## 6 Discussion  
Evaluation results may be limited due to the number of case studies (three), the number of users interviewed and the prototypical character of the three case studies. To overcome these deficits, both method and software tool were discussed with three more project managers at the companies, not involved so far, who were responsible for new product development projects of various volumes. The use and applicability was confirmed in these interviews. Additionally, four workshops with six to ten experts from various positions of a large engineering company in automotive industry, independent from the OptiAMix project, were conducted. The workshops were used to evaluate the current state of research results and indicate further research directions to foster industrial application. Assessment of results as well as future research was in line with evaluation results. Still, for an extensive success evaluation and as part of ongoing research, the method needs to be applied in several other companies and branches and results need to be benchmarked to other projects. Since the case studies were in the context of business-to-business markets and centered around additive manufacturing, the evaluation results as well as the underlying database for risk assessment must be reassessed before application in other fields. For instance, there was a predominance of technical aspects in change causes over emotional ones. Although the introduced method captures all categories of change causes, the assessment of change likelihood might be less accurate when emotional aspects were more important and the target group is more diverse (for instance in the field of business-to-consumer markets). As a key to address the diversity of change causes [20; 43; 44; 45], research on different types of uncertainty [2] is essential for validating clear limitations in terms of applicability. The presented approach contributes to the demand for methodical support in requirement change management research [6; 10; 13] and practice [15; 16; 17; 18; 19]. Its holistic approach on risk assessment enables existing approaches from ECM [9; 21; 28; 36] and RCM [6; 10; 20] to be integrated into the broader context of risk assessment and management. Additionally, it reveals the usability of domain independent methods for dependency analysis to reduce application effort [1; 30; 31; 32; 33]. Evaluation also indicated future research directions. Most importantly, the support needs to be linked to risk management activities more closely. As intended, risk assessment is the first step towards holistic risk management of requirement changes and does not provide sufficient support on its own. To unlock the potential of risk management to reduce risk of project failure, the selection of risk management actions needs to be supported as well as the integration into product development processes and activities. To promote this change and to foster the adaption of design practices, the application effort needs to be further reduced. One option is to fully automate dependency analysis. Furthermore, implementing \"learning algorithms\" from historical data and applications seems promising. Since there is a lack of such data within the companies, researchers need to find solutions to enables learning from public sources. With regard to efficiency potentials not addressed so far, two aspects weighed most heavily. First, the scope should be enlarged to include the addition of new requirements. Second, the value presumably increases with the complexity of the system to be developed and the size of the project team. Looking at new requirements added later on in the project, they occurred frequently in the case study projects and caused high development effort. Similar to studies on requirement changes (Section 1), a high proportion of those came from insufficient requirement elicitation and specification. Therefore, risk management might also include actions to encourage the creation of complete and accurate requirement sets.