And, as weâve seen in this chapter, the problem with almost all data relating to peopleâincluding youâis that it isnât reliable. Goals data that reports your âpercent completeâ; competency data comparing you to abstractions; ratings data measuring your performance and your potential through the eyes of unreliable witnesses: it wobbles by itself, and fails to measure what it says itâs measuring.
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When we carry our competencies across the measurement bridge, we enter a fake and dangerous worldâas a tool of assessment, order and control, they are worse than useless. But as public signifiers for what we deem most important, they are another way we can cascade meaning in our organizations, and thereby help our leaders and teams understand whatâs most important.
So far, weâve seen that 1) human beings can never be trained to reliably rate other human beings, that 2) ratings data derived in this way is contaminated because it reveals far more of the rater than it does of the person being rated, and that 3) the contamination cannot be removed by adding more contaminated data. And this means, in turn, that ratings-based tools, be they annual engagement surveys, performance-rating tools, 360-degree surveys, or any of the many other varieties at large, do not measure what they purport to measure. And this means, in turn, that discussions based on the data generated by these tools do not accurately reflect the truth of you.
The key to understanding performance is to stop thinking of it as a broad abstraction, and instead start finding elements of it that we can measure reliably and act on usefully.
...you want to be represented by data that simply, reliably, and humbly captures the reaction of your team leader to you. Thatâs not you, and it shouldnât pretend to be you. Itâs your leader, and what she feels, and what she would do in the future. And thatâs enough. Truly.
There are limits to data, however, and some people rely on it too heavily. Analyzing it correctly is difficult, and it is dangerous to assume that you always know what it means. It is very easy to find false patterns in data. Instead, I prefer to think of data as one way of seeing, one of many tools we can use to look for whatâs hidden. If we think data alone provides answers, then we have misapplied the tool. It is important to get this right. Some people swing to the extremes of either having no interest in the data or believing that the facts of measurement alone should drive our management. Either extreme can lead to false conclusions.
âYou canât manage what you canât measureâ is a maxim that is taught and believed by many in both the business and education sectors. But in fact, the phrase is ridiculous - something said by people who are unaware of how much is hidden. A large portion of what we manage canât be measured, and not realizing this has unintended consequences. The problem comes when people think that data paints a full picture, leading them to ignore what they canât see. Hereâs my approach: Measure what you can, evaluate what you measure, and appreciate that you cannot measure the vast majority of what you do. And at least every once in a while, make time to take a step back and think about what you are doing.