Toward Fairer Data-Driven Performance Management

Meritocracy matters. A company that rewards talent, effort, and achievement can be expected to outperform those where nepotism, systemic biases, toxic politics, and sheer incompetence are prevalent; it’s just a matter of time. The rise of people analytics, innovations in the field of HR technologies, as well as the inevitable integration of AI and machine learning algorithms into talent management practices, are all signals of the same underlying phenomenon: a relentless quest for a more rational, fair, and evidence-based approach to managing workers, and unlocking human potential at work.

Yet reliable, accurate, and bias-free measures of employees’ job performance, key to managing performance more fairly, remain notoriously elusive. Indeed, despite ubiquitous tech tools, not to mention avalanches of fancy data, visualizations, and dashboards, the reliable quantification of workers’ value creation remains as distant from real-world management realities…

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This article was written by Tomas Chamorro-Premuzic and originally published on hbr.org