This post is authored by Daniel Moisescu, a workplace technology strategist and thought leader with deep experience in real estate, IoT, and data-driven facilities management. As a key contributor at Tango, he works at the intersection of product, data, and operations—helping guide product innovation and share insights on how occupancy intelligence and hybrid work are transforming modern workplaces.
Introduction
The way we use office space has changed dramatically. Hybrid work has introduced a level of unpredictability that traditional workplace strategies weren’t designed to handle. Spaces that were once consistently occupied now fluctuate in usage from day to day, and assumptions about how people interact with the office no longer hold true. This shift has made occupancy data more important than ever—not just for facilities teams, but for HR, IT, and real estate decision-makers alike.
Understanding occupancy isn’t limited only to counting people. One must be focused on uncovering patterns—how employees move through a space, which areas are consistently used, and which sit empty despite being booked. It’s also about reconciling different types of data that each tell part of the story. Badge swipes, Wi-Fi connections, Ethernet activity, room reservations, and sensor readings all offer clues, but none are complete on their own.
What the Data Sources Reveal and What They Don’t
Badge data, for example, is ubiquitous and easy to access. It tells you when someone entered a building, but not where they went or how long they stayed. Reservation systems show intent—what people planned to use—but not whether they actually showed up. Wi-Fi and Ethernet data is more dynamic, capturing real-time presence based on device connectivity, but they require a more substantial resource commitment for setup and maintenance. These sources can be surprisingly accurate, especially when combined, but they require careful filtering to avoid counting the same person twice or misinterpreting passive device activity. Sensors add another layer, offering granular insights into motion and people counts, though they come with scalability challenges.
To make sense of all this, it helps to think in terms of structure. Occupancy data can be broken down by what is being measured (people, seats, spaces), where it’s being measured (building, floor, zone, room), and how it’s being aggregated (average, peak, unique counts). This framework allows organizations to ask more precise questions, like which meeting rooms are consistently underutilized, or how many unique employees visited a particular floor last week—and get answers that are grounded in actual behavior rather than assumptions.
The real value of occupancy data emerges when these sources are layered together. For instance, combining Ethernet and Wi-Fi data leverages the multitude of devices associated to a user to generate a full picture of office presence and an accurate picture of seat usage—no matter whether people spend most of their time at their desk or in meeting rooms. Adding sensor data to the mix can validate presence in areas such as phone booths, where network coverage is weak.
Turning Insights into Action
These insights have practical implications. They can inform decisions about space planning, such as whether to reconfigure large meeting rooms that rarely fill to capacity. They can support compliance efforts by tracking attendance against hybrid work policies. They can even guide portfolio strategy, helping organizations identify underutilized floors or buildings that could be consolidated or subleased.
Of course, working with occupancy data isn’t without its challenges. Over-reliance on a single source can lead to blind spots. Data may be incomplete, outdated, or distorted by human behavior—think ghost bookings or tailgating through access-controlled doors. Ensuring accuracy often requires validation against benchmarks, thoughtful coverage across different space types, and a clear understanding of what level of granularity is appropriate for each use case.
Privacy and compliance also play a critical role. Different regions have different standards and handling sensitive data like device identifiers or HR records requires careful governance. Successful implementations tend to involve close collaboration between IT, facilities, and HR, with clear communication and shared goals.
Ultimately, occupancy data is a strategic asset rather than a technical one. When used thoughtfully, it can help organizations create workplaces that are more responsive, efficient, and aligned with the needs of their people. In a world where the office is no longer a fixed destination but a flexible resource, understanding how it’s actually used is the first step toward making it work better for everyone.
