The concept of buildings as producers of valuable data is relatively new and multifaceted. As part of our Q2 TRENDS report, we’ve spoken to the experts to break it down and answer the big questions on this hot topic.
What is building data and why is it valuable?
The data a building accumulates through day-to-day automated processes can be harnessed to reveal insights that improve energy usage, operational efficiency, maintenance and comfort.
Until recently, however, gathering and processing the data has been challenging—as has responding to the insight it offers. But things are changing. “The market has evolved and it’s now possible to apply new analytic software to building data,” explains Matt Ernst, commissioning engineer at Burns & McDonnell.
One of the key applications of this technology is energy reduction. “We can use analytic tools to look at data and identify things going wrong or energy being wasted in ways that were previously not obvious,” says Ernst.
Another driver is maintenance. While a building might have thousands of sensors functioning at the same time, it’s not easy for a small team of human operators to understand what’s going on. Analytic software provides a big picture view, so managers can identify issues much faster, and improve the overall comfort of building.
At the same time, new hardware and technology suites are available that gather useful datasets, for example, tracking how space is used in real time and historically, or monitoring the wellbeing of users through personal, connected wearables.
Is my building already collecting data?
Probably. “One of the great things about buildings is that their systems have benefited from years of automation and the standards that go with them,” says Ernst.
Sensors are already set up to gather data; for example, you might already have service desks or humidity monitors collecting various types of data. In many cases, harnessing the data value of a building is about layering software on top of what’s already there.
Plus, it’s a lot more cost effective to use data that already exists.
How do I start extracting value from building data?
As the market evolves, there’s an increasingly diverse set of solutions available.
SkySpark is among the leaders, with software installed in 1bn sq ft across the world – a fact that, according to the company, “further validates the financial benefits of applying data analytics to building and equipment systems to reduce energy and operational costs.”
Others include Copper Tree, which helped Canberra Airport reduce the energy consumed by its chillers by 70%; Iconics, the system of choice on Microsoft’s campus; and OSIsoft’s PI System, which is used to digitally overhaul industrial operations.
Most new analytical software comes with pre-programmed algorithms and rules, making it user-friendly for building owners and facilities managers, who may not have technical training in data analysis.
There are also plenty of off-the-shelf proptech products available to optimise buildings through their data—though navigating the
options can be overwhelming.
Linda Chandler, CTO and co-founder of Liquid Real Estate Innovation advises:
“Start by asking: what is the problem I want to solve, and what business value can be derived from solving it? Then work backwards in terms of the data and technology required.”
How does leveraging building data give me a competitive edge?
Currently, improving energy efficiency is one of the the biggest wins.
“You can use granular data to access unprecedented levels of detail, such as comparing the energy usage of individual wings or different equipment, week to week, day to day, or even mornings versus afternoons,” says Ernst. “Then identify new ways to save energy or come up with new insight to operate more efficiently.”
Plus, as competition for talent continues to grow, for many business owners, creating a responsive, intuitive and comfortable environment, data-driven workplace strategies are becoming the new norm.
What are the challenges right now?
Possibly the biggest challenge at the moment is how to cross-analyse disparate datasets. For example, you might want to look at how temperature or air quality intersects with human productivity—two very different types of data.
“The whole business around data exchange and gaining value is a puzzle that hasn’t been solved in a deep sense,” says Chandler.
Another issue is the long life cycle of the built environment versus the increasingly quick turnaround of technologies. It can be difficult to make long-term decisions about the building fabric when hardware becomes quickly outdated or in need of an upgrade.
“It’s all about investing in the tech that will last longest and can give you the data that’s most valuable to you,” says Chandler.
How is this trend going to develop? Should I wait and see, or is it now or never?
“Real estate management companies, universities and organisations that manage tens or hundreds of buildings have already dipped their toes into data analytics,” says Ernst.
At this point, many companies are grappling with the question of how to transform their new data-driven insights into something useful and effective.
Ernst is confident that in the coming months and years more smaller organisations and building owners will start adopting the technology, too: “People are no longer on the fence about the ROI of digital. For many who run buildings, it’s easier than ever to invest because the value has become a lot more obvious recently.”
“We tend to value the physical asset of a building but not the data asset. We’re at a crucial point now where that is about to change.”