Shipulski On Design

As creatures of habit, we like to do what we did last time. Outcomes match expectations and things go as planned – no surprises, no delays, no problems. But as creatures swimming in an evolutionary soup, doing what we did last time leads to extinction. Customers’ expectations multiply and competitors mutate into a higher performing organism and eat us. There are two competing functions – do what we did last time to minimize energy and try new things to harden ourselves for the ever more competitive future.

You can’t reinvent yourself at every turn or your brain will run out of glucose and you’ll pass out. And you can’t always lounge on the couch or you’ll get out of shape and become a slow-moving snack for the new T-Rex on the block.  If the endpoints lead to our demise, the solution must be something like the middle way.

If you can get away with it, do what you did last time – minimum energy living is a good gig if you can get it. With little investment and lots of return, there’s enough for everyone.  Plenty to eat and some left over to put in stores for the winter. But plenty to eat and plenty of time to goof off may make for lazy (but happy) tribe members who may be of little use when it’s time to defend the business model against hostile species.

Live frugally to develop a surplus and spend some of it trying new things. Improved fitness is the best way to navigate the landscape, even the landscape still beyond the horizon.  More than physical fitness, improved mental fitness is the dominant trait that leads to survival. But doing new work is energy intensive and must be done skillfully.

The primary reason we try new things is to learn. In that way, the new things we try are a means to an end – improved mental fitness. But because doing new is expensive from an energy perspective, the learning ratio (new learning divided by the energy to learn) must be high. First, be clear about what you want to learn because learning the wrong thing costs more energy than resting on the couch. Second, maximize the learning of your experiments.

If you run an experiment where you are 100% sure of the outcome, your learning is zero. You already knew how it would go, so there was no need to run the experiment. The least costly experiment is the one you didn’t have to run, so don’t run experiments when you know how they’ll turn out.  If you run an experiment where you are 0% sure of the outcome, your learning is zero. These experiments are like buying a lottery ticket – you learn the number you chose didn’t win, but you learned nothing about how to choose next week’s number.  You’re down a dollar, but no smarter.

The learning ratio is maximized when energy is minimized (the simplest experiment is run) and probability the experimental results match your hypothesis (expectation) is 50%.  In that way, half of the experiments confirm your hypothesis and the other half tell you why your hypothesis was off track.

We can argue about the energy balance between leveraging best practices and creating new recipes. But, when you want to learn, there can be no argument – maximize the learning ratio.

Image credit – Craig Sunter

Comments are closed.