The Tyranny of Metrics, Jerry Z. Muller
"There is nothing intrinsically pernicious about counting and measuring human performance."
"Used judiciously, then, measurement of the previously unmeasured can provide real benefits. The attempt to measure performance--while pocked with pitfalls, as we will see--is intrinsically desirable. If what is actually measured is a reasonable proxy for what is intended to be measured, and if it is combined with judgment, then measurement can help practitioners to assess their own performance, both for individuals and for organizations. But problems arise when such measures become the criteria used to reward and punish--when metrics become the basis of pay-for-performance or ratings."
"Because belief in its efficacy seems to outlast evidence that it frequently doesn't work, metric fixation has elements of a cult. Studies that demonstrate its lack of effectiveness are either ignored, or met with the assertion that what is needed is more data and better measurement. Metric fixation, which aspires to imitate science, too often resembles faith."
"The quest for numerical metrics of accountability is particularly attractive in cultures marked by low social trust. And mistrusts of authority has been a leitmotif of American culture since the 1960s. Thus in politics, administration, and many other fields, numbers are valued precisely because they replace reliance on the subjective, experience-based judgments of those in power. The quest for metrics of accountability exerts its spell over those on both the political left and right. There is a close affinity between it and the populist, egalitarian suspicion of authority based on class, expertise, and background."
"CEOs, university presidents, and heads of government agencies move from one organization to another to a greater degree now than in the past. A strange, egalitarian alchemy often assumes that there must be someone better to be found outside the organization than within it: that no one within the organization is good enough to ascend, but unknown people from other places might be. That assumption leads to turnover of top leaders, executives, and managers, who arrive at their new posts with limited substantive knowledge of the institutions they are to manage. Hence their greater reliance on metrics, and preferably metrics that are similar from one organization to another (aka "best practices"). These outsiders-turned-insiders, lacking the deep knowledge of context that comes from experience, are more dependent on standardized forms of measurement. Not only that, but with an eye on their eventual exit to some better job with another organization, mobile managers are on the lookout for metrics of performance that can be deployed when the headhunter calls."
""To demand or preach mechanical precision, even in principle, in a field incapable of it is to be blind and to mislead others," as the British liberal philosopher Isaiah Berlin noted in an essay on political judgment. Indeed what Berlin says of political judgment applies more broadly: judgment is a sort of skill at grasping the unique particularities of a situation, and it entails a talent for synthesis rather than analysis, "a capacity for taking in the total pattern of a human situation, of the way in which things hang together." A feel for the whole and a sense for the unique are precisely what numerical metrics cannot supply."
"Remember that, as we've seen, performance metrics that link reward and punishment may actually help reinforce intrinsic motivation when the goals to be rewarded accord with the professional goals of the practitioners. If, on the other hand, the scheme of reward and punishment is meant to elicit behavior that the practitioners consider useless or harmful, the metrics are more likely to be manipulated in the many ways we've explored. And if the practitioners are too geared toward extrinsic reward, they may well react by focusing their activity on what is measured and rewarded, at the expense of other facets of their work that may be equally important. For all these reasons, "low stakes" metrics are often more effective than when the stakes are higher."