Abstract for: Improving the Management of Innovation Risks

Global network structures of products and services are important value creators in many companies. Complex business models include a variety of relationships and interrelationships within and across different systems, especially in innovation processes. This leads to lower predictability and higher behavioral deviations or, in other words, increases innovation risks. Risk management is becoming more and more important and is crucial for the German Machinery and Plant Engineering Industry (MPEI). Many companies are medium-sized and are using standard static risk management methods. Use of these methods often means that critical situations are detected late, they do not help in the understanding of problem characteristics and their interdependencies and, therefore, lead to erroneous decisions. With the industry focusing on its core competence in innovation, companies have complex success factors and complex risk clusters. Therefore, the modelling of cause-and-effect structures of innovation risks in the German MPEI facilitates the exploration and understanding of the behavioral dynamic of risk clusters. In a comparison of standard risk assessment with the Causal Loop Diagram and the System Dynamics Model of Innovation Risks, the potential of System Dynamics for systemic and multi-dimensional risk management is demonstrated.