Beyond peak demand: integrating occupancy sensing and analytics for evidence-based meeting space optimization

What is it about?

Many organizations plan meeting rooms for rare peak days and rely on booking data that often overstates real use. This can lead to too much space being dedicated to meeting rooms, while still leaving employees unable to find an appropriate room at busy times. In this study, we used seat-mounted sensors to record 1-minute occupancy in 17 meeting rooms in an office building over 2 working weeks. We then analyzed the data to estimate the meeting-room capacity needed to meet demand most of the time, identify common types of meetings, and test hundreds of alternative room mixes using repeated computer simulations that account for overlapping meetings. The results show that an evidence-based redesign can meaningfully reduce the area allocated to meeting rooms while maintaining reliable access. In our case, the recommended room mix reduced active meeting space by about 23 percent and lowered the share of meetings that could not be accommodated to about 3 percent. The analysis also revealed substantial demand for single-person focus rooms, which were not part of the existing portfolio.

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