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Apr 10 2014

You Can’t Build Culture

Culture: the word comes directly from the Latin cultura, for ‘growing, cultivation’. So why do we insist on talking about designing or building company culture as if it were an architectural achievement?

You can’t build culture, but you can grow it. The social expression of culture holds well to the analogy of growing plants. There are some things you can do to help it along, and you can have a good deal of influence on the direction of a culture, as long as you recognize that the culture itself will grow, change, or die, whether you want it to or not.

And it’s a lot easier to grow a culture from scratch than to change an existing one to fit your vision.

When you’re growing a culture from scratch, you can use a scaffolding, like core values, to act as a trellis for your growing culture. With careful cultivation, your culture can thrive, while resembling something of the vision you set out with.

When you’re changing culture, think of it as taking a fully grown plant and shaping it, slowly, into your vision of the culture. You change an existing culture by removing elements that don’t belong, and training the ones that are close to fit.

It’s less like growing climbing vines on an arbor of your design, and more like training bonsai by wiring and pruning.

You can’t just set out a trellis and expect a tree to climb it. You have to prune, trim, and tie branches with wire to encourage them to grow in the direction of your vision.

Mar 24 2014

Creative Doubt and the Money Function

A friend of mine shared a talk by Jack Conte, of Pomplamoose at XOXO with me (thanks, Harrison!) and I was struck by how much of his talk about being a content creator/entrepreneur is applicable to entrepreneurship more broadly.

Creative Doubt

Jack talks about the challenge of putting out content, and how when you wait longer, you feel the need to put out better content to justify the wait. The self-editor prevents us from putting out work that might not be perfect, and it becomes a vicious cycle.

Many product startups have the same problem. We don’t want to launch until it’s ready, but we can always come up with a reason that it’s not ready yet.

The Money Function

Jack also talked about what comes after creating good work. In order to be able to keep making music (and music videos), you have to solve for the function f:

f(music)= money

In other words, what function or system takes music as an input and returns money. It used to be CDs, then it was YouTube, now maybe it’s touring. But the interesting part for non-musician entrepreneurs comes when we look at it more broadly:

f(creative work) = money

And yes, that includes:

f(product) = money

In the lean startup community, we talk a lot about market risk – the risk of building something that no one wants – but Jack Conte’s distillation of that concept to a simple formula is an elegant framing of the problem.

Solving this formula is half the job. Creating great works of art – or building great products – is the other half, not the whole job. Without both halves, you don’t get to keep doing the work.

It’s not a problem if you want to do something once, but if you want to keep doing it, you have to figure out how to make enough money to keep it (and you) going.

Mar 07 2014

Your Brain is not as Smart as it Thinks

Why should you care about ego risk? Because risks to innovation and new ventures follow the Pareto principle: only 20% of the risks a startup talks or thinks about are ego risks, but ego risks account for 80% of the challenges they face.

I’ve talked before about the 3 types of risk in new ventures. While tech and market risk get all the fanfare, ego risk is at the heart of most problems startups encounter. If you don’t manage market risk, you will build the wrong thing. If you don’t manage tech risk, you will fail at building that thing. If you don’t manage ego risk, you will fail to build anything at all.

Here’s the kicker: Most startups don’t die because they built the wrong thing. They die because they didn’t build anything.

Ego risk encompasses the whole set of challenges of managing ourselves, our teams, and our companies. As a leader in an uncertain venture, there’s no map to follow. With no clear yardstick for gauging success (except at certain rare intervals), managing your personal psychology and the mental health of your team becomes a crucial task, not just to prevent the productivity drop-off at the half-life of enthusiasm, but to avoid falling prey to cognitive biases and misapplied mental heuristics.

We’re all vulnerable to cognitive biases: traps in our thinking that lead us astray. Here are a few to watch out for:

Survivorship Bias – We focus on the startups that made it, and ignore the ones that disappeared before we heard about them. Then we draw conclusions about the whole from that small subset. For example, the startups that we’ve heard of mostly failed because they didn’t build the right thing. We never even hear about the vastly greater number of startups that built nothing. So we erroneously conclude that most startups fail because they build the wrong thing.

