When I quit my job to start my own business advising startups and small businesses, I knew failure was possible. But in the 18 months prior, I had already validated the core assumptions that mattered: I could price my time at 250 dollars an hour, I could get in front of prospects and convert them into clients, and I could reliably deliver on what I sold. The uncertainty that remained was narrower. Would my current pipeline convert, how long would clients keep me on retainer, and could I eventually systematize the business, so it became something scalable rather than a string of consulting gigs? When the entire pipeline converted and it looked like I had an overnight success, it was simply the result of 18 months of hypothesis development, experimentation, and assumption validation that reduced the real risk of entrepreneurship.
This experience shaped the way I think about risk more broadly. Among my peer group of entrepreneurs, I consider myself to be a relatively conservative risk taker. While many people see any entrepreneurial journey as an indulgence in risky behavior, I have found that the most sustainable and dependable path to success is the path that is deliberately de-risked through information gathering, experimentation, and validation. So, when someone says, “But quitting your job to start a company is always a highly risky endeavor,” I disagree with the binary nature of that statement. Risk is not fixed. It can be mitigated through careful study, thoughtful experiments, and patience for validation.
Defining and Pricing Risk
Howard Marks offers the definition of risk that I find most helpful for startups and small businesses: risk means uncertainty about which outcome will occur and about the possibility of loss when the unfavorable ones do. Put simply, risk is what we face when we move forward without enough information, not unlike taking a step in a dark room before we know what is in front of us. By this definition, risk can be managed by increasing certainty of outcome or decreasing the possibility of loss, which is essentially the process of bringing more light to the path ahead.
Crucially, every entrepreneur or investor comes to a risk with different levels of information. My prediction about what OpenAI will do in the next six months is based on low information, while Sam Altman operates from a high information perspective. That asymmetry alone means we price the same risk differently. A Managing Director I once worked for captured this idea simply: “The best thing about the private markets is that I can trade on insider information.” The broader point is that more information reduces true uncertainty.
Finance gives us language for this. Beta represents the expected return for a given level of true uncertainty. Alpha is the additional return created when perceived uncertainty differs from true uncertainty. In public markets, where liquidity is high, Beta tends to be priced efficiently. In private markets, Beta is often mispriced because assumptions rely on limited information or common wisdom rather than validation. Entrepreneurship, especially the jump from zero to one, carries a societal risk premium due to the opportunity cost of a stable job, which only increases the likelihood that the market has overpriced the underlying risk.
When we uncover situations where risk appears high but is actually lower than perceived, Alpha becomes attainable through increasing certainty and reducing potential losses.
Underwriting Beta and Reducing Risk
Underwriting Beta means analyzing risk with the intention of increasing certainty. For small businesses, this often involves building explicit hypotheses and applying the scientific method to validate or invalidate them.
As a financial modeler, the first month with any client involves diving into structural assumptions to identify the levers that matter. A basic example might be: “We acquire customers for Y dollars each, they buy X dollars worth of product, and it costs 40 percent of X to deliver.” From there we can translate these assumptions into testable hypotheses:
It costs us 25 dollars to acquire each customer
Each customer buys an average of 100 dollars of product
It costs us 40 dollars to deliver this product
Instead of accepting these assumptions at face value, we can design small, low-cost experiments to test them.
Take the CAC assumption. Many entrepreneurs internalize an acquisition cost and only realize months later that it is far higher. Instead, we can research industry benchmarks, reference public companies, speak with advisors who have sold similar products, or use tools like Google Keywords and Google Trends to estimate relevant marketing costs. If that does not disprove the assumption, we can run advertisements under our brand or a fake door brand to test demand. If the product already exists, we can analyze real data. If it does not, pre-orders or funnel progression can give us useful signals.
If the assumption still holds, we can investigate second-order effects. CAC at ten customers is rarely the same as CAC at ten thousand customers. We can design experiments that help us understand how the assumption behaves at scale.
By validating hypotheses or narrowing their possible ranges, we reduce uncertainty and better understand our downside scenarios. This is the essence of de-risking a business. We are not eliminating uncertainty, but we are tightening the band of possible outcomes so that decisions come from information rather than assumption.
Taking the Big Swing
In the end, entrepreneurship and large internal investment do not need to be a blind leap. The founders who survive are not the ones who tolerate the most uncertainty but the ones who work systematically to shrink it. By treating assumptions as hypotheses, seeking information instead of relying on intuition, and running experiments that intentionally challenge our beliefs, we convert what looks like risk into something far more manageable. Most people overestimate the danger because they underestimate how much can be learned before taking the big swing. When we invest the time to underwrite our own Beta, we often find that opportunities are not inherently risky. They are simply unvalidated.
Entrepreneurship will always involve stepping into the unknown. Some founders sprint into the darkness and hope for the best. Others take the time to build a flashlight. In my experience, the ones who build the flashlight are the ones who make it through.
