There is an increasing focus on risks in the delivery of welfare services in the public sector. Often, there are no evidently right or wrong answers to the challenges faced by employees with citizen contact. Take for instance physicians who diagnose and make treatment plans based on various tests and statements from the patients that potentially are contradictory. Likewise, social workers must decide whether to take action or not in cases of suspected child neglect. Both of these situations are risky. Employees' decisions depend on the (limited) information available to them, combined with their professional knowledge, experience, and discretion. These are risky situations, because there is uncertainty about the consequences of the decisions. Does the patient's knee get better after surgery? What happens if the child is abused but not removed? What happens if the child is not abused, but is removed from its parents? The lack of clear answers when employees make decisions in complex cases involving citizens makes leadership all the more important.
Objective and methods
The project focuses on risk management. Specifically, how public managers handle the discretion of employees in situations where there is uncertainty about the consequences of a decision that matters to citizens. The project will provide knowledge about what risk management entails, how it is exercised by public managers, and how it affects the behavior of public sector employees. It compares healthcare and social services. They are both sectors where there is a lot at stake for citizens, the risks are visible, and employees have a high degree of discretion.
The project draws on psychological insights about human behavior in risky situations. This is combined with knowledge about leadership and employee behavior in public organizations. Empirically, the project uses various qualitative and quantitative research methods such as observations, interviews, and survey experiments. Based on this data, the project will answer the following questions:
The project is headed by PhD student Emily Tangsgaard and supported by Associate Professor Anne Mette Kjeldsen and Professor Søren Serritzlew.