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infrastructure with thousands of sensors in the ceiling. by gateways being the data integration hub, but much
Commonly, wayfinding is done through Bluetooth bea- more can be done by looking at specifically enterprise
cons. For SRR4, we are attempting to use a light signa- data sources. As an industry, we’ve done a pretty good
ture. Individual fixtures send out light at a very specific job starting to get building data integrated, but we’re still
constant frequency and each frequency is different—no a long way off from really marrying building data with
two light fixtures have the same value. We are using that enterprise data and there’s a lot of value there.
data to track occupancy; we can understand location
based on the frequency of light that is being emitted What trends do you see impacting corporate real estate
where they stand. over the next three years?
The key trend is continuing the integration of building
Data is important here; you need to have a database of data and enterprise data. Working at a corporate scale,
the light frequencies—the signature of each fixture, so to you must have the visibility. The marriage of these two
speak. It’s actually being done in retail stores; I don’t think datasets will lead to deeper functional insights that will
it’s ever been done on a general purpose building, but we’re greatly enhance how we manage buildings. It’s the dif-
making progress. ference between selling a product versus a solution that
solves a greater business value proposition. It’s frustrat-
Another area we’ve been focused on is the SRR4 water ing to have all this data but then not doing enough with it.
project. While our technology initiatives need to make Data cannot live on an island all by itself; it must gener-
business sense, it is also absolutely critical we are socially ate value. Our growth as an industry and as individuals
responsible from a sustainability perspective. With SRR4, depends on this mindset. It really can create opportuni-
our goal is to effectively recycle all the water we use in ties for everybody.
a building. We’re deploying an IoT solution that will give
us constant monitoring information about water quality I also see machine learning as being big, because we are
parameters. We must do a lot of manual lab tests, which trying to make sense of tons of data. If machine learning
are very expensive; we are trying to eliminate manual is a success, a lot of the building operations will become
processing through this solution. We are also actively touchless. People interpreting data can be inaccurate.
partnering with the government of India to see if this can This is not to say you get rid of people in a building
be a major trend in the region. That’s happening in APAC operations function, but I think definitely machine learn-
in places like Vietnam, where the government has already ing will make it more accurate and can give us a lot of
mandated it. insight.

What are the technology initiatives you’ll be focusing on
in the next 12 months?
Something we’re actively pursuing is in free-address
solutions. Space is critical, especially in places like India
where the employee population is essentially going
through the roof. The challenge is, while we know that
the typical benchmark is about 60-70 percent occupancy,
until you have hard data, you can’t convince people to give
up their cubes. We are putting in free-address in a big way
in the APAC region.

In the U.S. region, we are looking at fault diagnostics and
detection, because it’s something that has a lot of poten-
tial if done right. FDD is great but if it’s not integrated with
work order management, it really doesn’t mean anything.
If we’re not tracking fault corrections or repairs to com-
pletion we can’t really claim the success. As we expand
this, an integrated view of how our buildings are doing is
very key. After all these years, we still talk about silos, it’s
very real. Part of the integration challenge has been met

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