Management controls as a success factor in the post-merger integration of M&A transactions: From a German perspective

Scholars and practitioners agree on the importance of the post-merger integration phase for the success of mergers and acquisitions. Nevertheless, the post-merger integration phase is described as one of the most complex and uncertain phases. In this regard, it was analyzed how management control systems can contribute to the success of an integration. This thesis aims to shed light on effective management control systems that are used during the post-merger integration. How do experts apply and implement management controls in reality? What lessons learned and best practices can be drawn from their experience? There has been a gap in past research on management controls in PMI. This thesis thus aims to create an in-depth understanding on how to best apply and set up management control systems during an integration from a German perspective. A qualitative data collection approach was followed. Findings were drawn from eight interviews with ten experts from consulting firms and industrial companies in Germany. All experts had previous integration experience and worked on actual integrations in a German context. This allowed a broad overview on management controls used. Examples were given of management control mechanisms, the tools used and lessons learned from a German perspective. A management control framework by Malmi & Brown (2008) served as a basis for research. The framework has not previously been applied to M&A transactions, especially the post-merger integration, but has proven as applicable during this research. It was found that management controls are considered to have a positive effect on the integration success. From a German perspective, the control categories of cybernetic and planning controls are viewed as the most important control categories. The Malmi & Brown framework reflects all management controls that are important for the experts in an integration. Further, the control categories show high interdependencies among each other. The research findings were then used to draw up recommendations for managers and identify possible future research topics.