Using PeopleHour For Occupant-Centric Office Building Performance Assessment
Gulai Shen, John J. Gilbert IV, Ali Mehmani
Nantum AI, New York, NY, United States of America
Harvard University, Cambridge, MA, United States of America
Highlights
Introduces PeopleHour concept for occupant-centric building performance assessment.
Uses high-frequency occupancy data in office building performance analysis.
Shows PeopleHour metrics reveal insights overlooked by traditional metrics.
Compares pre- and post-pandemic building performance with new metrics.
Abstract
Measuring and benchmarking office building performance is crucial for enhancing energy efficiency, reducing environmental impact, and improving occupant productivity. Traditional Energy Use Intensity (EUI) metrics and benchmarking methods developed based on them have limitations in accounting for factors like occupancy, can hardly be explainable, and lack evolution with the advent of more real-time data. This paper introduces a set of metrics for building performance based on PeopleHour, which incorporates both the number and duration of occupancy to provide a more occupant-centric perspective on office building performance. By adjusting EUI and other related metrics to reflect building performance normalized by occupancy, we offer a more accurate measure of office building efficiency. Using sample office building data from Nantum OS, we demonstrate how PeopleHour-adjusted metrics reveal insights that traditional methods may overlook, particularly during significant occupancy changes before and after the COVID-19 pandemic. This approach emphasizes the importance of occupancy-driven operations especially as the shift of work mode and office building uses after the pandemic. It suggests that PeopleHour can enhance energy benchmarking practices, leading to more informed decisions for improving building performance across various sectors.
