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    • ROIs Crew Mgmt
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  • CASE
    • ROIs Crew Mgmt
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Polaris Resource Management Solution

Polaris Resource Management Solution (RMS) is designed to tackle the challenges of rising operational costs, staffing issues, and resource inefficiencies in the aviation industry. By utilizing real-time, AI-driven task dispatching and planning optimization, Polaris enhances cost control, service quality, and staff experience. Key benefits include reducing labor costs, improving task completion efficiency, and minimizing delays. With powerful reporting tools, integrated planning, and streamlined communication, Polaris enables airlines and ground operations to meet the demands of increasing passenger volumes and operational complexities while maintaining high service standards and operational effectiveness.

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Flight Data Manager

Pain Points & Requirements:

  • Constraints to select flight data within any date period
  • Conflicting flight data from multiple data sources
  • Lack of passenger/cargo volumes when airline schedules change

Values:

  • Multi-scene schedule edit and publish
  • Real-time flight information management & alerts
  • Single view of flight, 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, 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.

Case Study

Forecast Manager

Pain Points & Requirements:

  • Lack of mechanism to accurately identify resource shortage and future resource requirements

Values:

  • Resource Forecasting based on business trends & planning
  • Simulate daily operation without risk
  • Find potential resource bottlenecks and improve resource efficiency

Key Features:

  • Scenario based resource planning optimization for long term workforce management
  • Modify data of each dimension (resource, demand, rules, service standards, etc.) according to business logic and management purpose
  • Enhance KPl's report with comparative analysis of cost, efficiency and service levels to assist decision-making
  • Utilize flight forecast models to enhance accuracy and robustness in resource planning

Case Study

Demand Manager

Pain Points & Requirements:

  • Lack of accurate resource demand when flight schedule or SLA changes
  • Lacks identification of resource demand changes in the peak and 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

Case Study

Roster Manager

Pain Points & Requirements:

  • Lack of an automatic & intelligent rostering system:
  • Operational inefficiency and resource cost imbalance
  • Illegal and unfair workload distribution
  • Missing decision support for roster strategy when business requirements change

Values:

  • Maximize staff and equipment resources
  • identify resource supply bottlenecks
  • Ensure legality and fairness for rostering efficiently

Key Features:

  • Optimizes staff rosters and equipment allocation
  • Creates a roster schedule by matching desired on/off patterns and shift start/end times for each employee
  • Uses actual or simulated resources, by individuals or by groups, by flexible or fixed patterns with auto rotation
  • Multi-qualification optimization
  • Tracks leave and training records
  • Observes fairness, staff preferences and fatigue levels
  • Compares KPl's among scenarios to support decision making

Case Study

Assignment Manager

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
  • Provides timely recoveries during irregular operation

Key Features:

  • Auto task re-assignment in real time with a 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 violations
  • Quick adjustment: manually add, modify or delete task, modify resource availability, etc..
  • Auto alerts for violations

Case Study

Staff Care Manager

Pain Points & Requirements:

  • Need to close the loop from schedule to execution
  • Addressing concerns about 'unfairness'
  • Expectation from staff for preferred rosters

Values:

  • Enhances transparency and improves communications
  • Increases employee satisfaction and engagement
  • Helps prevent bias, promote fairness, and minimize conflicts
  • Creates a balance between work efficiency and employee wellness & fatigue

Key Features:

  • Staff portal: a web-based tool for staff to access their assigned schedules, request time-off, and swap shifts
  • Staff preference: allows staff to state personal preferences
  • Fairness management: ensures an equitable distribution of shifts and tasks among staff members. Incorporates algorithms to consider seniority, skill levels, and workload distribution when generating rosters
  • Fatigue management: incorporates regulations and guidelines related to maximum working hours and rest periods by considering factors such as shift length, consecutive shifts, and minimum breaks
  • Auto Grouping: a real-time communication tool to improve flight service efficiency for grouped staff

Case Study

Critical Path Manager

Pain Points & Requirements:

  • Lack of decision support on task/resource bottlenecks 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 during the aircraft turnaround
  • 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

Case Study

Stand Manager

Pain Points & Requirements:

  • Challenges in managing gate and stand allocations efficiently in dynamic environments.
  • Limited visibility into allocation conflicts and operational disruptions.
  • Complexities in coordinating aircraft tow planning across multiple stakeholders.

Values:

  • Enhanced operational efficiency through optimized gate and stand management.
  • Real-time visibility and proactive alerting for allocation changes.
  • Seamless adaptability to various operational responsibilities—airline, ground handler, or airport authority.
  • Provides an optimized towing plan

Key Features:

  • Alerts-based gate and stand allocation for efficient decision-making.
  • Multiple visualization options, including Gantt chart, flight display list, and terminal graphic.
  • Operates independently or integrates with AODB for comprehensive functionality.
  • Handles complex aircraft tow planning, minimizing disruptions and optimizing stand utilization.
  • Real-time alerts for allocation conflicts, ensuring timely resolution and recovery.

Case Study

Business Intelligence Manager

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:

  • Generates reports for cost, efficiency, and fairness analysis.
  • Creates operational reports for overtime, leave, service quality, and workload statistics.
  • Uses configurable tools for quick and dynamic reporting.
  • Reviews schedule effectiveness and labor costs to reflect and adjust.
  • Makes data-driven decisions with robust analytics.
  • Monitors labor costs to ensure sustainable staffing levels.
  • Manages overtime efficiently by spreading shifts and planning for peaks.

Case Study

ROIs Solution Advantages

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