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Still Counting People? You May Be Missing the Forest For the Trees

Sometimes to solve for big-picture problems like Corporate or Higher Education Real Estate leases that have 3-6 year life cycles, looking at too fine an aperture can actually distract from your ability to notice patterns and trends in office utilization over quarters, semesters, or years. 

When the enthusiasm for the return to office lagged, panic drove workplace leaders into a frenzy looking for any data forms to help alleviate the mounding complexities of hybrid workplaces.

People started considering technologies that count every single person. Much to the chagrin of IT and Facilities Teams, sensors started to appear across campuses for both Higher Education and Corporate entities. These sensors, though highly accurate, gave employees and students alike the big ick. 

But the reality is the minutiae data is irrelevant in major real estate and finance decisions that drive space and capital planning. The exact count of occupants per floor or zone is only relevant if you’re looking for space right this second, not if you’re projecting growth over time or even looking for surge space for a few weeks or months. With seat sharing ratios on the rise and open concepts, the need for square footage per employee isn’t exactly diminishing – it’s as flexible as the employees themselves.

Before you undertake a major hardware installation like sensors across your portfolio, consider the types of questions you’re looking to answer. It may be that what you actually need is floor-level occupancy that feeds into HVAC or Cleaning and Sanitation schedules or that can show you pockets of opportunity for restacking or surge space exists. These data points aren’t available with badge data or scalable with sensors. 

Things to Consider When Evaluating Occupancy Technology: 

  1. How will scale affect your decisions? Multinational corporations with sprawling campuses need a multitude of solutions. As business needs evolve, the agility of the solution and granularity of  the occupancy data needed changes. For example, utilization rates at a small satellite office might present an opportunity for divestment or rearranging departments might open up flex space or save on overall operational costs. 
  2. What level of accuracy is needed? An office manager trying to unlock heavily-trafficked office spaces needs a different view into how many people are using a conference room whereas cleaning service crews can right size staffing with a fairly good estimate. Another example would be HVAC adjustments. Patterns of office usage can help eliminate waste by adjusting heating and cooling to average occupancy at the floor-level. 
  3. What other data sources can add context to your occupancy data? Integrations with occupancy analytics platforms can provide necessary context to turn data into usable insights. If your organization already has cameras, badge data, or scheduling tools this data adds context where more granular data is needed. Some occupancy platforms are closed-loop, lacking the ability to receive contextual information from scheduling systems or other integrations. This can cause analytics to fall short when making short-term decisions about space planning or understanding patterns of underutilization. 
  4. Is the technology dependent on any specific carrier? Be wary of placing technologies that are dependent on specific Wi-Fi network providers or that have closed-looped systems that don’t integrate with external data sources. This can be particularly problematic at organizations with several satellite offices where each office park has a different network provider. In today’s world, the need for flexibility extends into the IT infrastructure world. 

The Importance of Continuous Data in Space Planning

In the tug-of-war between accuracy, speed to insights, and scalability, Wi-Fi based occupancy analytics makes a compelling case for the significance of continuous data in space planning. While 100% accuracy is desirable, studies showing the downsides of point-in-time measurements like badge data emphasize that continuous data, showcasing patterns of office life, holds greater value for space planning needs. Anomalies and surge space needs are inevitable, and by zooming out of desk-level seating, organizations can gain a holistic view of space utilization trends.

Continuous Space Utilization Example: Identifying Space Hoarders 

Meetings and classrooms are ghosted all the time – it happens – last minute conflicts arise and the reservation hold is never canceled. It’s an organic part of hybrid work and learning models. But if these reservation systems are the primary source of truth for space utilization, it becomes challenging to identify gaps between reserved space and utilized space. Leveraging advanced analytics platforms and premier integrations can surface actual occupancy at a level of accuracy that can highlight space hoarding quickly and at-scale in a way counting individuals never could. This will become increasingly important as hybrid work and learning life evolves. 

Occupancy Analytics vs Utilization Rates for Real Estate Planning 

There’s no one-size-fits-all approach to understanding utilization across large corporate and college campuses – dynamic spaces require dynamic space planning tools. Start with an understanding of the types of challenges you’re looking to solve for and identify what level of occupancy analytics is required where. 

If you’re looking to mature your CRE or Higher Education organization’s understanding of utilization and occupancy analytics, Lambent Spaces Sales Directors can help you assess your current needs and match your goals to the appropriate solution. 

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