Industrial trends show that the lead time and costs of integrating and testing high-tech multi-disciplinary systems are becoming critical factors for commercial success. In our research, we developed a method for early, model-based integration and testing to reduce this criticality. Although its benefits have been demonstrated in industrial practice, the method requires certain investments to achieve these benefits, e.g. time needed for modeling. Making the necessary trade-off between investments and potential benefits to decide when modeling is profitable is a difficult task that is often based on personal intuition and experience. In this paper, we describe how integration and test sequencing techniques can be used to quantitatively determine where and when the integration and testing process can profit from models. An industrial case study shows that it is feasible to quantify the costs and benefits of using models in terms of risk, time, and costs, such that the profitability can be determined.