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Transcript
- Lucas: You know how every time you walk into a WeWork, you tap your phone or badge at the door? Luna: Yeah, I've done that hundreds of times. Lucas: That tap generates data. And not just for security — it feeds into a massive dataset that's now being used by Fortune 500 companies and landlords to predict office demand. Luna: Wait, so my coworking check-in is helping some corporate real estate team decide whether to renew a lease? Lucas: Exactly. And it's getting very granular. We're talking floor-level occupancy rates, peak usage hours, even which desk configurations people choose. That data is becoming a commodity. Luna: So coworking spaces aren't just office rental — they're data brokers now? Lucas: In a way. But it's more nuanced. Let me give you a concrete example. There's a Fortune 500 tech company — I won't name them, but they're based in the Bay Area — that had a ten-year lease coming up for renewal on a 200-thousand square foot building. Before deciding, they ran a pilot: they put a hundred employees in a coworking space for six months and tracked everything. Luna: Everything? Like, badge swipes and meeting room bookings? Lucas: Yes, plus Wi-Fi connection data, seat sensor data, even pantry traffic. They found that their peak desk usage never exceeded 45 percent. The coworking operator gave them a heat map showing that most people came in on Tuesdays and Wednesdays, and almost nobody on Fridays. The company used that to negotiate a much smaller lease — they cut their space by 60 percent. Luna: So the coworking data saved them millions. But who owns that data? The company that paid for the pilot, or the coworking operator? Lucas: Great question. In this case, the company owned the aggregated data, but the operator owned the raw data. That's becoming a standard split. But it gets messier when you consider that the operator might combine data across clients to create broader market insights and sell them to landlords. Luna: And the employees? Did they know their movements were being tracked? Lucas: That's the privacy angle. Most coworking membership agreements include a clause about usage analytics, but it's buried. And employees in a pilot might not read the fine print. I think as this practice grows, we'll see more scrutiny — especially in Europe under GDPR. Luna: Right. So there's a tension between the value of the data for real estate decisions and the potential for surveillance. Lucas: Exactly. And it's not just coworking. Traditional office landlords are starting to install sensors too. JLL and CBRE are both offering analytics services that aggregate data from multiple buildings. They can tell you, for example, that office space in downtown Chicago is only 38 percent utilized on average. Luna: That's a huge shift from the pre-pandemic world where occupancy was assumed to be near 100 percent. Lucas: Right. And it changes how leases are structured. We're seeing more 'space as a service' deals where rent is partially tied to usage data. If you use less, you pay less. That's a radical departure from the traditional triple-net lease. Luna: So the data isn't just informing decisions — it's being built into the pricing model. Lucas: Yes. And that's where it gets really interesting. One coworking operator — Industrious — has started offering what they call 'demand-based leasing.' They share anonymized booking data with landlords to justify variable rent. If a building's average occupancy drops below 50 percent for two quarters, the rent drops. No negotiation, it's contractual. Luna: That's wild. But it also means the landlord is taking on occupancy risk that used to fall on the tenant. Lucas: Exactly. It's a risk transfer. And it's only possible because of the data. Without granular occupancy numbers, you can't write that contract. Luna: I want to circle back to the privacy piece. Are there any guardrails being put in place? Lucas: A few. The General Data Protection Regulation in Europe requires that data be anonymized at the point of collection. Some operators are doing that. But in the US, there's no federal law governing workplace data. A few states have introduced bills — California's Consumer Privacy Act gives employees some rights — but it's patchwork. Luna: So if I'm an employee in a coworking space, my movement data could be sold without my explicit consent? Lucas: It depends on the operator. WeWork, for example, has a privacy policy that says they use data for 'operational analytics' and 'improving services' — which is vague enough to cover a lot. They also have a B2B product called WeWork Workplace that sells aggregated insights to corporate clients. They claim it's anonymized, but we know that re-identification is possible with enough data points. Luna: That's unsettling. But at the same time, the data clearly has value for companies trying to optimize their real estate footprint. Lucas: Right. And that's the tension we're living with. The genie is out of the bottle. The question is how we regulate it. Luna: It feels like this is an area where the technology is ahead of the law, and the law will take years to catch up. Lucas: That's often the case with tech. But there's a push from some industry groups to create a voluntary standard — something like a 'Workplace Data Bill of Rights' that operators could commit to. Luna: I'd like to see that. Because I think the data itself is really valuable — it could help companies save money and reduce wasted space — but it has to be done transparently. Lucas: Absolutely. And one thing we should mention: the use of this data isn't limited to big corporations. Small businesses that use coworking spaces can also benefit. A three-person startup in a coworking space gets access to the same aggregated data about peak times and popular areas, helping them decide when to come in and where to sit. Luna: So it democratizes real estate intelligence. You don't need a giant corporate real estate team to get these insights. Lucas: Exactly. And that's the promise. But it only works if the data is used ethically. Luna: Before we wrap up, I want to touch on something you said earlier about the data being a commodity. Are there any startups specifically focused on aggregating coworking data? Lucas: Yes, there are several. One is called Spacebase — they aggregate booking data from hundreds of coworking spaces and sell it to real estate investors. Another is Equiem, which focuses on tenant experience data. And then there's a company called Locatee that does workplace analytics for traditional offices, but they're now moving into coworking. Luna: So it's becoming its own little ecosystem. Lucas: Definitely. And I think we'll see more M&A activity as larger real estate firms try to buy their way into the data game. Luna: That's fascinating. And speaking of staying ahead of trends, this is exactly the kind of deep dive we love to bring you on this show — no ads, no sponsors, just the stuff that matters. Lucas: Yeah, we keep Future of Work Tech ad-free because we think the topic deserves a clear, honest conversation. If you find value in these episodes and want to support that mission, you can do so at buy me a coffee dot com slash fexingo. Luna: Even a small contribution helps us keep the lights on and the research deep. And we genuinely appreciate everyone who's already chipped in. Lucas: So back to coworking data — one last angle I want to explore. How do you think this data will change the design of offices themselves? Luna: I think we'll see more flexible layouts informed by actual usage patterns. Instead of rows of cubicles, you'll get modular furniture that can be reconfigured based on data. Lucas: Exactly. Some architecture firms are already using occupancy data to design buildings with moveable walls and adjustable floor plans. The building becomes a kind of responsive system. Luna: That sounds like the office of the future — literally shaped by data. Lucas: And the data is coming from the coworking spaces that pioneered this model. So in a way, the coworking industry is the laboratory for the future of all offices. Luna: I think that's a great note to end on. Thanks for listening, everyone. We'll be back next week with another deep dive. Lucas: See you then.