Often the processes for purchasing commodities and services within a business enterprise are centralized into a procurement organization. These purchases are often sourced from one or more suppliers, or vendors, based on contract terms and conditions (such as price, payment terms etc.), availability, and quality or legacy habit of purchasing service with known vendors. We have found that many organizations lack appropriate processes and disciplines to drive demand to preferred suppliers. Thus these enterprises are unable to leverage the value of the pre-negotiated contracts due to lack of process education, approval process steps or appropriate purchasing tools that could result in significant amounts of spending that would be considered not compliant (not being sourced through preferred suppliers). Depending upon the size of the organization, such transactions range from several million dollars to billions of dollars. Manually sifting or employing typical query tools to review large amounts of spend transaction data with multiple attributes to identify the level of non compliant spend and identify areas to take action is a daunting task. In this paper, we discuss a software solution for spend compliance analytics that includes measurements of cost savings due to increased compliance and identification of areas where spend tends to be non compliant. We have developed a web enabled advanced analytical solution called Compliance Analytics Tool (CAT) that embeds a two phase methodology for compliance management. In the first phase, we use advanced data mining techniques to segment a large amount of historical spend transactions to quickly identify promising areas of improvement, exploiting a multitude of purchasing attributes such as business unit, procurement category, suppliers, etc. The second phase employs portfolio optimization techniques to further focus on specific segments that provide maximum benefit based on desired compliance targets or available budget. We also discuss the solution architecture that integrates business analytics along with business intelligence tools, dashboards, and data warehousing. © 2011 IEEE.