The proliferation of data about the built environment is supporting a new level of visibility into the supply chain for real estate. As designers learn from this data, workplaces will continue to become more flexible, diversified, and responsive.

Start counting in zettabytes

The quantity of data generated worldwide every day is staggering, and increasing all the time. A study by SeaGate projects that by the year 2025, the world will have 175 zettabytes of data, (a zettabyte is equivalent to a billion terabytes). Much of it will be media, but one of the most rapidly growing segments is secondary or trace data generated by objects, from phones to buildings systems to sensor networks.

Already, many of the activities we perform each day leave behind trace data. Making calls, sending emails, and browsing the web leave footprints, of course. To an increasing degree, so do less obvious actions like entering a building (via badge swipe or facial recognition), turning on the lights, adjusting the temperature, or even talking to the voice-enabled coffee machine. Every interaction with a building system or connected device—which, with the impending rollout of 5G, may soon be just about everything—generates data. Much of that data collection happens seamlessly, without our awareness.

Why collect data about so many things that seem non-essential to work? For one, much of it can be turned right around to improve the experience for people who use a space. Data about a user’s location can be used to adjust their schedule for the day. Knowledge of their preferences can make sure that the conference room lighting is already just the way they like it by the time they walk into the room. That talking coffee maker can have coffee ready to go.

Beyond these immediate improvements to the experience, the proliferation of data offers an even bigger benefit: it creates a more responsive market. In the past, decisions about what to build might be made using out-of-date, even years-old information about what people want. The data capabilities that have evolved over the last few years have offered a much faster feedback loop. Occurring along with the combination of growth in supply (new building fueled by a period of economic growth) and a simultaneous surge in demand (savvy occupants who are demanding better workplaces), this has turbo-charged the evolution of  commercial real estate.

Big data informs supply chains

Long before people had Amazon accounts connected to their purchases at Whole Foods, companies were using aggregated trace data to improve their products and services. By collecting data about what people bought, retailers such as Target generated insights that improved their sales and optimized their selection of products. These effects propagated through the whole supply chain, guiding the development of consumer products.

Just as more data supports the evolution of a consumer product supply chain, more data about the physical environment will contribute to its growing diversity and responsiveness. For example, data showing that people want more flexible desking gives rise to office products that fulfill that need. Knowing that occupants strongly desire more control over temperature creates a business case for apps like Comfy and building systems that can deliver that. The result is the birth of whole ecosystems of products and services that then generate data of their own, which feeds back into the cycle.

The evolution of the workplace is likely to continue to accelerate as more companies see the benefits of using social data in their approach to workplace. The term “learning curve” is thrown around in casual conversation as a way of speaking about how difficult it is to learn to do something new, but it actually refers to something slightly different; as more people engage in a certain practice, the entire community gets better at it, and the costs also fall. So, what may be costly and rare in the first few years of the smart office will become cheap and ubiquitous.

Better spaces—and space types—to come

One of the best ways to test a space is to see whether people are using it. Especially in a contemporary work environment or a public setting, people will physically be in the spaces that they like and that work for them. They will tend to avoid the spaces that they don’t like, or those which aren’t comfortable, engaging or desirable. This is a good thing, provided people are given the opportunity to choose where to sit. As we shared at ROOM’s inaugural event in its speaker series, the autonomy to choose and control one’s environment contributes to both wellness and satisfaction. It also provides employers with an opportunity to use the workplace as a tool to both study and improve human performance.

In traditional offices, a person who didn’t like the spaces provided by their employer had two choices: live with it or find a new job. At the same time, employers might have had a difficult time figuring out what their employees wanted from the work environment or why they might be unhappy in their job. For example, is that colleague who is grouchy all the time really a difficult person, or are they simply irritated because their environment is distractingly noisy? In the past, the paucity of data about these human factors was partially caused by a lack of sufficient measurement technology. The environments themselves are also to blame; it’s not very meaningful to collect data if the office environments being compared all look and feel the same.

Conference room PLASTARC

In the modern workplace, optimizing your space through data is a crucial way to reduce wasted real estate.

Coworking has changed this dynamic, offering occupants the ability to choose their own spaces to suit their needs. The result is a consumerization of the office environment. The design and functionality of the workplace are now directly subject to market forces, turning the work environment into a product. As people “consume” space by using it, providers and employers can study the choices they make through the lenses of cognitive and social science, yielding increasingly granular information about what occupants want. Future designers can then use that data to create better environments.

Space planning gets agile

Pilot programs and design iteration in the built environment are both much easier to do than they were just a few years ago. If, for instance, a workplace with a large portfolio of open plan office space is considering adding mobile phone booths, they can try them out in one space, then collect very detailed data about how people use them before expanding company-wide.

The same is true of changes to desk arrangements, conference rooms, or other amenities. Direct feedback from occupants—such as surveys—and observational research about how spaces are actually used can be combined with the “big data” from the digital layer to paint a full picture of the occupant experience. This helps shift the conversation about how success is measured in the workplace from one about productivity to one about maximizing human performance.

The massive expansion of data capabilities in the built environment means that workplaces can become more flexible, diversified, and responsive. Occupants will benefit from the choice that comes from the consumerization of space. Developers, owners, and facility managers stand to gain a valuable new tool with which to build the workplaces that people want to use.

Melissa Marsh is Founder and Executive Director of PLASTARC, a social research, workplace innovation, and real estate strategy firm. She is also Senior Managing Director of Occupant Experience at Savills. Her work leverages the tools of social science and business strategy to help organizations make more data-driven and people-centric real estate decisions. Combining quantitative and qualitative research with architectural expertise, Melissa is dedicated to shifting the metrics associated with workplace from “square feet and inches” to “occupant satisfaction and performance.”