# Life-Cycle Oriented Risk Assessment Using a Monte Carlo Simulation
## 5 Discussion
### Case Implications  
The presented use-case shows the importance of incorporating the fundamental system dynamics presented in Figure 4 into the decision-making process. Within the use-case, two basic strategies can be identified:  
1. Immediate switch: an immediate switch is only reasonable if the specifications are well defined and effects of the switched parts on the overall performance are well known--i.e., if \(\int_{\infty}^{0}f_{\rm A}(\rm u)du\) is sufficiently low. This strategy always offers the biggest savings if the specifications and the effects of the change are well known.
2. Testing: should there be any significant uncertainty about the specification or the performance of the new product, testing is mandatory. In the presented case, testing before switching was always the preferred strategy compared to parallel testing and switching. Additional soft criteria, such as the demand for immediate effective savings, might favor the parallel approach. This is, however, only recommended if the testing time is short enough and the certainty level of the new performance is high enough.  
Generally, the risk-assessment tool used here assists the assessment of the three switching strategies. Additionally, it enables the visualization of the expected development over time. This is a very important indicator to understand the dynamics of the different strategies. The tool further helps to identify additional improvement measures, by quantifying the sensitivity analysis of different parameters. Only by having resilient product specifications and good predictions of the product's new performance, can the risk be minimized, and the potential saving maximized. This shows that the inter-department work is mandatory: the production department is generally limited to testing the new parts given the--possibly uncertain--specifications.  
Relating to the research question, the Monte Carlo simulation was able to map the technical uncertainty to a managerial uncertainty measured by the expected savings. The tool was able to reproduce real scenarios and was proved useful by the involved indus  
Figure 7: Dependency of the expected saving, testing time and certainty about the specification and performance of the product.  
try partners. The approach was especially able to close the gap between technical and managerial viewpoints on the problem of how to change the supplier of a part.  
The application of the implemented tool in the firms has further triggered an internal discussion during the parametrization: Estimations and quantification of certain parameters required an intensive analysis of the product requirements and performances over several departments. Hence, two case-specific contributions of the developed tool can be identified:  
1. Quantification of the lifetime-oriented risk given certain product properties and parameter uncertainties and thus assisting the decision-making progress on a managerial level. This advantage is in line with the finding of existing applications described in Section 2.5.
2. Internal awareness about missing or misfitting product requirements, specification, and performance characteristics. This insight occurred during the parametrization of the model prior to the Monte Carlo simulation.