Supply chains set their ultimate aim as to satisfy their end customers. In other words, they implement a set of practices along their chain in order to generate value for customers. Therefore, aligning supply chain practices with customer values is a core objective of supply chains. The current research employs Bayesian Network (BN) and Analytic Network Process (ANP) to quantify mutual correlations between supply chain practices and customer values. In the first phase, it collects and analyzes data about six specific customer values; in the second phase, the importance of practices is evaluated by expert in the respective industry using ANP; and in the final phase, the output of the two analysis meet in a BN to generate a model which is capable of quantifying their mutual correlations given the input data. In addition, the proposed approach can handle scenarios to identify in case a specific customer value is preferred by the end customer what practice should be implemented; or vice versa, in case a specific practice is implemented how does it contribute to customer values. This approach is applied to a case study in the food industry to present its application in practice.