, and we suggest a second sprint design based on our current learnings.
Option 3 - Disappointing Results: We decide the intervention perhaps had an opposite or negative effect, and we report on any conclusions we might draw from the experience.
It is exciting to me that we are developing and running experiments that could legitimately fall into any of these options. We want to see real, impactful results, and are willing to test ideas that might “fail” during the experiment process.
This is why I’m so excited for our Sprint Showcase event on October 30th. At this event, we’ll be sharing the results from these first two sprints - the potential successes or failures. We’re still deep in the work of facilitating the experiments and analyzing the results, so even I don’t know what those results will be yet! I’d love for you to join us in exploring this process, learning about our early results, and helping us brainstorm and craft future sprints for next year.
2024 Sprint Progress Update
The Funding Innovation Lab is live and actively working on experiments now! We will be keeping you updated on our progress with this weekly Progress Update section.
Phase 1: Design the Sprints for 2024 (July-August)
July 25: We announced the focus areas for this year’s two sprints at our Kickoff event
August 6: We finalized the sprint design teams and scheduled the meetings where these teams will determine what/how/when we will run these experiments
August 21: One experiment is fully designed and in motion. The second is partially designed, with some logistics around how it will get executed still to be determined.
Phase 2: Facilitate the Sprints (September)
Sprint 1 complete. Data has been gathered and the Sprint team has met to debrief, analyze the results, and propose next steps.
Sprint 2 is in motion. Details to be shared later!
Phase 3: Open source the Sprint Results (October)
Register for our Launch Party and Sprint Showcase! —> register here to join us
October 30th in Cambridge MA 12:30pm-5pm
The Funding Innovation Lab is a non-profit program, founded by LabCentral and led by Beth McKeon, with a mission to increase funding inclusion, access, and opportunity for women and BIPOC founders in the life sciences.
The Funding Innovation Lab convenes and supports innovators from across VC, universities, and entrepreneurial support organizations as they run rapid design sprints to solve the persistent systemic barriers and bias in the fundraising and capital deployment process. The Funding Innovation Lab has an open-source policy, sharing the wins and fails from these experiments here on Substack and with its community of practitioners with the goal to see widespread adoption and replication of emerging best practices in this field.