There’s a lot to be gained from a smarter use of space.
We’ve all been there. Scrambling around the hallways trying to find a free meeting room. When you finally find an unoccupied room, the relief is short-lived as you discover that the room is reserved. Do you claim the room hoping that the person who reserved the room won’t show up? or do you continue the hunt for a free room?
No-shows – i.e. when a meeting room is booked but for some reason not used – is a common phenomenon in most large offices. From our conversations with facility management companies it seems that 30-35% no-shows is a industry average. Think about that. A third of all booked meeting rooms result in a no-show.
These booked-but-unused rooms not only worsen meeting room congestion, they also impede the real estate utilization and ultimately lower the productivity of the organization by hindering the employees from doing their job.
Surely there must be a way to solve this?
There are several different methods of solving the no-show problem. One of the more common approaches is to use room displays — tablet-like touch screens that display booking status — mounted outside the meeting room. When the person who reserved the room arrives, he or she checks in on the tablet to confirm their reservation.
If the person who reserved the room fails to check in after a certain amount of time — an industry standard seems to be 15 minutes — the reservation is canceled, and the room is now free for others to use.
This may ease the congestion somewhat, but at the end of the day it’s a suboptimal solution. The room is released yes, but now there’s only 45 minutes left on the hour. And what about those people who were looking for a room just before 2 o’clock? They gave up and rescheduled since there were no rooms available at the time.
Releasing rooms is a step in the right direction, but the real value is only realized when someone else is actually using the room.
Fifteen minutes before, not fifteen minutes after
What if that room had been released 15 minutes before 2 pm instead of 15 minutes after? The total availability of the room would have been 60 minutes instead of 45 minutes. But more importantly, more people would have had a chance to reserve it in time since it was released 15 minutes ahead of time, just when the pressure to find a room for 2 pm is at its peak. We call this the Law of Early Cancellations.
The Law of Early CancellationsThe earlier a room is released, the higher the chances that it will actually be used.
This is what we’re aiming for — to release the rooms as early as possible. Ideally, no room should be released later than 15 minutes before the meeting would have started.
Our approach is to make smart use of the available data to predict, identify and terminate no-shows before they even happen. That is, not just detect that a no-show has happened, but understand why no-shows happen and prevent them.
A Transatlantic Prediction
To illustrate how data can be used to predict a future no-show let’s look at a simple example.
Adam is on a business trip in London but has a recurring room reservation in his home office located outside Chicago. Since this room will most likely not be used by him, we can prompt and nudge Adam as to whether he’d like to cancel the reservation. With a tap on his smartphone, the room in Chicago is released.
Why wait until Adam fails to check in when it’s possible to release the room before his coworkers have even had their first cup of coffee?
>> Read more about nudging people for a smarter use of the office
It might sound self-evident but not being present in the office is a common reason for no-shows. The above example illustrates one of the most rudimentary ways to predict a no-show – measuring the distance between the user and the meeting room. This concept works on smaller scales as well. If Adam instead was in another part of Chicago, it still makes sense to prompt him about the reservation.
Measuring distance to meeting rooms is one way to catch no-shows. But for different situations there are other, more sophisticated ways to gauge whether a room will be used or not.
Making smart use of data at hand
The key is for the system to understand the context of the user. In the example above, the context is understanding that Adam is in fact 4,000 miles away from Conference Room C41, and probably won’t make it in time. In an ordinary office environment, there are other inferences that can be made by understanding the context of the specific user.
The “secret ingredient” that makes our smart office solution Senion at Work especially good at this is our own proprietary indoor positioning technology. Your current location is a strong predictor of your context. Which office are you in? What floor? What room of that floor? With this information (and more) Senion at Work can make qualified guesses as to whether you’re likely to use that room you reserved.
Our notion is that a no-show is not a building problem, or a meeting room problem, it’s a people problem. We can’t solve no-shows by just focusing on the building – the key to the solution is contextual understanding of the end-user. Where you are, what other reservations you may have (eg. double bookings), if there are meetings you tend to cancel late, if you are on vacation, parental leave or even have left the company (yes that happens!) are all examples of information that can be useful to predict no-shows. Taking this information into account makes it possible to not just detect no-shows but to prevent them from happening all together.
A quick note on user privacy
While Senion at Work uses location data to provide smart services in the office, the user’s location data never leaves the phone.
Here’s how it works: the location is calculated on your phone and and is used to understand what you may or may not do next. This location is not saved and never leaves the phone. If you choose to cancel a reservation, the room booking server will only recognize that you did cancel, not where you were or why you did it.
So in summary
- No-shows are a common problem that lead to inefficiencies in real-estate and productivity.
- Most solutions rely on canceling room reservations 15 minutes after a no-show has occurred. This approach is unsatisfactory as releasing the room 15 minutes after is at least 30 minutes too late.
- In contrast, Senion at Work makes smart use of available data to predict and eliminates no-shows before they happen.
- The key to better predictions is to understand the context of the user.
- Indoor location is the secret sauce to better contextual intelligence.