Ancillary Asset Data Management in State Departments of Transportation: Enhancing Current Trends in Data Collection, Management, and Utilization

This study investigates the current ancillary asset management practices of state Departments of Transportation (DoTs) in the United States through a combination of a comprehensive survey of 39 state DoTs, cluster analysis, and case examples of the Michigan and Minnesota DOTs. The research examines how state DoTs collect, manage, and utilize data for 38 different ancillary asset classes which reveals quite significant variations in data collection methods, frequency, repository management, and updating processes across different asset types and state DoTs. Cluster analysis identified distinct patterns for the management practices; generally, the assets that were identified as safety-critical received more frequent attention in a more systematic manner. Also, centralized data management with increased automation in data collection and updates are highlighted as general trends for technical and frequently monitored assets. Additionally, it uncovers challenges related to integrating data and standardization, as well as achieving consistent upper management engagement. Implementation strategies associated with successful case example in both MDOT and MnDOT are identified, including risk-based strategies, robust quality control measures, and the integration of advanced technologies. The findings of the study bring insight into best practices in ancillary asset management, offering ways to improve them though providing valuable insights to those state DoTs that have ambitions to enhance their ancillary asset management strategies in an era of aging infrastructure and limited resources.