The lean start-up approach has become the mainstream in the entrepreneurship world. Even established companies such as Dropbox, Slack, GE have embraced it as a way to rapidly test and refine ideas for products or businesses. But is lean start-up all what is needed to form a strong start-up?
As for the lean start-up methodology, its effectiveness has been proved in many researches. The methodology allows start-ups to explore hypotheses and converge on ideas. Feature, teams who engaged with the method more intensely had more operational success (i.e., established a company and employed more people).
But there is a catch: The approach doesn’t work equally well for everyone. While educationally diverse teams – those whose members have different kinds of degrees (engineering, medicine, and so on) – embraced its experimental, learning-by-doing nature, adding people with business degrees to the mix had both positive and negative effects. MBAs tended to resist the method at first likely because their training emphasizes learning by thinking. Yet teams with MBA members who started using the components of the method (particularly customer interviews) were more likely to improve the teams’ business ideas. This suggests unex[ected benefits if we get MBAs to embrace the method in the first place. Several researches have studied the method and concluded tips for innovators to overcome the method’s limitations and make the most of it.
First, a quick primer: The lean approach was devised in the early 2000s. Its key features are formulating hypotheses about different aspects of the business and “getting out of the building” to probe each hypothesis by interviewing potential clients and consumers and quickly pushing testable prototypes to them. Using this method, companies can avoid devoting time and energy to ideas that won’t work in the real world, and instead emerge with a viable plan of attack.
Putting lean start-ups to the test
A research conducted by Harvard Business School measured 3 key dimensions of the lean approach: hypothesis formulation (the number of new assumptions teams developed about their business model), hypothesis probing (the number of interviews conducted about those assumptions), and idea convergence (the number of items teams either added to their business model because they had been proved or removed because they had been disapproved.)
The research shows that the lean star-up method does what it promises to do. There is a positive correlation between teams’ interviews of potential customers in a given week and their convergence on a particular idea in a given week and their convergence on a particular idea the next. In other words, the more interviews the teams conducted, the faster they settled on whether a business idea was worth pursuing – something advocates of the approach assume but which has not been empirically proven until now. Simply put, it pays off to leave the building and ask customers what they think of your idea.
What’s more, talking to customers appeared to create a useful feedback loop: While conducting interviews, teams got brand-new ideas that became new hypotheses. This may come as a surprise to innovators who’ve long been told that customers never provide brand new ideas. It turns out that they can and do.
One common criticism of lean start-ups is that the feedback loop never stops. As an innovator, you may exhaust your time and resources on testing hypotheses rather than building a business. The research found this is not true. There is a natural stopping mechanism baked into the method: Teams gradually settled their open questions about their business ideas.
Why team makeup matters
But all of these useful downstream effects of lean start-up rest on getting teams to propose and probe hypotheses in the first place. And teams with different educational backgrounds diverge most sharply on this. Teams with at least one member who held an MBA degree struggled relative to others and, as a result, formulated fewer hypotheses and converged more slowly on business ideas.
Why do MBA teams tend to struggle? One reason may be that traditional business school curriculum emphasizes learning by thinking – for instance, analyzing case studies – rather than learning by doing; as a result, MBA teams may believe that by thinking through a business model, they’ve already validated it, so no hypotheses are required. MBAs may feel reluctant to hypothesize and probe because they view themselves as business experts who know more than customers do.
How to make the most of lean start-up
So what does this all mean for aspiring innovators considering the lean approach? Here are 3 ways to make the most of it:
When it comes to developing hypotheses, focus on quality, not quantity. Teams who developed lots of hypotheses tended to investigate gewer of them. This may be triggered by the fact that it is much easier to probe a few clear thoughtful hypotheses than lots of vague, slapdash ones. To yield all the benefits of probing, lean teams should focus on developing a smaller number of hypotheses they really want to test.
If you’re an MBA, prepare to eat some humble pie. MBAs and lean start-ups aren’t necessarily a natural fit. But MBAs can find great success with this approach. So, if you’re a business school alum, prepare for some discomfort at first – but know your skills will give you a boost when it comes time to analyze the results of your probe.
Embrace diversity. Educationally diverse teams, according to studies, are more likely to take advantage of the lean start-up methodology. Homogenous teams (e.g., those made up of only engineers or only MBAs) may be overly optimistic about their initial ideas and less willing to probe them. That’s likely because a group of people with similar backgrounds may be prone to groupthink. But educationally diverse teams don’t have this problem. Thanks to members’ varied backgrounds, they are less susceptible to groupthink and have less attachment to initial beliefs, likely making them especially willing to embrace the experimental nature of the method and probe their ideas.
So if your innovation teams are made up mostly of people with similar backgrounds, you should broaden them. And if you’ve got an MBA on your team, know that it may take a little convincing to get them to develop and probe hypotheses – but that you’ll all benefit in the end.