In 2009 IBM was recognized as a finalist of the INFORMS Edelman competition for its predictive modeling initiative to improve the productivity of its global salesforce and with an estimated business impact of ~ 100 Million dollars. The first component implements some traditional propensity modeling to identify new sales opportunities and is currently used by over 13,000 sales reps. The second 'wallet estimation' component is used strategically to allocate sales resources based on validated analytical estimates of revenue opportunity. In this case study we cover the key elements leading to the success including the data integration, data mining and predictive modeling, solution delivery, human guided model validation, integration of the business process and we conclude with an assessment of the bottom-line business impact.