Models aid in the analysis of outsourcing opportunities. We demonstrate the use of DEA, followed by a DEA simulation model and also a Monte Carlo Simulation using a risk‐adjusted cost concept. DEA method aids the buyer in classifying the suppliers (or their initial bids) into two categories: the efficient suppliers and the inefficient suppliers. Weber has primarily discussed the application of DEA in supplier selection in several publications; see Weber and Ellram (1993), and Weber and Desai (1996). Apart from simply categorizing suppliers, Weber demonstrated how DEA can be used as a tool for negotiating with inefficient suppliers. However, classical DEA often fails to work effectively since classical DEA is very sensitive to statistical noise (Wu, 2009a), which motivates the utilization of a DEA simulation model. We do this with hypothetical data, with the intent of showing how alternative vendors in supply chains can be evaluated. Using hypothetical data is somewhat lack of empirical evidence, but can keep approaches and insights in a general framework. Real data would be specific to each organization making the selection decision. The rest of the paper is organized as follows. Section 2 of the paper presents outsourcing risk categories. Section 3 discusses outsourcing to China. Section 4 presents simulation of DEA Model results and analysis, Section 5 presents Monte Carlo Simulation for Analysis, and section 6 concludes the paper.