Background
Data on processes, performance, and challenges of public
organizations is increasingly collected and made available. The

promises of using big data and data-informed decision making are frequently heralded as prerequisites in addressing present and future challenges of public sectors across the globe. Yet, research shows that data is seldom used consistently by decision makers, and when it is used, it is often for other purposes than problem-solving and improvement. Moreover, our knowledge about how organizational decision makers interpret and respond to such data is scarce.

Existing research largely focuses on self-reported measures of whether managers use performance information, and the few studies that seek to address decision making are unable to track the decision-making process and have clear limitations in terms of causal identification.

Objective and research method

The project aims to increase our understanding of how performance data informs organizational decision making, how various factors influence the use of data, and how data-informed decision-making processes can better help improve public services. To that end, two related research questions are pursued:

1. How can we develop new ways of tracking and studying data-informed decision processes?
2. How do decision makers interpret and respond to performance data, and what factors influence this
   process?

The project draws on methodological developments in psychology and economics regarding the study of multi- attribute decision making and conjoint experiments and adapts these tools to focus on data-informed organizational decision making. Theoretically, the influence of data in organizational settings is modelled by applying psychological insights about basic human heuristics and biases, focusing on how decision makers interpret and make inferences based on new information. The research questions will be studied in the context of healthcare management.

Healthcare is both the largest welfare service sector, and the sector where data collection is most intensive and data-based decision processes are most institutionalized with daily or weekly use of data dashboard meetings involving managers and professionals. As such, it represents the type of data-oriented setting that many consider to be the future of public organizations.

Additional information

The project is headed by Associate Professor Poul Aaes Nielsen. It is funded with DKK 1.7 million from Aarhus University Research Foundation.