Hot-Desking Allocation and Sanitization Scheduling Automation

This automation eliminates the manual, error-prone process of managing flexible seating and reactive cleaning. It ingests employee preferences, team adjacency requirements, and real-time bookings from systems like Microsoft 365 or Google Workspace. An optimization agent then assigns desks to maximize density and collaboration, while occupancy sensors (e.g., via PoE or IoT) confirm usage. The operational upside comes from a 15-25% increase in seat utilization, reducing required square footage, and eliminating the labor cost of manual desk management and cleaning dispatch.

Implementation requires integrating the orchestration layer with the building's IoT sensor network, identity and access management (IAM) system, and computerized maintenance management system (CMMS). The architecture must include approval gates for management overrides, real-time dashboards for facilities teams, and exception routing for cleaning delays or sensor faults. Rollout is sequenced by floor or department, with controls to ensure data privacy (anonymizing occupancy data) and governance over the optimization rules to prevent unintended exclusion.

This workflow automates the daily operational bottleneck of manually assigning desks and scheduling cleanings in a hybrid workplace. It eliminates administrative overhead, reduces unoccupied but reserved 'ghost bookings,' and ensures health standards are met after each use. The business value comes from higher space utilization, lower labor costs for coordination, and demonstrable compliance with sanitization protocols, directly impacting operational margin and employee experience.

Implementation integrates with systems like Office 365/Google Calendar, IoT occupancy sensors, and CMMS platforms like ServiceNow. The orchestration layer, built with frameworks like LangGraph, handles optimization logic, exception routing for special requests, and real-time status updates to digital signage and mobile apps. Controls include approval gates for overrides, audit logs for compliance, and performance dashboards tracking utilization and cleaning cycle times.

Phase 1 establishes the core data pipeline and allocation engine, delivering immediate value by automating desk assignments based on team adjacency and real-time bookings from systems like Office 365 or Google Workspace. This initial layer integrates with occupancy sensors and the building's access control system (e.g., Lenel) to validate usage, creating a closed feedback loop. The focus is on proving the optimization algorithm's accuracy and user adoption via a mobile app, setting the stage for downstream automation without disrupting existing operations.

Phase 2 introduces the sanitization orchestration layer, triggering cleaning work orders in the CMMS (e.g., ServiceNow) upon sensor-confirmed desk vacancy. This phase integrates IoT data flows with janitorial dispatch logic, including exception routing for high-touch areas. The final optimization phase adds predictive scheduling based on historical patterns and deploys the workflow across a portfolio. Each phase includes defined governance checkpoints for data quality, user feedback, and system performance before proceeding, ensuring the build delivers compounding ROI while controlling rollout risk.

Effective governance starts with a clear decision hierarchy. The workflow's optimization logic—balancing team adjacency, historical usage, and real-time bookings—must be auditable. We implement approval gates for policy overrides, such as VIP desk assignments or sanitation waivers, routed through facilities or department heads via Slack or ServiceNow. This control layer prevents algorithmic decisions from violating operational policies or labor agreements, ensuring the system augments rather than disrupts workplace management.

Phased rollout is critical for risk management and validating ROI. Phase 1 deploys to a pilot floor, integrating with occupancy sensors and a single cleaning vendor tablet to refine the sanitation trigger logic. Phase 2 expands building-wide, activating mobile app interfaces and integrating deep cleaning schedules. Each phase is monitored via an observability dashboard tracking utilization, sanitation compliance rates, and labor cost savings. This measured approach allows for tuning based on real feedback, ensuring the system delivers the promised 15-25% reduction in cleaning labor and maximized desk utilization before full portfolio deployment.

This automation directly reduces real estate costs by maximizing desk utilization and eliminates manual coordination overhead between facilities and workplace teams. The core business value comes from an optimization algorithm that assigns desks based on team adjacency, historical patterns, and real-time bookings, increasing effective capacity by 20-30%. Post-use, the system automatically triggers sanitization work orders in your CMMS (e.g., ServiceNow, IBM Maximo), ensuring health standards without staff intervention. Savings are realized through lower cleaning labor costs, reduced vacancy, and improved employee experience from seamless desk claims.

Implementation requires integrating the mobile booking front-end with your IWMS (e.g., OfficeSpace, Serraview) via API. The orchestrator, built on a framework like LangGraph, ingests sensor data from IoT platforms (e.g., Enlighted, VergeSense) to confirm occupancy and trigger the sanitization workflow. Critical controls include human-in-the-loop approval for booking exceptions, sanitization quality audits via QR code scans, and a real-time dashboard for facilities managers to monitor utilization and backlog. Rollout should be sequenced by floor or department to manage change and validate sensor calibration, ensuring the system's logic aligns with physical workplace layouts and cleaning crew capacity.