How to Quantify the Financial Impact of Ghost Floors in Corporate Buildings

Data sources for occupancy measurement (pros and cons)

Badge and access logs

• Pros: existing infrastructure, person-level events.
• Cons: doesn\'t capture visitors or non-badge movements; privacy concerns if misused.

Wi‑Fi and BLE (device) data

• Pros: broad coverage, passive.
• Cons: device-to-person mapping is imperfect; variable accuracy.

Desk booking and calendar systems

• Pros: reflects planned usage.
• Cons: doesn\'t confirm actual presence; can overstate occupancy.

Manual counts and headcounts

• Pros: accurate snapshots.
• Cons: labor-intensive; limited temporal coverage.

Environmental and HVAC sensors (CO2, motion)

• Pros: useful proxies for presence and density.
• Cons: can lag actual occupancy; affected by ventilation.

Privacy-first people sensing (thermal, anonymous)

• Pros: accurate, high-frequency presence data without cameras or personally identifiable information; suitable for continuous monitoring.
• Cons: requires deployment and integration.

A practical step-by-step method to quantify financial impact

Step 1: Define the time window and analysis granularity

• Use a representative period (e.g., 90 days) that covers typical work patterns and seasonality.
• Choose granularity (hourly, daily) aligned to your decision horizon.

Step 2: Establish baseline occupancy and utilization

• Collect continuous occupancy data per floor using one or more sensors.
• Calculate average daily occupancy, peak occupancy, and utilization percentage during core hours.

Step 3: Inventory floor-level costs

• Direct operating costs: energy, cleaning, maintenance, elevator service, security, insurance.
• Allocable fixed costs: property taxes, common area maintenance (CAM) if applicable.
• Capital and opportunity costs: depreciation or cost of capital for space that could be monetized.
• Incremental variable costs: supplies, on-demand services tied to presence.

Step 4: Allocate costs to floors and occupants

• Break down total building costs to a per-floor basis using allocation rules (e.g., area, service consumption).
• Compute cost per sqft and cost per occupant at current occupancy levels.

Step 5: Compute the vacancy-adjusted cost and financial exposure

• Vacancy-adjusted cost per occupant = (Floor cost) / (Average occupied sqft or occupants).
• Annual financial exposure = Floor cost × proportion of time floor remains unused.

Step 6: Model remediation scenarios

• Consolidation: shift occupants to other floors, reduce leased area, and quantify net savings after relocation costs.
• Sublease: estimate achievable rent and subtract subleasing transaction and fit-out costs.
• Repurpose: convert to revenue-generating space and model capex vs. revenue.
• Mothball: shut down systems, calculate reduced operating costs and reactivation costs.

Step 7: Compute core financial metrics

• Annual savings for each scenario.
• Payback period = One-time implementation costs / Annual savings.
• Simple ROI and, if warranted, NPV using your organization\'s discount rate.

Step 8: Sensitivity analysis

• Vary key assumptions: achievable sublease rent, occupancy growth, energy costs, and conversion capex.
• Identify break-even points and robust strategies across scenarios.

Costs to include (detailed)

• Energy and utilities: heating, cooling, lighting, and standby loads for unoccupied areas.
• Cleaning and janitorial contracts: usually charged per floor or sqft.
• HVAC and mechanical maintenance: filters, preventive maintenance, zone controls.
• Security and access control: staffing or monitoring for vacant floors.
• Insurance and property taxes: proportionally attributable to the floor.
• Depreciation and capital costs: structural and finishing maintenance to keep lease-ready.
• Opportunity cost: foregone rental revenue or alternative uses of the floor.
• Transaction and conversion costs: fit-out, MEP adjustments, tenant improvement allowances for subleasing or repurposing.

Improving measurement accuracy

• Use continuous, anonymous sensing for persistent visibility; thermal or camera-free people sensing provides occupancy counts without collecting PII.
• Calibrate sensors with spot checks and cross-reference multiple data sources to reduce bias.
• Monitor over multiple months to account for seasonality, special events, and hybrid schedules.
• Segment by zone: perimeter vs core, meeting rooms vs open plan, to identify micro-ghost zones.

Practical considerations and pitfalls

• Don\'t conflate planned vacancies with ghost floors; planned renovations or phase-outs require different accounting.
• Over-reliance on one data source can mislead; triangulate across badge logs, sensors, and booking systems.
• Understand lease terms and landlord-imposed minimums—some floors may not be releasable or sublet without consent.
• Consider employee experience and business continuity; savings that degrade culture or productivity may cost more long-term.

Actionable next steps

• Run a pilot: instrument 1–3 candidate floors with occupancy sensors for 60–90 days.
• Build the cost model: compile floor-level operating costs and allocate them consistently.
• Model scenarios: compute savings, paybacks, and sensitivity ranges for sublease, consolidation, and repurpose.
• Decide and act: pick the option with acceptable ROI and organizational alignment; monitor performance post-implementation.

Conclusion

Ghost floors are more than an aesthetic or managerial annoyance; they represent tangible financial and strategic exposure. By combining continuous, privacy-respecting occupancy sensing with a straightforward cost model and scenario analysis, real estate and facilities teams can quantify the financial impact and make evidence-based decisions.

Start with a short pilot, focus on clean occupancy data, and use clear financial metrics—annual savings, payback, and ROI—to drive the next steps in portfolio optimization.

About Butlr: Butlr provides privacy-first, camera-free people sensing and spatial intelligence for buildings, enabling accurate occupancy measurement without capturing personally identifiable information. Their technology supports the continuous occupancy data that facilities and real estate teams need to identify ghost floors and quantify financial impact.