reflections on investigating >300 startup concepts at Simple Ventures 📈 in the last 18 months
at simple ventures, we take a hypothesis-driven approach to testing new concepts and innovations. it’s non-linear, but staying focused on structured learning rather than blind execution has built muscle and tribal knowledge.
we are learning when to go slow and when to go fast to increase expected value (and im learning to temper my own “need for speed” to stay focused).
1. start with a clear hypothesis (and in our case, an international example to test in 🇨🇦)
every idea begins as an assumption about a problem, a customer, or a market. articulating the core assumptions upfront forces first principles thinking, and ensures we focus on the riskiest hypotheses.
2. directly test customer value propositions and ideal client personas to cut through noise
our first step is validating demand-side hypotheses in a “building block” manner. for example, in regulated industries like fintech or healthcare, we test whether customers see enough value to engage at all—before diving into operational or regulatory complexity.
3. design targeted experiments and stage-gate when to go deep & when to cut
validation isn’t about proving you’re right—it’s about learning quickly and proving you’re less wrong than yesterday. for one idea in the “home electrification” space, we ran a 3-day test with a landing page, search ads, and a survey to gauge (non)-interest, saving weeks of wasted effort on a low ev idea.
4. constantly interrogate the business model with new evidence (and points of view)
after validating early demand signals through tests or discovery, we deep dive into the “business model” (literally a spreadsheet), cell by cell, to blow out the riskiest assumptions—whether that’s margins, pricing, or client acquisition costs. we all have blind spots, so it’s helpful to get domain expertise and other eyes on our #’s.
5. kill ideas early
most concepts won’t work, and that’s a feature, not a bug, of a studio. tests are designed to expose flaws so we can pivot or move on. the learning curve is steep, and occasionally we’ll have false positives or false negatives. that’s okay—progress over perfection 😇. get comfortable with discomfort.
6. local market knowledge matters
what works in other markets doesn’t always work in canada. for example, industry nuances and customer behavior around willingness to pay can make or break an idea. reality > our hypothesis.
7. venture studio diligence ≠ vc diligence
the beauty of operating as a venture studio is we get a first hand view on how a company actually performs in market. there’s a sort of reverse-information assymetry compared to traditional venture, in that we learn what it takes to actually build and *operate* the startup.
building something new is always non-linear. but by starting with clear hypotheses and structured experiments, we can de-risk ideas systematically and “stack the odds”.
learning every day. 🙏