Where do learning launches fit strategically? Companies should undertake a portfolio  of growth initiatives and manage that portfolio across business units based on  timelines designed to produce new sources of revenue, which can be scaled across a  large geographical area or customer base. The purpose of growth initiatives is to  create new S Curves of income to replace existing S Curves as their useful lives peak.  In order to do this, companies need to generate growth ideas and test them in a  disciplined manner to determine which ideas warrant investment.

Learning launches are a methodology for testing ideas to determine which qualify as  business opportunities. Because they should occur quickly and be low cost, learning  launches have also been described as “placing small bets fast.” Unfortunately, some  executives have interpreted that phrase as advocating the pursuit of small revenue  opportunities, which is not the case. Most good growth companies are looking for  growth opportunities to be scaled and result in needle-movers. “Small bets fast” is a  testing procedure, however, and not a strategy decision. A learning launch is a  business-world application of the scientific method; it is a way of thinking that relies  on generating and testing hypotheses. It starts with hypothesis-generating by asking  a what-if question, which allows you to identify a new possibility to act on. That  possibility is your hypothesis — basically an educated guess about something  you think is likely to be a good idea. That’s the creative part. Then to test your  hypothesis, you specify what scientists call the boundary conditions. In other words,  you ask: Under what conditions would that hypothesis, in fact, be a good idea? Or —  worded differently — what would need to be true in order for my idea to be a good  one? So, you bring to the surface the assumptions that lie under your hypothesis, and  then you go find the appropriate data with which to test them. That is the analytic  part. If it turns out that your assumptions are not true, and your hypothesis  is disproved, then you should take the new data and go back and use it to restate the  hypothesis better. And then you test that new and improved hypothesis. It is an  iterative process that you cycle through continuously, learning something new each  time that allows you to develop a better hypothesis for the next pass. The process is  what we refer to as intelligently opportunistic. In other words, it lets you rigorously  examine your current best guess, but not in a way that forces you to accept or reject  it. It instead allows new and previously unanticipated improvements to your idea to  emerge. This is learning as you go. This hypothesis-driven approach is based on the  idea of learning, rather than knowing. As a result, it is particularly useful under  conditions of uncertainty in which we don’t know as much as we’d like to. Does all of  this sound familiar? Of course it does — a new business idea is, in fact, just a  hypothesis. And a learning launch is just a process for testing and improving that  hypothesis.

That’s the rub. Hypotheses about the future are a lot trickier to deal with than those  about the present; in fact, they can never really be proven to be true. As a strategist or  a growth leader, the best you can do is to marshal compelling evidence that supports  your argument that your view or your “story” about the future is likely to be worth  pursuing. It has to be testable with today’s data.

