Statistical analysis of process simulations

Simulations of New Product Development (NPD) processes using their specific contexts can provide project managers with decisions-making aids. The NPD context, which incorporates knowledge about the product, requirements, technology, and other factors, is dynamically evolving during the process. The Design Structure Matrix (DSM) could be used to model this product knowledge and reordering algorithms could be used for process planning. The plan should be updated as the product knowledge evolves; however, the transition from DSM-based plan to process scheme implementation is not unique. The process can then be used for simulating process related measures that can guide the decision making regarding the preferable implementation strategy. However, such decisions should reflect the statistical confidence of the simulation results. In the current work, the properties of multiple repetitive simulations are used for supporting decision-making based on statistical confidence interval derived by evaluating the significance of the difference between the results of applying different DSM-based plan implementation options (defined as business rules). The same approach is applicable to similar decision-making related to processes in general.