2013 has seen growing interest in the idea of ‘people analytics’ – informally described as the application of ‘Moneyball’ to corporate HR, but more formally defined as the use of predictive statistical analysis to inform the recruitment and assessment in workers. Just as sports teams are increasingly attuned to the power of statistics in judging player ability and informing their signings, so companies are looking to use the power of numbers over potentially misleading ‘gut instincts’ and all too short interviews. The hope is that the use of ‘big data’ can offer more reliable insight into the attributes that make for effective employees by drawing robust correlations. For years baseball coaches focused on the wrong statistics, according to Moneyball, for example emphasising batting average, rather than On Base Percentage. Perhaps the same is true of Human Resource managers, who could be over-emphasising things like educational attainment – an early finding appears to be that college degrees are overrated.
Commentators have been divided as to whether the people analytics is a promising or ominous development for society. For Don Peck, people analytics offers hope for fairer hiring processes, with the marginalisation of (often unintentionally) prejudiced human intervention, since “A mountain of scholarly literature has shown that the intuitive way we now judge professional potential is rife with snap judgments and hidden biases”. Moreover, people analytics can enhance social mobility by reducing the influence of educational background:
For decades, as we’ve assessed people’s potential in the professional workforce, the most important piece of data—the one that launches careers or keeps them grounded—has been educational background: typically, whether and where people went to college, and how they did there. Over the past couple of generations, colleges and universities have become the gatekeepers to a prosperous life…But this relationship is likely to loosen in the coming years
However, Andrew Leonard is wary of a world in which bosses have a clear view of their employees’ productivity, foreseeing “a darker scenario, one that increasingly seems to be playing out already: The best workers reap huge rewards; everyone else struggles for the scraps”.
To a large extent these arguments play out familiar debates from political philosophy over the value and desirability of meritocracy. Peck’s account of helping those consigned to the scrapheap because of their past, or neglected because of latent prejudice gets to the heart of the view that meritocracy is morally valuable because it avoids wrongful discrimination. On the other hand, Leonard taps into a concern that meritocracy neglects substantive inequalities – as Adam Swift puts it: “Why care about unequal chances of mobility between positions rather than the extent to which those positions are unequal?”. Moreover, there is the concern that material inequality could be exacerbated by the psychological effects of living in a perfect meritocracy, as famously suggested by Michael Young:
If meritocrats believe, as more and more of them are encouraged to, that their advancement comes from their own merits, they can feel they deserve whatever they can get.
They can be insufferably smug, much more so than the people who knew they had achieved advancement not on their own merit but because they were, as somebody’s son or daughter, the beneficiaries of nepotism. The newcomers can actually believe they have morality on their side
Thus if meritocracy is achieved, the successful develop a superiority complex and increase their power and privilege while the unsuccessful lose all sense of self-worth, with nobody to blame for their plight but themselves. The result is a society polarised beyond recognition.
Peck and Leonard do not add anything distinctive to the debate around meritocracy, but rather offer a glimpse of a society which more closely approximates meritocracy. However, I think that people analytics has the potential to bring to the surface tensions which are currently insignificant or neglected in the meritocracy debate.
First, people analytics could have an effect on the perceived relationship between meritocracy and economic efficiency. One common rationale for meritocracy is that ensuring that the best candidates are in the best positions should secure higher productivity and consequently make society as a whole richer. But this is not necessarily the case. If the cost of securing a better candidate is greater than the extra wealth generated by that worker (over and above the candidate that would otherwise be hired) then meritocratic hiring is less efficient.
People analytics is likely to bring this tension into the open because it is likely to develop more or less fine grained tools, leaving it to the hirers how much they believe it is worth investing in securing the best workers. In some cases, cruder and cheaper methods are bound to be chosen, even though they might mean overlooking the best person for the role, because the cost of identifying that person is greater than the benefit they would provide. This is likely to test the resolve of meritocrats – is their ideal important enough to force companies to invest in recruitment, even if is not worth the cost?
A second – more hopeful – possibility is that people analytics might bring to the fore the flexibility of the concept of merit. Peck alludes to the possibility that people analytics might be more about getting people into “better-fitting”, rather than “better” jobs. That is – people analytics might be less about separating the capable and brilliant from the incompetent than about finding the niche that suits each individual’s aptitudes.
Even if this is a bit utopian, people analytics could help bring to the fore the changeability of marketable skills. The original idea of Moneyball was not to find the best players, but rather those who are ‘undervalued’ – players whose talents were insufficiently appreciated by the market. This is an inherently dynamic process – for as soon as other teams adopt a similar scouting and tactical style, a different type of player will become undervalued. A couple of cycles of this process should serve to demonstrate that success is not simply about being the best player, but to have the right skills for the right environment.
If people analytics produces similar cycles in the job market, then it should reinforce to the successful that they are lucky, and that at any given point their luck could change. Moreover, this sense of contingency is likely to guard against the arrogance and despair that Michael Young foresaw in his vision of meritocracy.
The idea of meritocracy is a complicated one, offering hope for human dignity and equality on the one hand, but carrying the risk of polarisation and division. The prospect of people analytics further clouds the purported ideal – its development must be watched carefully.