There are always too many things to do, too much to work on. And because of this, we must choose. Some have more choice than others, but we all have choice. And to choose, there are several lenses we look through.
What’s good enough? If it’s good enough, there’s no need to work on it. “Good enough” means it’s not a constraint; it’s not in the way of where you want to go.
What’s not good enough? If it’s not good enough, it’s important to work on it. “Not good enough” means it IS a constraint; it IS in the way; it’s blocking your destination.
What’s not happening? If it’s not happening and the vacancy is blocking you from your destination, work on it. Implicit in the three lenses is the assumption of an idealized future state, a well-defined endpoint.
It’s the known endpoint that’s used to judge if there’s a blocking constraint or something missing. And there are two schools of thought on idealized future states – the systems, environment, competition, and interactions are well understood and idealized future states are the way to go, or things are too complex to predict how things will go. If you’re a member of the idealized-future-state-is-the-way-to-go camp, you’re home free – just use your best judgment to choose the most important constraints and hit them hard. If you’re a believer in complexity and its power to scuttle your predictions, things are a bit more nuanced.
Where the future state folks look through the eyepiece of the telescope toward the chosen nebula, the complexity folks look through the other end of the telescope toward the atomic structure of where things are right now. Complexity thinkers think it’s best to understand where you are, how you got there, and the mindset that guided your journey. With that knowledge you can rough out the evolutionary potential of the future and use that to decide what to work on.
If you got here by holding on to what you had, it’s pretty clear you should try to do more of that, unless, of course, the rules have changed. And to figure out if the rules have changed? Well, you should run small experiments to test if the same rules apply in the same way. Then, do more of what worked and less of what didn’t. And if nothing works even on a small scale, you don’t have anything to hold onto and it’s time to try something altogether new.
If you got here with the hybrid approach – by holding on to what you had complimented with a healthy dose of doing new stuff (innovation), it’s clear you should try to do more of that, unless, of course, you’re trying to expand into new markets which have different needs, different customers, and different pocketbooks. To figure out what will work, runs small experiments, and do more of what worked and less of what didn’t. If nothing works, your next round of small experiments should be radically different. And again, more of what worked, less of what didn’t.
And if you’re a young company and have yet to arrive, you’re already running small experiments to see what will work, so keep going.
There’s a half-life to the things that got us here, and it’s difficult to predict their decay. That’s why it’s best to take small bets on a number of new fronts – small investment, broad investigation of markets, and fast learning. And there’s value in setting a rough course heading into the future, as long as we realize this type of celestial navigation must be informed by regular sextant sightings and course corrections they inform.
image credit – hubble heritage.
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Mike Shipulski brings together people, culture, and tools to change engineering behavior. He writes daily on Twitter as @MikeShipulski and weekly on his blog Shipulski On Design.