As public organizations seek innovations to improve the services delivered, knowledge on the processes of innovation and improvement is an important public management question that requires further attention (Walker, Damanpour, & Devece, 2011). This panel investigates the intra-organizational mechanisms related to organizational change, learning, and improvement through a set of papers that use computational and network techniques to characterize the flow of information, resources, and influence within complex service delivery settings (schools and child protective services). Diagnostically, this panel attempts to better understand the following issues related to improving the performance of public organizations: • How do social and technical processes interact to enable or impede the implementation of innovation? • How does knowledge about an innovation flow between subgroups in organizations, and how is that flow related to the level of adoption? • How does the use of performance information about public programs unfold in organizations, and how do actors use the information in practice? Prescriptively, the papers that comprise the panel provide implications for the following organizational challenges: • How can organizations “roll out” innovations in a way that increases the level of implementation? • What kinds of intra-organizational social network structures best facilitate the flow of information and resources for the implementation of innovation? • How can organizations use artifacts such as performance dashboards to better facilitate the flow of information between public managers and front-line workers? In addition to addressing these public management questions, the papers in this panel also provide examples of methodological innovations in the study of organizations, each integrating qualitative and quantitative data with computational methods in unique ways. By bringing together studies that utilize a diverse set of technical methods while sharing the objective of pushing beyond discursive descriptions of improvement processes, we aim to generate discussion on how traditional qualitative and quantitative data can be leveraged into a more mechanistic understanding of organizational improvement.