Any occupancy data can be useful. Badge scanning
data can be enough to generally indicate
underutilized space and reduce real estate costs.
But to take advantage of more advanced
opportunities—like identifying precisely which
spaces are underutilized—you need more granular
data.
Different data sources measure occupancy with
different levels of specificity at different
frequencies. Some solutions were built for other
purposes (like access control) which limits what
they can actually track and where. Others were
purpose-built to deliver more precise insights,
tracking occupancy in a wider range of spaces and
contexts, and with greater frequency.
Badge scanning systems provide the most
basic building-level data showing the number of
people who have passed an access point.
Desk booking software provides room-and-
desk level data for your reservable spaces,
showing when a space is reserved and
presumably occupied.
Manual walkthroughs provide precise counts of
the people in a space or occupied and
unoccupied desks, but there are typically
significant gaps in the intervals between
walkthroughs.
Network-based occupancy monitoring gives an
approximate position of every person who is
connected to your network infrastructure.
Space utilization sensors can provide precise
positioning data for every occupant in a space,
whether it's a floor, room, or individual
workstation.
The most mature organizations have the technology
and processes in place to collect real-time data that
shows exactly where people are in the office. And
they'll typically use data from a variety of sources,
depending on how granular it needs to be for a
given use case.
In our study, data granularity was an area where
some of the enterprises we surveyed would be
considered very mature—36% had the ability to
track real-time data, and about one-third had
occupancy sensors—but they were held back by
how they actually used their data and the value they
were able to extract from it.
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The Occupancy Tracking Maturity Model
4
Data granularity
