What many leaders call understanding is often times something else - a parroting of information e.g., some blog post they read somewhere. This is human nature. Rates of information upload vs. synthesis (e.g., we read much without proper time to process it all fully) are unfavorable - we're moving ever closer to some asymptotic mode of existence where we're literally always online. So it's good to build in processes to keep ourselves honest.
To understand is to have the ability to predict. And to really understand a thing - to discover - is to extend prediction beyond the horizon of others. Bless those who codified the rules for the rest of us so we can stand on their shoulders. Sometimes the understanding is axiomatic: think Newton's laws; and sometimes its intuitive: think Steve jobs' knack for product development. But the persistent theme I've noticed in myself irrespective the content, is the drive - ok, a pathological obsession - to define those rules.
An game I sometimes will play with myself is to take some topic and check my understanding based on my predictions. Getting explicit really helps clear the fog around some areas. So for example I will ask:
- What can you predict what will happen next/tomorrow.
- What can you predict that your peers cannot? Then ask:
- ...*How did you know?*
- Can you repeat this prediction or was it luck?
- If it was repeatable, how would you communicate the rule to someone else?
- How can you use this to achieve your goals. How can you outsmart the competition?
One of the best ways to apply this to your business is to use Andy Grove's (former CEO of Intel) stagger chart - this is straight out of 'High Output Management'. Here's a hypothetical one generated for unit sales on a widget:
Forecast for:
Aug Sep Oct Nov Dec
Forecast made in: Aug 136* 150 165 250 475
Sep
160* 150 260 490
Oct
140* 285 499
Nov
212* 505
Dec
515*
Looking across the chart tells you the n-month forecast.
Looking down the chart tells you how the forecast is changing over time. Taking November unit sales we can see that the forecast has gotten worse over time - farther from the actuals. In contrast December has improved. The team has some misalignment in business drivers and expectations.
The key takeaway is that it's vitally important to implement a feedback mechanism for the organization to check for understanding. This will keep objective reality a value and minimize getting blindsided. In practice this leads to a sharpening of the thought-process itself. While this is a simple example based on widget sales this can be applied to virtually any quantitative measure.