This paper aims to investigate data elements, transfer, gaps and the challenges to implement data analytics in facilities management. The goal is not to search for a definite solution but to gather necessary information, understand the challenges faced and develop a proper foundation for future study.
This paper used a case study approach with a qualitative method. The case of the Georgia Institute of Technology was investigated by having a semi-structured interview with six relevant personnel. The recorded interview content was analyzed and presented based on six work processes.
Higher education institutions are taking initiatives but facing challenges in implementing data analytics. There were 36 software tools used to manage different aspects of facilities at Georgia Tech. Identified data elements and data processing indicated that major challenges for data-driven decision-making were inconsistency in data input and structure, the issue of interoperability among different software tools and a lack of software training.
The authors only interviewed individuals who work closely with data gathering, transfer and processing. Thus, the study did not explore the perspective of individuals in the leadership level or the user group level.
Facilities management departments in higher education institutions perform multi-disciplinary functions, including building automation, continuous commissioning and preventative maintenance, all of which are data- and technology-intensive. Managing this overwhelming amount of information is often a challenge, but well-planned data analytics can be used to draw keen insights about any aspect of facilities management and operations and assist in evidence-based decision-making.
