Local Market Dynamics Are Key for Benchmarking and Comparing Costs Across Locations

In a world of hybrid work and low space utilization, a workplace that is well-utilized and appropriately sized for local market expectations can be highly cost-effective—even with a high cost per sq. ft./sq. m.—making utilization adjustments critical when comparing costs across locations. Benchmarking sq. ft./sq. m. per average daily peak attendance at the market level allows calibration of a portfolio’s performance, as perceptions of how density affects the experience can vary significantly by market.

Benchmarking Reports Are Not Created Equally

When accessing a benchmark resource, it is critical to understand the scope, methodology and what the data tells you relative to your peers or pre-pandemic metrics. Scope may include how many buildings, cities and organizations are represented by the report and data collection date range. When evaluating methodology, look at how calculations and metrics are used; whether the calculations are summarized, averaged or otherwise transformed; and what the benchmarking is attempting to communicate. To navigate a dynamic landscape of space needs, organizations must first understand space occupancy and effectiveness. Top organizations evaluate various data sources—such as occupancy sensors, surveys and benchmarking tools—to monitor employee engagement and competitiveness of their space. Combining this information with predictive analytics provides actionable data for CRE teams.

Workplace Effectiveness is Redefining How We Measure and Improve the Workplace

High-performing workplaces evaluate four key metrics: employee experience, organizational dynamics, financial performance and ESG. This requires robust and varied data from numerous sources. By leveraging AI, combined with a feedback loop for continuous improvement, this data can help CRE teams determine their workplace effectiveness score and prioritize capital projects. AI data models can also provide insights into anticipated future space needs by analyzing key time-sensitive activities within a building, such as cross-functional team meetings or events. This improves efficiency and decreases human error by providing a unified system to understand and manage various building services like janitorial and catering, instead of accessing different siloed systems.

Since the pandemic, the mandate for Corporate Real Estate has changed: It is no longer a remit for standardization, efficiency and performance. Organizational leaders now expect real estate to align with strategic business objectives and reframe and change the terms of decision making beyond cost and risk.

Three Ways AI Can Enhance the Workplace and Visitor Experience

1. Delivering a positive and memorable guest experience by evaluating past interactions to prepare, greet and manage the end-to-end visitor journey.
2. Forecasting expected space demand throughout the day using occupancy utilization data, event planning/booking schedules, visitor data and other data sources to ensure team members are tasked and stationed in the right place at the right time.
3. Maintaining occupant satisfaction with timely intervention and recommendations during potential building and service status changes, such as meeting space schedules, catering deliveries and janitorial services.

Critical Domain Elements Are Driving the Need for Data Governance, Quality and Standardization

Advancements in data science and the increasing application of AI in CRE functions necessitate a robust data governance, quality and standardization program to manage an organization’s critical data elements (CDEs). CDEs are an integral, irreplaceable component of an organization's data governance program used by various CRE domains—such as facilities and portfolio management—for key decision-making, operations, transactions, regulatory compliance, cost savings and innovation.