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The Occupancy Tracking Maturity Model
Occupancy sensors generally provide the greatest
accuracy, but it depends on the specific types and
models of sensors that you use, as the underlying
technology uses different methods to detect and
track an occupant's presence.
With greater data accuracy, an organization may
find that their average or peak occupancy rates for
reservable spaces are lower than what their
reservation data suggested, due to no-show
cancellations. Or they may find that their occupancy
levels in a building are much higher than their badge
data shows, as employees regularly hold the door
for colleagues, or the prevalence of badge
malfunctions makes the data less reliable. These
accuracy issues can cause employers with an
immature implementation of occupancy tracking to
believe they've optimized their workplace around
their people, only to discover new problems, which
make them hesitant to trust and utilize occupancy
data in the future.
5
Data accuracy
Organizations with high occupancy tracking
maturity have data they can trust to inform
decisions about individual spaces within a
workplace. Less accurate data sources are good
enough for basic use cases like real estate, but more
accurate data increases the value of these use
cases and opens the door to new opportunities.
Badge scanning data can have several accuracy
issues:
Some systems allow multiple occupants to
enter or exit at a time with a single badge swipe.
Badges can malfunction and require someone to
be let in without a scan.
Not all systems track exits, making it difficult to
know how many people are in the building
(especially if employees engage in "coffee
badging").
Desk booking software can have issues as well:
someone can reserve a space and then not show up,
so the space appears to be occupied when it's
vacant. (Tango Reserve has a feature for addressing
"no-show cancellations" like this, but it's not the
norm for this category of solutions.)
Network-based occupancy monitoring uses signal
strength to triangulate a network user's position, or
the location of an ethernet port they're connected
to. Some systems may not be sophisticated enough
to recognize "duplicate" users when a single
occupant is connected with multiple devices (Tango
Occupancy de-duplicates this data), but more
importantly, signal strength can only provide an
approximate location. It works well for tracking large
spaces or specific workstations, but may not always
recognize when occupants move into rooms that
are connected to larger spaces.
