On Risk and Imagining the Future

One of the most important aspects of the Silicon Valley ethos is the emphasis on learning in a startup. In particular, we often see the promotion of learning in the name of risk reduction — you try things, learn, and iterate so you can solve your core risks. I love the notion, introduced by Phin Barnes of First Round, of learning per dollar spent that suggests the most important metric as you scale is your capital efficiency in learning and derisking a business. However, I’ve been thinking more about the notion of risk in venture-backed startups (aside: this post addresses only venture-backed startups) and I’ve come to worry that the startup ecosystem doesn’t have a healthy relationship with risk. The ecosystem has seemingly forgotten that taking on large risks is actually a core competitive advantage startups have. While incumbents can take on greater financial risk, they tend to shy away from other kinds of risk such as market risk, scalability risk, business model risk, etc. Many well-known pieces of startup advice like starting in a small niche (market risk), “do things that don’t scale,” (scalability risk) or “look for products that seem like toys,” (monetization risk) are just specific incidences of advising a startup that it’s OK to take on risk. While derisking per dollar is certainly a metric to shoot for, sometimes it’s not possible and we need to be ok with ambitious shots that have sustained risk over long periods of time.

How do you win as a startup?

Startups have a couple of core advantages: constraints, velocity, and agility among them. Constraints on your strategy end up helping you build a differentiated company, product, or solution. For example, not having a network of stores forced Netflix to bet on the alternative content delivery models that beat Blockbuster. Facebook initially targeted college students, which was a user segmentation constraint that helped them cold start (and grow) their network. Velocity has helped many small companies win (e.g., Uber, Amazon, etc.). Velocity, which I consider to mean the speed at which a startup can move in a given direction, is different than agility, which I consider to be how quickly a startup can change directions. Being agile doesn’t necessarily mean pivoting, just reacting to new information in some capacity. Agility is a huge advantage startups have over big companies which typically require buy-in from multiple people to act on new information. While constraints, velocity, and agility are frequently discussed, they aren’t the only advantages a startup has.

On top of these, I would argue that calculated risk appetite needs to be your biggest advantage. From a strategic perspective, unless you have defensibility that accrues rapidly, moving fast as your only advantage is a recipe for serious competitive pressures. This is something that both investors and startup founders need to remember and keep in mind.

In the startup world, all our pattern matching efforts are biases. Exceptions are the rule.

So what does this mean practically? As a startup, you should have explicitly stated and carefully selected risks. Startups are risky business by nature and your strategy should embrace that. Risk allows you to do things that are objectively foolish and thus nonsensical for other players. That is exactly where you can win. Note that in some cases, such as with Netflix, risks can come from your constraints, but that’s not always true. Airbnb was built on the hypothesis that people would rent out their bedrooms. SpaceX decided to build a rocket from scratch. Snapchat built a company around college students sexting. By any measure, these are objectively crazy decisions that worked. Risks can be in your product, market, business model, or technology approach but they can also be baked far deeper into the organization (who you hire, how you hire, your culture, etc.). As a great example, GitLab built a completely remote business from the start and it’s a big reason they’ve been so capital efficient. In the startup world, all our pattern matching efforts are biases. Exceptions are the rule. Never forget this.

from Hacker News https://ift.tt/3B8NkNL