Middle Level: Exploratory Projects

We arrive now at the middle level of the pyramid, which is responsible for most of the work I produce as a professor. As explained in Rule #4, an effective strategy for making the leap from a tentative mission idea to compelling accomplishments is to use small projects that I called “little bets” (borrowing the phrase from Peter Sims’s 2010 book of the same title). As you might recall, a little bet, in the setting of mission exploration, has the following characteristics:

• It’s a project small enough to be completed in less than a month.

• It forces you to create new value (e.g., master a new skill and produce new results that didn’t exist before).

• It produces a concrete result that you can use to gather concrete feedback.

I use little bets to explore the most promising ideas turned up by the processes described by the bottom level of my pyramid. I try to keep only two or three bets active at a time so that they can receive intense attention. I also use deadlines, which I highlight in yellow in my planning documents, to help keep the urgency of their completion high. Finally, I also track my hours spent on these bets in the hour tally I described back in the section of this conclusion dedicated to my application of Rule #2. I found that without these accountability tools, I tended to procrastinate on this work, turning my attention to more urgent but less important matters.

When a little bet finishes, I use the concrete feedback it generates to guide my research efforts going forward. This feedback tells me, for example, whether a given project should be aborted and, if not, what direction is most promising to explore next. The effort of completing these bets also has the added side benefit of inducing deliberate practice—yet another tactic in my ever-growing playbook dedicated to making me better and better at what I do.

Ultimately, the success or failure of the projects pursued in this middle level helps me evolve the research mission maintained by the top level. In other words, the system as a whole is a closed feedback loop—constantly evolving toward a clearer and better supported vision for my work.