The Path to Getting Better

Getting better is pretty hard. Though as a performance psychologist I try to focus attention on simply getting a little bit better each day (you eat an elephant one bite at a time, after all), the reality is that it's quite difficult for people to figure out what to do to get better, what they need to get better at, and how much work it'll take to make real progress.

In a recent edition of the newsletter, I wrote about the benefits of embracing monotony and how setting a self-transcendent goal can help performers stick with it, even when the activity is mind-numbing.

But there's another reason that falling in love with boredom becomes critical in the development of expertise. That's because, for most high performers, there will be long periods of practice marked by little or no progress. These well-known performance plateaus are places where the truly elite decide that there's nothing more important than rising above it, and where some talented but less dedicated athletes fizzle out - either because it's not interesting, it's not worth the time required, or they just don't care or understand how.

A big part of that is the reduced reward people experience from no longer making progress based on the work they put in. We believe that more work leads to better performance, as though work quantity is all that matters. As famous expertise researcher Anders Ericsson put it, "the belief that a sufficient amount of experience or practice leads to maximal performance appears incorrect" (Ericsson, Krampe, & Tesch-Romer, 1993, pg. 366). In other words, just practicing more isn't likely to help you progress at all times - you'll need a bit more innovation and experimentation, which may look and feel crappy before you make progress to the next level.

Long periods of less-than-ideal performance are part of the gig on a quest for high performance.

So how do we get people out of the stale, static periods of no progress and back to the meaningful (albeit potentially incremental) changes that move their talent forward?

Plateaus, Dips, and Leaps

Wayne Gray and John Lindstedt are cognitive scientists who set out to explore the patterns of behavior that underpin the development of real, skilled performance. The framework they introduced - plateaus, dips, and leaps - helps us understand both the trajectory of improvement and what can be done to help people progress from one stage to the next (Gray & Lindstedt, 2017).

Plateaus

Plateaus are part of the process, but they're unpleasant for most performers and can lead to periods of high frustration, burnout, and, at worst, quitting. 

Plateaus are "periods of stable suboptimal performance" where people simply aren't getting any better and are also not functioning at the level that they could be.

Dips

Part of what maintains a behavior in a plateau is the anticipated (and probable) dip in the quality of execution that comes with learning. When we start to execute a new skill, we tend to be bad at it. Unfortunately, being bad is both an experience we're motivated to avoid and something hard to reinforce - which also makes it harder for people to stick with it.

Leaps

Not to be too literal here, but the Fosbury Flop is an example of a leap - a new method is invented, people learn a new skill, and performance reaches a level that we weren't sure was possible before.

When we start to execute the new and better method we're experimenting with during the dip phase, we tend to have leaps of performance that exceed our previous levels of performance. The leaps are incredibly rewarding, so working to reach the leap phase can make the development of skill (patience with the plateau and self-compassion with the dips) more tolerable. When we experience rapid progress and see ourselves get better through experimentation, we are more willing to try it again in the future.

"League-Stepping"

In the research on getting out of plateaus, the methods that move performance to the next level are referred to as "league-stepping methods", which, to be honest, just sounds awesome.

And, the good news is, there is a 3-step process we can take to find our way out of a dip.

The first step is finding a better way. This involves experimenting with new behaviors and discovering new ways to approach the specific skill. What you'd observe during this phase is trying, failing, and iterating repeatedly until the new method is discovered.

The second step refining the way. Once you've discovered the Fosbury Flop, for example, you need to refine the details.

And once that's done, the final step is to practice. Once you've identified the new method and refined it, you have to get it to a point where you can execute it flawlessly. As you get better and better, the dips are erased and you reach a new level.

Going through these steps boils down to discovering new ways to execute, working out the details, and then experiencing the gains that come from using a better method.

You're building your own, improved performance mousetrap.

Finding a better way

When we first need to find our way off the plateau, we begin by searching for new techniques, experimenting, iterating, and trying again. These techniques can come from trying new things during practice, self-reflection, or being told that we should try something new. 

This type of experimenting and searching requires a lot of motivation and hard work.

If you've ever tried to learn or teach a new skill, you know that you tend to be awful in the beginning. When people are no good, they tend to lose motivation quickly. It's rarely rewarding to do a bad job (despite what we tend to say about our colleagues we don't like).

We stay in this period of awful - the dip - until the new technique that's getting us off the plateau becomes more automatic and effortless. 

Reminding yourself that this dip is temporary can help you sustain engagement during the time of toiling. You can also make the dip more enjoyable by reminding yourself that it's a time to explore widely without fear of failure and to let go of preconceived notions of the way things have always been done. 

Once you've built a better mousetrap, it's time to practice.

Practice makes better... To a point

When you're first trying to develop your new skill, you're likely going to perform poorly at the start. When you go to change an NBA player's shot between college and the pros, for example, it's not uncommon for the player to get considerably worse before they get better. Adjusting and developing your methods is hard.

Once we practice enough (here's a formula for mastering skill-building), we should expect to return and then ultimately surpass the previous performance.

It looks like this:

Once the optimal method is selected and developed, the athlete (or any performer, really) has a chance to take their game to the next level.

Practice alone, though, does not advance performance.

People can break skills down into "hierarchies," such that they only adjust one part of the skill at a given time. This allows for a more refined, nuanced approach to development. And, the Power Law of Practice suggests that, at a certain point, more time practicing is not leading to greater development in a skill.

Making the leap

What the research suggests happens when people make a leap - when performance improves - is that they improve multiple methods to reach their goals (Gray & Lindstedt, 2017; Rickard, 1997).

In other words, practice helps us refine and develop the methods after we've explored, but too much practice of one skill has diminishing marginal utility - and real progress is made when we make incremental improvements to multiple skills that move us toward our goal.

Real expertise develops through this cycle of experimentation, performance dip, leap, and begin again.

References

Gray, W. D., & Lindstedt, J. K. (2017). Plateaus, dips, and leaps: Where to look for inventions and discoveries during skilled performance. Cognitive science, 41(7), 1838-1870.

Rickard, T. C. (1997). Bending the power law: A CMPL theory of strategy shifts and the automatization of cognitive skills. Journal of Experimental Psychology: General, 126(3), 288.