Introduction:

For commercial real estate owners and operators, providing outsized value to existing and potential tenants are key initiatives in today's competitive market. One simple way to provide value to occupiers is ensuring they use their space efficiently (i.e., there’s minimal unused and underutilized space within their leased demise). This used to be a rather simple calculation based on headcount and target workplace density numbers. However, the rise of hybrid work/WFH has made understanding actual space utilization more critical (and complex) than ever. This post explores how data-driven insights, moving beyond traditional occupancy metrics, are essential for creating efficient, customer-centric workspaces that drive ROI.

Beyond Occupancy: The Power of Utilization Data

Traditional CRE metrics like capacity, vacancy percentage, and design density focus on planned space usage. While valuable in conventional office settings where every occupier uses their office uniformly, these metrics can fall short in the hybrid era. Today, actual space utilization must be understood. Hybrid work models introduce greater variability in space demand, making utilization data crucial for informed decision-making. A recent study found that 80% of organizations have adopted hybrid/WFH, creating unprecedented variability in tenant workspace needs (Source: Gallup), highlighting the need for data to guide these transformations.

Why Measuring Actual Utilization Matters: A Competitive Edge

For owners and operators, utilization data is more than just a metric; it's a strategic tool. It reveals how customers actually use different workspace types, enabling:

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• ‍Optimized Space Allocation for Maximum ROI: Identify unused and underutilized areas for repurposing or elimination, leading to significant cost savings and increased NO.
• Enhanced Customer Experience for Increased Retention: Tailor workspace design to meet the needs of a more fluid workforce, creating a more attractive and productive environment that fosters customer loyalty. Just like other industries (hotels, airlines, power grids) prioritize customer preferences, CRE should strive to segment customer needs.‍
• Data-Driven Decision Making: Rejecting Anecdotes: Move beyond gut feelings and anecdotal evidence. Base real estate decisions on concrete, first-party data. This is the "crawl, walk, run" approach to becoming truly data-driven – start with collecting the data, then analyze it, and finally, act on the insights.

Collecting Utilization Data: Practical Approaches

‍Several methods can be used to gather utilization data:

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• ‍Badge Swipes: Track building and room access.‍
• Wi-Fi and Network Analysis: Monitor device connectivity to understand space usage patterns.‍
• Sensor Technology: Implement ceiling-mounted area sensors or threshold sensors for real-time occupancy data.

The Future of Space Utilization: Predictive Analytics

‍Beyond simply measuring actual utilization, the next frontier in CRE will be leveraging data to predict future space needs. By integrating utilization data with other datasets (e.g., rent rolls, floor plans, hybrid work policies, project timelines, even external market trends), demand can be forecast, and strategies can be proactively adjusted. This is where data science truly intersects with CRE, opening up exciting possibilities for optimizing occupier efficiency and maximizing ROI delivered to customers. Imagine being able to dynamically adjust lease terms or reconfigure spaces based on reliable predicted demand – this is the power of predictive analytics in CRE, giving owners and operators a significant competitive advantage.