HBR: Toward Fairer Data-Driven Performance Management

The new world of work has made managing company performance more complex than ever before. Increased concerns around “quiet quitting” and employee surveillance tools have only further complicated this and raised doubts about whether vendors and employers alike can be trusted with the use of workplace data.
Thanks to key advancements in AI and people analytics over the last decade, there are proven, ethical approaches to data-driven performance management that enable companies to define, measure, and improve KPI’s that fit the unique needs and contexts of their enterprise.
Humanyze President & Co-Founder, Ben Waber, co-writes for Harvard Business Review on how the right use of workplace data & analytics is the key to better performance management and overall results across any organization:

“Reliable, accurate, and bias-free measures of employees’ job performance are notoriously elusive. And while companies are awash with data about their employees, their ability to translate them into trustworthy markers of performance is at best a work in progress. Research shows that self-ratings and supervisory ratings of job performance overlap by merely 4%. While true meritocracy in organizations is impossible and performance won’t ever be entirely measurable, organizations can become more merit-based, fairer, and overall more successful if they identify KPIs about performance within their organizations and use the right data to measure it.”

Click here to read to the full article in HBR.


Last Updated 20 December 2022