Public administration scholars have often sought to determine the predictors of organizational performance. For example, Moynihan and Lavertu (2012) look at predicting the use of performance information as a function of PART scores, GPRA, and a set of individual characteristics. Additionally, Chun and Rainey (2005) measure organization effectiveness (an aspect of performance) using four separate perceptual measures: managerial performance, customer service orientation, productivity, and work quality. These studies add to our knowledge of both perceptions of organizational performance and PART scores as a measure of performance. However, the first set of results is possibly fraught with common source bias as both the dependent and independent variables of interest are measured with the same survey performance (Meier & O’Toole, 2013a, 2013b; Huselid, 1995; Favero & Bullock, 2014). The second set uses PART scores as a reliable indicator of performance, although scholars have also found this to be particularly problematic (Radin, 2006). The Office of Management and Budget’s (OMB) Improper Payment dataset (which examines approximately 100 federal programs from 2004-2011) provides an alternative measure to test the predictors organizational level performance. The improper payments measure focuses on performance in terms of minimizing errors, which is a conceptualization that has not yet been tested in the public management literature. This approach allows for an examination of changes in error rates over time by program, organizational-level characteristics might predict error rates, and employee perceptions to explain the variance in error rates.