DRAFT SOO - OrchestrateSI - 10.19.2026.pdf

DRAFT

OrchestrateSI: Integrated Statement of Objectives (SOO)

1. Background, Purpose, and Operational Vision

1.1 Program Background — TSA manages passenger throughput across more than 430 federalized commercial airports.

Over 70 decentralized scheduling offices manually coordinate tens of thousands of Transportation Security Officers using disparate legacy systems and static bidding procedures, which limits frontline agility, inflates overtime costs, and complicates labor-policy compliance. Checkpoint layouts vary by airport category and terminal design, and frontline supervisors currently rely on manual, reactive observation to spot queue surges — meaning bottlenecks are often identified only after throughput has already degraded. Passengers also face unpredictability across their curb-to-gate journey because transit, traffic, flight, and border data remain fragmented across isolated platforms, leaving both passengers and TSA leadership without reliable advance demand indicators.

1.2 Combined Purpose and Strategic Vision — TSA is seeking to evolve toward an integrated, data-driven security operations ecosystem that synchronizes Demand Intelligence, Tactical Checkpoint Visibility, and Workforce Supply Optimization. By unifying external arrival signals, intra-checkpoint sensor telemetry, and automated personnel scheduling into one operational framework, TSA aims to shift from reactive bottleneck mitigation to predictive operational mastery

— lowering costs, maintaining passenger wait times at or below target thresholds, enhancing accountability, and reinforcing national security screening standards.

2. Individual Objectives and Performance Metrics

TSA is seeking a consolidated solution, or set of integrated solutions, unified under a single operational architecture but comprising three distinct technical workstreams.

2.1 Workstream 1 – Workforce Orchestration: Objectives include SI-driven predictive scheduling using historical throughput, seasonal patterns, and real-time flight data; an automated bidding engine supporting leave bidding, seniority-based shift bidding, shift trades, call-outs, and split shifts up to 14 months in advance; a dynamic "what-if" capacity simulation environment for leadership to model lane configurations, equipment availability, and budget constraints;

automated tracking of Paid Not Worked (PNW), Overtime (OT), FTE burn rates, training, and certifications; and bi-directional data exchange with existing HR, payroll, and credentialing systems. Performance metrics include measurable reduction in non-emergency overtime hours, elimination of manual scheduling tools across 70+ offices, a defined confidence interval between forecasted and realized staffing needs, and 99.9% platform uptime.

2.2 Workstream 2 – Checkpoint Visualization & Bottleneck Detection: Objectives include deploying non-invasive, privacy-compliant sensors across the full checkpoint footprint — queue entry/overflow, CAT lanes, divestiture, on-person screening (WTMD, AIT, pat-down), ADA gates, additional screening/alarm resolution, and recomposure zones; computer vision and algorithmic pattern detection to identify flow anomalies and lane imbalance in real time;

predictive modeling to flag emerging blockages 10 minutes before severe degradation; and role-based digital alerts to checkpoint supervisors for proactive lane adjustments. Performance metrics include rapid alert generation upon threshold breach, a minimum 15-minute prediction horizon, and a low false-positive alarm rate during peak hours.

2.3 Workstream 3 – Real-Time Multi-Source Wait

Time & Queue Intelligence: Objectives include ingesting and fusing information sources such as FAA data, transit feeds, CBP Airport Wait Time data, and TSA throughput baselines; correlating seat capacity, load factors, and flight clusters to forecast passenger surges 30 minutes in advance; computing real-time and forecasted wait times segmented by screening modality; and deploying a zero-registration public interface with wayfinding, checkpoint comparisons, push alerts, and trip-planning tools via web, mobile, and open APIs. Performance metrics include defined ingestion-to-display latency targets, Mean Absolute

Percentage Error accuracy thresholds for peak and steady-state periods, monthly system uptime targets, fast mobile load times, automated stale-feed fallback triggers, and full Section 508/WCAG 2.1 Level AA compliance.

3. Consolidated Operating Constraints and Assumptions

Hardware must remain within the TSA checkpoint physical footprint, with standalone non-invasive sensors deployed where CCTV access is unavailable, proprietary, or legally restricted, and installation must not disrupt active screening operations. All cloud applications and databases must be hosted in a FedRAMP-authorized or TSA-approved environment compliant with DHS 4300A guidelines, and SaaS components must support SSO and federal ICAM standards. No PII, facial recognition templates, or persistent device tracking may be captured. The public wait-time engine must rely primarily on public/open-access feeds, and TSA will retain full, unencumbered ownership of all raw telemetry, derived datasets, schedules, and logs. Workforce optimization and leave/shift-bidding rules must strictly adhere to the TSA Collective Bargaining Agreement and applicable DHS human capital directives. The government prefers enterprise-wide, permissive open-source licensing over per-seat models.

4. Delivery Schedule

Delivery is sequenced across five phases over 12 months. Phase I covers project initiation, system architecture design, data flow diagrams, security/privacy plans, and a checkpoint site discovery plan. Phase II delivers MVP in a lab/test environment, and an Alpha public wait-time visualizer at one pilot hub. Phase III includes formal workforce operational assessments across five TSA-designated airports, hardware/sensor verification, and integration of the wait-time platform with at least one commercial airline mobile app. Phase IV expands real-time wait-time models to available airports, delivers journey-planning tools and notification engines. Phase V achieves nationwide rollout across all TSA airports.

5. Planned Acquisition Strategy

TSA is seeking white papers of not more than 5 pages from industry describing their solution to the problems identified in this SOO. TSA will not consider graphics when assessing submissions. TSA is interested in industry’s assessment of feasible timelines for the acquisition strategy discussed below.

The acquisition strategy is structured into a 4-stage challenge-based phased approach, shifting the focus from paper milestones to iterative demonstration and continuous government input:

• Stage 1: Concept Paper & Architecture baseline (2 weeks – followed by government evaluation): Responds directly to the Statement of Objectives (SOO) by establishing the overall system architecture, data flow models, security, and privacy frameworks, and a checkpoint design discovery plan, alongside core Total Cost of Ownership (TCO) drivers to include proposed new business models, team qualifications, and deployment parameters. TSA will perform a down-select at the conclusion of Stage 1.

• Stage 2: Working System & Minimum Viable Product Demonstration (6 weeks – followed by government evaluation):

Delivers and validates a functional Minimum Viable Product (MVP) within a controlled test/lab environment, demonstrating technical viability via an Alpha public wait-time visualizer deployed at a designated pilot hub. TSA will perform a down-select at the conclusion of Stage 2.

• Stage 3: Multi-Phase Refinement with Continuous Government Input (3 months): Iteratively scales and hardens the platform in direct partnership with government stakeholders through operational assessments across 4 TSA-designated airports, sensor verification, commercial airline mobile app integration, real-time wait-time modeling across all available facilities, journey-planning tool deployment, and Section 508 accessibility compliance.

• Stage 4: Contract Award and Nationwide Production Rollout: Down-selects to the final production contract award to deploy the hardened, fully integrated platform nationwide across all TSA airports.