Polaris Resource Management Solution

Pain Points & Requirements:

• Constraints to select flight data within any date period
• Conflicting flight data from multiple data sources
• Lack of quest/co fight volume estimates when airline schedules change

Values:

• Multi-scene schedule edit and publish
• Real-time flight information management & alert
• Single view off light, tasks and resources

Key Features:

• Edit actual/simulated flight schedules
• Store multiple schedule scenarios for production or analysis
• Publish confirmed schedule to production
• Update flight data with pre-set data priority from multiple sources
• Integrate with upstream systems such as AODB, PSS, ADS-B, ACARS etc. for real-time flight data exchange. includes but not limited to: Aircraft Registration REGNo., Bay, Gate, Carousel, Loading Message for Guest and Cargo, etc..
• Set triggers and thresholds for auto alert on flight information changes such as cancel, delay, aircraft type change, bay change, etc.

Pain Points & Requirements:

• Lack accurate resource demand when flight schedule or SLA changes
• Lack easy way to identify resource demand changes in the peak/off peak windows

Values:

• Optimize task calculation& generation
• Provide multi-scene resource demand calculation

Key Features:

• Set configurable demand generation rules
• Generate-demand automatically based on KPl's and business operation rules using flight schedules-historical, present or simulated scenarios
• Store multiple demand scenarios for production or analysis
• Visual display of demand curve showing peak and off-peak status
• Differentiate task volumes for different qualifications or business units
• Real-time task updates according to changing flight dynamics

Pain Points & Requirements:

• Lack of real time automatic task re-assignment and recovery when violations occur
• Need to capture both dynamic changes and future predictive situation

Values:

• Dynamic optimization on task assignment and real-time resource prediction
• Provide timely recovery during irregular operation

Key Features:

• Auto task re-assignment in real time with high performance algorithm
• Optimal assignments -fairness, fatigue, business/staff preference, etc.
• Advanced 2-4 hours demand prediction based on changing demand dynamics
• Predictive and proactive dispatch assignment for potential violation
• Quick adjustment: manually add, modify or delete task, modify resource availability, etc..
• Auto alerts for violations

Pain Points & Requirements:

• Lack of decision support on task/resource bottleneck during ground process management to improve on time performance
• Lack of accurate prediction on flight status and ground operation capabilities

Values:

• Whole services process monitoring, tracking, alerting and forecasting to provide optimization
• Data driven simulation to improve operational robustness

Key Features:

• Process monitoring with task dependencies displayed in Gantt chart
• Auto calculation of the longest service path with real-time data
• Task Delay Prediction
• Turnaround Time Prediction
• Dynamic alerts for the deviation from actual tracking status to scheduled assignments
• Service Recovery: request additional resources or shorten the service duration
• Visualize resource status, task assignment, service progress, real-time alert, KPl's and critical information on digital map

Pain Points & Requirements:

• Data silos across departments prevent a unified view of operations and performance.
• High costs and complexity of traditional BI tools limit accessibility.
• Challenges in monitoring labor costs, schedule fairness, and operational efficiency.

Values:

• Transparent operations with clear reporting and visibility.
• Enhanced decision-making through actionable insights.
• Improved efficiency by identifying gaps and optimizing resource use.

Key Features:

• Generate schedule reports for cost, efficiency, and fairness analysis.
• Create operations reports for OT, leave, service quality, and workload stats.
• Use configurable tools for quick and dynamic reporting.
• Review schedule effectiveness and labor costs to reflect and adjust.
• Make data-driven decisions with robust analytics.
• Monitor labor costs to ensure sustainable staffing levels.
• Manage overtime efficiently by spreading shifts and planning for peaks.