“It doesn’t matter how good your engineering team is if they are not given something worthwhile to build.”
— Marty Cagan
Opportunity cost has two key components:
The expense of building the wrong thing is easy to pinpoint: you paid x engineers, y designers, and z managers to spend h total hours on the not-right product. The expense of that time and effort is hundreds of hours and however many thousands of dollars it correlates to.
The cost of not building the right thing is less precise. Most startups have severe money, time, and resource constraints. If you spend 6+ months building the wrong thing, it’s possible you burn through most of your initial runway, without gaining traction or profitability in the process. You’re left with little money and fewer reasons for VCs to re-open their checkbooks. The cost is your chance at success and maybe even your startup.
That may seem like an extreme example, but it’s not far from reality. CBInsights analyzed 101 post-mortems and found 42% of startups fail because there’s no market need. Autopsy analyzed 300 failed startups and found 11.1% failed because no market need. Either way you slice it, that’s a lot of startups building the wrong thing and dying because of it.
Opportunity Cost: the expense of building the wrong thing, plus the chances, advantages, or momentum you lose by not building the right thing
And while the impact may be less severe at established companies with fewer constraints—the success or failure of an individual product rarely sinks an enterprise—it’s still pernicious. If you go through multiple cycles of not shipping value to customers or the company, you weaken team morale, lose money, and create openings for smaller, more customer-driven companies to lap you.
Of course, no one sets out to build the wrong thing, rack up technical and financial debt, or sink their startup. No one wants to build a flop.
The first mistake is placing a bad bet.
Founders set out to build something awesome. But then things get messy and they make three big mistakes:
The first mistake is placing a bad bet (or at the very least, an uninformed one). The founder puts weeks, hours, and resources on the line, praying a problem or solution is valuable to customers and the business.
The second and third mistakes increase the bet with no evidence of return. Usually this looks like adding complexity and extending development time, which compounds opportunity cost and founder fear. And past a certain point, it’s difficult to face the reality that your product is all sunk cost.
All of which is why Basecamp makes constrained bets for each product cycle. As they describe in Shape Up:
“...a smart bet has a cap on the downside. If we bet six weeks on something, the most we can lose is six weeks. We don’t allow ourselves to get into a situation where we’re spending multiples of the original estimate for something that isn’t worth that price.”
But reducing opportunity cost isn’t just about constraining your bet—it’s about making a smart bet to begin with.
Martin Christensen, a UX researcher and agile coach, observed, “You can build a product in the right way, but if it is not the right product (and it rarely is, we as humans have too many biases), that is just colossal waste.”
Before you even worrying about constraining your bet, you need to worry about making a smart one.
...reducing opportunity cost isn’t just about constraining your bet—it’s about making a smart bet to begin with.
One of the best ways to do this is to rearrange the Lean Startup cycle. Instead of Build → Measure → Learn, you want to Learn → Build → Measure.
The origin of FYI, a document organization service, is a good example of this adjusted cycle at work.
To create FYI, Hiten Shah and his co-founder Marie Prokopets started learning. They used an early-access survey to uncover qualitative customer insight: the number one problem their prospective customers face is finding documents across different apps.
This insight sparked Shah and Prokopet’s minimum viable product (MVP), which their team built in 5 days. Shah explains, “We decided to build an MVP with the goal of learning as much as possible about how people interact with document tools.” The MVP delivered additional insights, which they leveraged to build the current product.
Through multiple methods of learning, Shah and Prokopets de-risked the opportunity cost of building the full-fledged version of FYI. And when it came time to launch FYI, Shah and Prokopets didn’t cross their fingers and hope they were making a smart bet—they had data-backed confidence it was the right move.
To mitigate your own opportunity costs, you need to stop thinking of your startup as a feature factory and start turning it into a learning machine. Customer-driven discovery is your toolkit for building that machine.
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