How occupancy analytics can finally put an end to wasteful offices

Workplaces have always been wasteful: empty offices with lights blazing, computers whirring overnight, giant meeting rooms warmed for a party of two. Taken individually, these examples may seem small but for larger businesses, the impact can quickly add up. An enterprise with $10 billion in revenue, for example, can spend $500 million a year on energy. Across commercial and industrial sectors, building energy waste costs an estimated $60 billion a year. The environmental cost, of course, is similarly problematic.

The issue is compounded by new mobility trends. People are not using workplaces like they used to. With remote work the new norm, workers come in at unpredictable times of the day, and offices are no longer nine-to-five operations. Building managers now face the near-impossible task of maintaining a clean and comfortable space without any clear way to predict when and how that space will be used.

“We’ve been trying for at least 20 years to control building systems based on actual occupancy”

– Clayton Miller, leader of the University of Singapore’s Building and Urban Data Science (BUDS) Lab

Carbon dioxide sensors have been a key technology from the start, providing a picture of how many people are in a given space based on CO2 buildup. “These systems save energy as long as the sensors are operating properly,” explains Miller. “But CO2 sensors are notorious for drift and miscalibration, so once sensors start failing, operations staff often switch them off.”

When we talk about a building’s efficiency, we tend to lump together two distinct areas of a building’s energy performance. The first is how efficiently its systems run. The second is conservation, or the savings made by switching off power when it’s not required. “I think conservation has the most potential for saving energy, at the lowest cost,” says Miller. “Energy auditors often focus on the efficiency side, because that’s something they can control, by replacing or upgrading equipment, for example; but they don’t have the confidence or power to tell people to use their building differently.” That’s because, in most cases, the data simply isn’t available.

Focusing on well-oiled equipment while ignoring the low hanging fruit of conservation significantly limits how much energy we can save. Or as Miller puts it: “It’s like having a super efficient car that you drive around in circles all day.”

It’s not just energy that’s squandered in wasteful workplaces. At a time when 37% of knowledge workers visit the office four days or less every week, company cafeterias increasingly struggle to predict how much food is required, and when. As well as adding unnecessary cost, corporate food waste contributes to the 60 million tons of produce (worth $160 billion) that’s thrown away each year in the US, clogging landfill and creating more climate pollution than all the cars in Georgia.

“37% of knowledge workers visit the office four days or less every week”

Many counting on technology to drastically improve conservation efforts and reduce waste. Until recently, however, our space utilization systems have been difficult to maintain – like the CO2 sensors – or raised privacy concerns, such as camera-based setups. New advances in machine learning and computer vision have made accurate, anonymous people count possible. At Density, we’ve leveraged the technology to track workspace occupancy both historically and in real time.

We mount the devices above entryways in corporate offices and help companies figure out how their assets perform. How are people using conference rooms and cafeterias? How busy are the spaces in a building when they’re in demand and, in some cases, when they’re not used at all – even though they’re being paid for?

In addition to the devices, we use a simple API that can be used to integrate into other systems. We feel that this type of open ecosystem is both scalable and accessible to building owners and facilities managers, who get a true picture of how offices are used and when they are populated and provide the right resources at the right time.

Simply knowing how many people are in a space, in a given moment and over time, is the key to cutting energy, reducing waste and improving user experience. One Fortune 500 company used our technology to discover that just 25% of employees come to the office on Fridays, yet their culinary team was regularly purchasing to cater almost three times that number.

“25% of employees come to the office on Fridays, yet their culinary team was regularly purchasing to cater almost three times that number”

In our new, flexible work culture, it’s not enough to make assumptions about how and when office space and facilities are used. We need hard data. “Co-working, hot-desking, and remote working all make demand control much more important,” concludes Miller. Understanding how a building is used is not only useful for the people who design and operate them, but also those who populate them. He envisions systems that act like an Uber or Airbnb for workplaces. “You can tell people how they can use the building: What space is sunny and quiet, where it’s a little bit breezy with an open desk… Even more interesting than controlling the systems is empowering people with information about spaces that match their comfort preferences.”

The agile, data-driven workplace is one where efficiency, optimization and responsiveness intersect seamlessly. And with the missing piece of the space utilization puzzle finally in place, it’s time to start reaping the financial, environmental and experiential rewards.

This article first appeared in PropModo.