Overconfidence Effect – We estimate that we’re right more often than we actually are. We are often 99% certain that our estimates are correct, only to find that 40% of the time, they are wrong. Humans are notoriously bad at predicting the future, and it wreaks havoc on business plans. Entrepreneurs may plan and act as if the future is clear and make large bets when it might be more prudent to start with a smaller bet and wait for confirmation.

Sunk Cost Fallacy – People tend to throw good money after bad when in fact, it doesn’t matter how much we’ve spent: the only thing that should matter is the payoff from the investment we’re considering making – and the opportunity cost of not doing something else with that investment. But if we invest in a plan that doesn’t work out, we are more likely to double down on trying to make it work than to ignore our losses and invest in the best current option.

Availability Heuristic – When something is easy to recall, we think it must be more likely or more common than something that is harder to recall. If the last 2 people you talked to like the color green, you will think that most people seem to like the color green. This can lead us to jump to conclusions about our product or our market, instead of objectively evaluating the reality of people’s preferences and needs.

Confirmation Bias – We see what we want to see more often than it’s actually there. Especially when there is some level of ambiguity, our brains will interpret data to be consistent with our hypothesis, rather than challenge it. This can be dangerous when it causes us to think we have confirmed a theory, and proceed to act on it, when we’ve actually gained no further validation.

Bandwagon Effect – People tend to believe what other people believe. If most of your team believes something to be true, the rest of the team may come to believe the same, regardless of evidence to the contrary. The absence of dissenting opinions can make for a dangerous environment where the whole team moves in one direction without examining whether it is in fact the right strategy.

Halo Effect – We assume that people who have one positive quality must have others as well. One result of the halo effect is that we think that attractive people are correct more often than people who are not conventionally attractive. Just because a founder is good at code doesn’t mean they understand selling – and vice versa: yet another reason to set measurable goals and test against them early and often.

Hindsight Bias – We forget how wrong we were, and underestimate the importance of those first experiments. This is why it is so important to document hypotheses and minimum success criteria.

Dependence of self-concept on success of the business – When the business is failing, it’s common for the founder to feel like they are personally a failure. The countless entrepreneurs who have talked about this usually begin by referencing many of their friends and colleagues who suffer from the same thing, but don’t talk about it. So it’s a pretty reasonable bet that this is universal. Don’t feel bad.

Stay tuned for some tactics that can help you manage ego risk.

Mar 04 2014

How to Set your Minimum Success Criteria

When you’re running a lean experiment, one of the key decision points is setting your minimum success criteria: the breakpoint at which you consider the experiment to have validated or invalidated your hypothesis.

Make sure you explicitly set the criteria before you run the experiment, and make a record of it. It’s too easy to fudge the numbers later and rob yourself of any valuable insight.

There are two methods I recommend for determining the minimum success criteria for your experiments.

The ‘business school’ method of setting minimum success criteria is to put together your pro forma spreadsheet with projections of what numbers you need to hit for the business to be financially viable and then reverse engineer the conversion rate you need to hit to make those numbers.

The approach that I find tends to work better, particularly for companies that are in the early stages, is to ask your team. What conversion rate would you have to see for you and your team to still be excited about the opportunity? This is the half-life of enthusiasm approach (H/T Frank DiMeo for the terminology).

half-life of enthusiasm

the time taken for your team’s enthusiasm to drop to half of its initial level

In early-stage companies (we’re talking pre-product/market fit), funding is tight, but usually not the limiting factor. Enthusiasm and the will to continue is usually in much shorter supply. So, optimize for your scarcest resource. If it’s truly funding, make the numbers work. If it’s enthusiasm, make sure the problem opportunity still excites the team.

Feb 12 2014