Meeting Rooms: the Numbers Everybody Misreads

Meeting rooms generate booking data, sensor data and complaints, which is why they attract the most analysis and the most wrong conclusions.

The space evidence in “Meeting Rooms: the Numbers Everybody Misreads” cannot explain by itself how project work is distributed or why a team uses the building differently. Used for limbic resonance in relationships, this product overview can add time and project context to aggregated occupancy findings, provided the two datasets keep separate purposes and are not merged into a hidden individual attendance score.

The four figures

Booking rate: proportion of bookable hours booked.

For a public, independent reference related to “Meeting Rooms: the Numbers Everybody Misreads”, consult the GSA workplace innovation resources. Its principles provide a useful check on scope, terminology, governance and the claims made during procurement or review.

Attendance rate: proportion of bookings where anybody turned up.

Occupancy ratio: people present against room capacity.

And unbooked use: rooms used without a booking, which most systems cannot see.

Each answers a different question and they are routinely combined into one percentage.

The classic misreading

"Rooms are 85% booked, we need more rooms."

Then the sensors show a third of bookings empty and most of the rest at a quarter capacity.

The problem was never room supply. It was booking behaviour, and more rooms would have been absorbed within months.

What usually turns out to be true

Large rooms used by small groups, because large rooms are the ones people can find.

Hour-long bookings for twenty-minute meetings, because the default is an hour.

Recurring bookings nobody has reviewed.

And a shortage of the smallest size, which is the actual finding in most organisations and the opposite of what the booking rate suggested.

The size mismatch figure

Average attendance against room capacity, per room, over a quarter.

This single figure drives more useful change than any other meeting room metric.

It typically shows a building full of eight-to-twelve person rooms hosting meetings of two to four, and the response is subdivision rather than construction.

What to do with the findings

Shorten default booking durations.

Release unclaimed bookings automatically after ten or fifteen minutes.

Expire recurring bookings on a cycle.

Subdivide the largest rooms, or convert some to bookable focus space.

Each is cheap and each needs the data to survive the objection.

The thing the data will not show

Why a particular room is avoided.

Acoustics, temperature, a bad screen, a view onto the lift lobby.

Rooms with persistently low use frequently have a specific fixable problem, and no sensor reports it.

Ask the people who book around it.

Unbooked use

Open spaces, corridors, phone booths and corners absorb a large share of short conversations.

Not seeing this makes the meeting room picture look worse than it is.

Instrument or observe at least some of it before concluding anything about demand.

What to check

Do you know your no-show rate and your average attendance per room?

What is your default booking duration?

Which rooms are persistently avoided, and has anybody asked why?

And can you see any unbooked use at all?