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Why HR Data May Demotivate Employees

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Why HR Data May Demotivate Employees

Wharton paper questions whether tracking and reporting data helps or hinders motivation in the workplace.

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As big data has flooded into the workplace, the use of data to track and report on the progress of employees has mushroomed. A recent paper from the Wharton School of the University of Pennsylvania questioned whether this level of reporting has actually helped or hindered motivation.

The Role Data Plays in Performance and Motivation

Techniques such as stack ranking have been both widely utilized but also widely derided over the past few years, and with more and more means of tracking performance, the study explored just what impact such monitoring has on employees. Does seeing how you compare with your peers motivate or demotivate?

The researchers examined the performance management system used in an American furniture company. The system attempted to tap into the desire for social comparison among its sales staff.

The rationale behind such methods is well established. It is supposed to act as both a motivation but also a means of learning from those that are performing well. Does it really work as we imagine however?

When the researchers showed employees, that were already paid on performance, how they compared with their peers, it didn’t have the desired effect whatsoever.

Those at the top of the charts seemed to slack off when their pre-eminence was revealed, with their peers from the control group (who were not ranked) scorching ahead.

The same seemed to occur for those at the lower end of the charts. They seemed to "check out" and lose motivation for the task compared to their similarly low performing peers in the control group.

Feedback Isn’t As Good As We Think
Interestingly, nearly all employees believed that seeing their ranking would motivate them to greater heights, but when the actual data was analyzed, this was not the case at all. Indeed, the opposite was witnessed.

The authors contend that this is because when we don’t know where we stand in relation to our peers, we focus more on the task and less on our ranking. It also ensures the team think of themselves collectively rather than individually.

Driving Change

One pleasing aspect of the research was that the company were quite willing to act upon the new insights they had gleaned from the data.

That isn’t to suggest that rankings are bad in every circumstance, merely that it is worthwhile doing your own research to see whether it works in your situation or not rather than blindly following what other companies do.

They do caution managers to be careful before implementing shared rankings however, as once the information is out there, it’s next to impossible to take it back.

Bias comes in a variety of forms, all of them potentially damaging to the efficacy of your ML algorithm. Our Chief Data Scientist discusses the source of most headlines about AI failures here.

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