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Enhanced Decision Support System for Cost Management and Operational Optimization
  1. case
  2. Enhanced Decision Support System for Cost Management and Operational Optimization

Enhanced Decision Support System for Cost Management and Operational Optimization

sigma.software
Transportation
Logistics
Supply Chain

Identifying Challenges in Legacy Decision Support and Cost Management Systems

The client relies on outdated decision support solutions that hinder operational efficiency, incur high maintenance costs, and lack comprehensive integration with real-time data sources such as route planning systems. This impacts accurate cost calculations, fuel management, and invoicing processes, resulting in suboptimal decision-making and increased operational overhead.

About the Client

A large transportation enterprise seeking to modernize its cost calculation, fuel management, and invoicing systems to improve operational efficiency and reduce maintenance costs.

Goals for Developing an Efficient and Cost-Effective Decision Support Platform

  • Replace existing legacy systems with a modern, lean, and cost-efficient platform capable of handling daily cost calculations based on actual operational data.
  • Enable multi-prognosis cost calculations for extended planning horizons (e.g., annual forecasts).
  • Develop modular components for fuel management, activity-based cost calculations, and invoicing that integrate seamlessly with the core platform.
  • Reduce system maintenance costs and improve data accuracy and reporting capabilities.
  • Ensure timely delivery of the project within scheduled timelines and budget constraints.

Key Functional Capabilities of the New Decision Support System

  • Core platform for automated daily cost calculations based on real routes and operational data.
  • Multiple prognosis instances functionality for long-term planning.
  • Fuel management module for tracking fuel consumption, costs, and vendor decisions.
  • Budgeting module for calculating and comparing projected versus actual costs using predefined price lists.
  • Invoicing module for automated invoice import, matching, and reporting.
  • Integration capabilities with existing flight planning and other operational systems.

Preferred Technologies and Architectural Approach

Modular system design for flexibility and scalability
Automated data import and processing mechanisms
Reporting dashboards for end-user insights
Secure deployment environment ensuring data integrity and compliance

External Systems and Data Sources Integration Needs

  • Operational data sources such as route planning and flight execution systems
  • Financial data for pricing and invoicing
  • Vendor management and fuel procurement systems

Critical Non-Functional System Attributes

  • System should support high scalability to accommodate increased data volume
  • High performance for daily calculations and real-time reporting
  • Robust security measures to protect sensitive financial and operational data
  • Availability of support and maintenance services post-deployment

Anticipated Business Impact and Benefits

The new decision support platform is expected to significantly improve operational efficiency by automating daily cost calculations, reducing maintenance costs, and enhancing decision-making accuracy. It aims to streamline fuel management, budgeting, and invoicing processes, leading to cost savings and more strategic resource utilization, ultimately supporting improved financial performance and operational agility.

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