Greetings from VentureWell! We are Stefanie Leite and Olivia Noel, serving as evaluators on the Data Intelligence team. VentureWell is a national nonprofit headquartered in Hadley, Massachusetts, that specializes in funding, training, and cultivating a pipeline of science and technology inventors, innovators, and entrepreneurs. Together with our partners, we are driven to solve the world’s biggest challenges and create positive social and environmental impact.
How often have you thought of a successful entrepreneur as lucky? The odds of getting their innovation into the hands of customers are not exactly in their favor. The path to commercialization is risky and uncertain, and they are often venturing into uncharted territory with unproven products, services, or markets–all under significant resource constraints. A groundbreaking innovation alone is not enough.
If you’re at all like us, you relish applying frameworks and methods to understand (and measure!) a complex system. You will appreciate knowing that methods exist to help an entrepreneur increase the odds, with at least a few that will sound familiar to you. Maybe you already apply these in another context.
One of these frameworks for early-stage startups was popularized by Eric Ries, in his book, The Lean Startup. As evaluators of such programs that both practice what they teach, here are a few things we learned about increasing the odds:
Articulate a value proposition. Behind every innovation is a belief system about the problem it will solve and why it will work. Like a theory of change, we pay attention to its underlying assumptions and are ready to adapt it to new information.
Conduct customer discovery. We interview people who would be our customers or end users. We ask them to describe their pain points, resisting the urge to discuss solutions until there is a clear view of the problem. Customer discovery should be ongoing to validate one’s learning, though at the beginning we might approach it as an evaluator would with a needs assessment. We learn and use their language.
Begin with a minimum viable product (MVP). Instead of pouring significant resources into the presumably perfect product, we create an MVP and iterate upon it based on feedback. Piloting smaller versions before rolling them out at scale helps minimize risk and allows for agile refinement before full implementation. In a similar build-measure-learn feedback loop, we might use a formative evaluation approach to a pilot program.
Map a business model canvas. This is a tool we use to detail how our innovation will work, which may vary by the type of customer. Inputs, activities, outputs, and outcomes are all defined here, calling to mind the humble logic model.
Seek product market fit. If an innovation is wanted, there will be sustainable demand for it. Should evidence suggest otherwise, we are ready to pivot. We recognize the non-linearity of growth.
Engage the innovation ecosystem. We improve the odds by engaging others with diverse backgrounds and expertise. We create opportunities by sharing knowledge, pooling resources, and collaborating with others. We create excitement around where our next relationship might lead.
To quote the Roman philosopher Seneca, “Luck is what happens when preparation meets opportunity.”
Rad Resources
- The Lean Startup: How today’s entrepreneurs use continuous innovation to create radically successful businesses by Eric Ries (Crown Currency, 2011)
- Talking to Humans: Success starts with understanding your customers by Giff Constable (Giff Constable, 2014)
Please check out our post tomorrow on effective data management in evaluation of I&E programs!
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