From the MVP Conference 2015, held May 18th – 19th in Rosslyn, VA.
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.
One of the big challenges with doing innovation in any setting is that most people are afraid of failure, and when you’re afraid to fail, you don’t take the risks that are necessary to keep creating and innovating.
Most professionals have had the idea that “failure is bad”, “failure is not acceptable”, or “failure is final” drilled into them through 16 years of schooling by the time they enter the workforce. We take tests in school and only get one shot to get it right, which is not usually how it works in the real world.
Recognition of this disconnect has led to a sort of “counter-cultural movement” among entrepreneurs of celebrating failure. While I understand how we got here, I think it’s an over-correction. We’re trying to balance one extreme out with another.
The problem with celebrating failure is that, unless you’re learning something, it’s still just failure.
We need to stop celebrating failure indiscriminately, and instead celebrate the learning that can come out of failure (and sometimes out of other things). Failure might be a necessary cost, but it’s the learning that helps us improve our creations and make the next ones better.
“What we ran out of first, before ideas, before money, before time, was steam,” [Chetrit] writes. “We spent two years tirelessly working, putting all our time, faith and resources into Tixelated. And what we were getting in return was stress, worry, and emotional haywire.”
This is not a case, as ego risk often is, of cognitive biases tripping up the founding team, but a simple reality that starting a company is hard and our own psychological wellbeing sometimes takes priority over the success of the business. It’s rare to see such open and honest evaluation of the emotional challenges leading to the decision to shut down a business. Kudos, Philippe for being a leader in the conversation on ego risk. We look forward to watching what you do next.
Starting any new venture is risky. Before we can limit or manage the risk, we have to understand it.
Most startup (or new product) risk can be divided into three buckets:
- Tech Risk
- Market Risk
- Ego Risk
Tech risk is what entrepreneurs (or intrapreneurs, for those starting something within an existing structure) most often think about when starting a new venture. Can I build this thing? Is it scalable? Do I have enough servers? The irony is that, especially for consumer web startups, this risk is usually negligible. Most web startups aren’t doing anything that hasn’t been done before, unless it involves patentable algorithms. It may not be easy, but there’s high certainty that it can be done, given sufficient resources.
Market risk is the antithesis of the idea that “if you build it, they will come.” Do people have this problem? If we can deliver the solution, will people even want it? Can we reach the people who will buy this product? Do people believe that our solution is credible? Entrepreneurs should be thinking carefully about market risk.
The final type of risk facing any new venture is ego risk – and it’s probably the most important and the least discussed type of risk. Ego risk is the chance that an entrepreneur can’t get out of her or his own way, pay attention to the data, overcome cognitive biases, and avoid falling prey to a reality distortion field.
With so much risk, it’s a wonder any new venture survives (many of them don’t). But researchers and entrepreneurs have worked hard on each of these types of risks, and there are strategies for ameliorating each one.
Tech Risk + Agile
Tech risk is often mitigated with some implementation of Agile methodologies. I sat down with Agile expert Elliot Susel to ask him how entrepreneurs can get started with Agile. Listen to that interview here: See the Full Transcript.
Market Risk + Lean Startup
Minimizing market risk is the driving force behind much of the lean startup movement. By making a set of small bets in the form of lightweight experiments, entrepreneurs can validate market demand before investing in building a system to deliver a solution or product. Plus, talking to customers often helps entrepreneurs identify problems they had not originally imagined. Sometimes those new problems are more pressing for the customer, and lead to a new product with less market risk.
Ego Risk + ?
Ego risk is the final and most difficult hurdle. There’s no clear-cut answer to this challenge. Religions and philosophers have been focused on ego for millennia. But a meditation or mindfulness practice can be particularly useful in helping us step back from our impulsive reactions to external stimuli (e.g. data that challenges our preconceived notions, particularly if our self-worth is invested in being right, or in one particular self-image.)
Of course, even a zen-master-like separation from the ego doesn’t completely protect us from cognitive biases, nor does a higher IQ or more awareness of these effects. In fact, there is some evidence to suggest a correlation between higher IQ and higher susceptibility to cognitive biases. We don’t yet have any proven methods for overcoming biases, but the Wikipedia page on mitigation is very interesting reading, and a good starting point for learning more.