One of the most important jobs of a supervisor is defining goals and targets together with their employees. Well-set targets increase motivation, make it easier to plan ahead, and help to coordinate activities within the company. But if performance targets are set too high or too low, the exact opposite occurs, and employee motivation decreases, along with employees’ trust in their supervisor. “This is often a risk with supervisors who have been promoted because of their excellent performance,” explains Christoph Feichter, associate professor at the Institute for Strategic Management and Managerial Accounting at WU (Vienna University of Economics and Business). “In the tasks that they carried out themselves, these supervisors expect their employees to deliver an equally strong performance. But in most cases, this is counterproductive.”

Christoph Feichter came to this conclusion with the help of a series of experiments. In the first one, he gave the participants simple tasks, and they received a small amount of money for completing them. Subsequently, some of the test subjects were promoted to supervisors: They had to set targets for the other participants and received money if these goals were achieved. The results showed that participants who had excelled at a given task earlier went on to set higher goals for this specific task in their role as supervisors – even if they were told what the average performance levels of the other participants had been.
 

Bias alert!

“We humans tend to overemphasize our own experiences,” explains Christoph Feichter from WU, “and this is what we call experience bias.” The problem here is that success depends on many factors – including luck. To demonstrate this, Christoph Feichter came up with a twist in his second experiment: Some of the test subjects were randomly assigned particularly easy or particularly difficult tasks. As supervisors, they then set unrealistically low or high goals, which made the other test subjects feel less motivated and caused them to give up more quickly.

The remedy: The more clearly supervisors are made aware that they cannot draw conclusions about the experiences of others based on their own experiences, the less pronounced the effect turns out to be. This is exactly what Christoph Feichter tested in the second experiment: He told some of the test subjects that their own tasks had been particularly easy compared to the others – and after receiving this information, they set more realistic targets. However, this only works if there is absolutely no room for interpretation and the supervisors are told in no uncertain terms that their own experience has been unique. “This goes to show how important it is for supervisors to remain humble and question their own ways of thinking,” says Christoph Feichter, the author of the study.

In practice, he says, experience bias primarily explains why some supervisors set targets that are far too demanding. This is especially true in industries where extremely high performance is expected and where managers have to work their way up, for example in finance, consulting, or law firms. Such companies should pay close attention to how targets are set. “Special training and development programs are one option here. In some companies, supervisors are also required to coordinate their targets with the supervisors of other teams before adopting them. Goals can also be set centrally, or companies can compare employee performance in comparative, relative terms rather than setting absolute targets for individual employees.”
 

Detailed research results and further information

Feichter C, 2022. The effect of supervisors’ prior task performance on employees’ targets. The Accounting Review January 2023; 98 (1): 191-214. https://doi.org/10.2308/TAR-2019-0454 
 

About the researcher

Christoph Feichter is an associate professor at the WU Institute for Strategic Management and Managerial Accounting. He carries out empirical behavioral research in management control. In particular, his research interests include behavioral management, target setting, and performance evaluation. Christoph Feichter holds a PhD from Maastricht University (the Netherlands), where he also worked as an assistant professor, and he has completed several research visits at world-class universities, including the University of Texas at Austin (USA), the University of Illinois Urbana-Champagne (USA), and the University of Waterloo (Canada).
 

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