Service centers can be viewed as facilities wherein service calls from customers relating to various service families cascade into work packages involving a set of service tasks. A service family is defined as a set of service type variants that have similar or common service tasks and hence may use a common set of resources (called the resource platform) over a given time horizon. In this paper, we present a methodology for determining cost-effective and robust resource platform configuration(s) for a given set of service families offered by a service center. The robust resource platform would be able to handle demand fluctuations from various service types within reasonable limits over a given planning horizon. Several successful studies have been reported in the manufacturing domain on successful application of product platforms to generate customizable product variants with cost advantages. In this paper, we extend the product platform concept to the service domain. The critical parts of the proposed Service Resource Platforming System (SRPS) methodology are: (1) generate rough cut resource selection using dynamic programming and create a resource schedule using linear programming; (2) generate final resource selection using uncertainty linear programming model proposed by Ben-Tal et al. (2003); and (3) construct resource platform using resource sub-sequence clustering concept. The objective for the rough cut and final resource selections is the maximization of the difference between the benefits and costs associated with in-house service processing and outsourcing. The proposed SRPS methodology is applied to an industry motivated problem.