Rapid development of technologies like building information modeling (BIM) and internet of things (IoT) has provided new tools and methods to facility owners for more effective asset management during the operation and maintenance (O&M) phase. However, many owners face a challenge to identify and address needed technical and organizational transformations to fully leverage new technologies. This paper reports on a series of workshops facilitated by the authors to discover key elements in developing standards and processes for data-driven asset management systems (AMS). For this applied research, the authors worked with six large public owners (including army, educational, transit, and seaport/airport facility owners) to analyze effectiveness of their current AMS, taxonomy and structure of their AMS database including asset's types, attributes, and specifications, as well as their means and methods for collaboration with designers and contractors to create reliable data required for O&M activities. The outcomes of this research are a standard framework for identifying and addressing data requirements for effective assets life-cycle management, as well as lessons learned from peer organizations' experiences and practices for integrating new technologies into asset management. The findings of this research will also help researchers in the academia to better understand the real-world constraints and requirements the AECO industry encounters to incorporate innovative research-based solutions into the existing practices.
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