Does a knowledge gap contribute to the performance gap? Interviews with building operators to identify how data-driven insights are interpreted

Data-driven operation and maintenance analytics for improving building energy performance are prevalent in the literature and produce various visualizations and key performance indicators that identify hard and soft heating, ventilation, and air conditioning faults, occupancy patterns, and energy use deficiencies. However, an underlying assumption exists that the outputs of these analyses, some adopted from ASHRAE guidelines, can effectively impart actionable energy-saving insights to building operations personnel and augment the handling of faults, optimized operating controls, or building-level scheduling. This paper attempts to identify potential barriers to effective interpretation and utilization of data-driven, energy-saving insights by building operators and facility managers. Eleven operations professionals were interviewed and assessed regarding what initiatives or changes they would make in light of various outputs of multiple established data-driven approaches. Data from the interviewees’ individual building portfolio were inputted into a multi-source data analytics web application, employing fault detection and diagnosis and inverse modelling techniques, and its outputs were presented to interviewees. Only two of the 11 interviewees expressed interest in making controls changes in response, revealing a possible knowledge gap of data-driven analytics, combined with the risk-adverse nature of building operations, which may inhibit operations personnel from effectively utilizing data-driven insights as presented.