By Kathryn Yap - 29th August, 2026

Reading the Room: What Workplace Data Can and Cannot Tell Us

WORKTECH26 Chicago brought workplace, real estate, design, and technology leaders together at Accenture Tower to examine how organizations are making decisions about space as AI, hybrid work, and changing expectations reshape the office. The program focused on workplace intelligence, human experience, and the practical work of moving ideas into day-to-day operations.

Early audience polling surfaced recurring workplace challenges: attendees cited fragmented data, technology complexity, ROI, attendance, culture, and change management as recurring pain points. Many said they were only somewhat confident in their organization’s readiness for the next three to five years.

For PLASTARC, one question carried through the day: with more workplace data available, how do we make sure the numbers actually describe the experience we are trying to understand?

Better tools still need better questions

Accenture’s Xavier Menendez opened with Portfolio IQ, an AI enabled platform developed to analyze the company’s global real estate portfolio. With lease, occupancy, utilization and financial information historically spread across separate systems, portfolio analysis that once required weeks of coordination can now be updated in hours.

Getting there required more than adding AI. Accenture first had to clean and contextualize its data, reconcile definitions, and establish the principles guiding portfolio decisions. AI can then propose scenarios while experienced real estate teams review the results and adjust the logic behind them.

Luke Tanen of Chicago Innovation and Eric Gannon of Gensler then turned the discussion toward the physical workplace. Gannon noted that “60% of our work environments have not been revisited since COVID.” Many organizations have changed schedules, policies, and expectations for work while the spaces supporting those behaviors remain largely the same.

Dr. Tracy Brower of Steelcase focused on connection and belonging at work. She compared offices to gathering places in cities, where repeated encounters build familiarity over time. Team neighborhoods, shared gathering areas, and spaces where people know where to find one another can create similar conditions at work.

Brower also emphasized synchronization. Flexible attendance has limited social value when colleagues continually miss each other. Schedule transparency and shared team days can make presence more useful.

Brower’s discussion of connection also complicated a familiar workplace metric: utilization. If offices are being designed for connection, learning, meetings, events, and collaboration, measuring them primarily through individual desks leaves out much of what the workplace is being asked to support.

What exactly is utilization?

Melissa Marsh, Founder and Executive Director of PLASTARC, moderated Scaling Workplace Intelligence: From Fragmented Signals to Strategic Decisions with Lisette Smyrnios, Managing Director of Global Workplace at Accenture, and Angie Bilstad, Senior Director of Campus Strategy and Design at Northwestern Mutual.

The two organizations offered very different conditions. Accenture manages a large global portfolio informed by occupancy sensors, Wi-Fi, badge data, reservations, and employee feedback. Northwestern Mutual has been centralizing employees into its Milwaukee campus while asking how to measure whether those spaces support culture, community, connection, and collaboration.

Marsh brought the conversation back to a basic question: “What exactly is utilization?”

Smyrnios showed how much the answer depends on the denominator. At Accenture Tower, average daily visits were 383.4. Measured against 614 individual “Me” spaces, attendance is 62%. Accenture also calculates the maximum capacity using 25% of collaboration and meeting spaces. That brings the denominator to 1,012 and changes the same attendance figure to 38%.

Both percentages describe the same building and attendance level; the difference comes entirely from how capacity is defined.

Marsh extended the discussion with PLASTARC’s “Your inputs defines your metric” framework. The numerator might represent total people present, peak staff, or average staff and guests. The denominator might include workstations and offices, individual enclosed spaces, or all available seats. Each calculation describes a different aspect of how the workplace is being used.

PLASTARC’s Experience Density example makes the difference visible. In the illustrated floor plan, 34 people are present among 36 traditional workpoints, producing 94% occupancy. Measured against 76 available seats, including shared settings, Experience Density is 45%.

The 94% figure suggests a nearly full floor, while 45% better reflects how much shared seating remains available.

Guests matter too. Clients, event attendees, and other visitors use real estate and contribute to how active an office feels, even when employee-based measures leave them out. For PLASTARC, the value of utilization metric comes from knowing what is counted and why.

The numbers need context

Smyrnios described a case where leaders focused on peak periods of attendance and began considering additional space. Looking across the full week and examining dwell time changed the picture. Other days were lighter, and employees were not necessarily staying for an entire workday. Better use of the existing workplace made more sense than expansion.

As Smyrnios put it, “You can't just look at one lens of data.”

Bilstad offered the inverse example. Utilization data suggested Northwestern Mutual could support desk sharing. Employee feedback showed that moving desks created a recurring “time tax" as people reset their workstations and dealt with the friction of moving. The organization gave that experience weight in the decision.

Sensors and badges describe patterns of use, while interviews, surveys, observations, and direct feedback help explain what those patterns mean to people occupying the space.

Bilstad also returned to the issue of data integrity: “Garbage in, garbage out.” Workplace teams need to understand how information is gathered and defined before treating a dashboard as evidence.

Scaling the learning

The panel closed with two different approaches to scale.

Accenture is shifting toward office segmentation. A flagship location designed for client events and large internal gatherings serves a different purpose from a mid-market office or a large delivery center. Space and services can respond to those differences while maintaining a recognizable Accenture experience.

Northwestern Mutual is applying the same learning process within one campus. Its team tests layout and behaviors, documents the results, and connects each experiment back to principles for employee experience before deciding where the idea should be repeated.

In both cases, what scales is the learning. The spatial response can still change by office, building, or workforce.

Final Reflections

WORKTECH26 Chicago made clear that workplace data is most useful when it is read alongside context and lived experience. AI can speed up analysis, and newer metrics can account for more of what happens beyond the desk. The harder work comes earlier: deciding what to measure, defining the inputs carefully, and checking whether the resulting number matches how people actually use the space.