Certainly. Here’s a structured breakdown of the advantages and requirements of implementing spend analytics for the supply chain department (technical parts) of an airline like Qatar Airways, with an added emphasis on integrating cargo and freight forwarder data to reduce expedition costs.
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Advantages of Spend Analytics in Supply Chain (Technical Parts - Airline)
1.
Cost Optimization
- Identify excessive or non-strategic spend on technical parts and maintenance services.
- Consolidate suppliers to negotiate better pricing and payment terms.
- Reduce dependency on emergency procurement or last-minute orders, which often cost more.
2.
Inventory Management Efficiency
- Analyze historical consumption patterns to optimize stock levels.
- Avoid overstocking or stockouts of high-value aircraft components.
3.
Supplier Performance Insights
- Assess delivery times, quality issues, compliance, and cost trends per supplier.
- Support decision-making for supplier rationalization or diversification.
4.
Category Management
- Segment spend by part category (e.g., avionics, hydraulics, engine components).
- Identify opportunities for bundling or volume purchasing.
5.
Strategic Sourcing
- Use analytics to drive sourcing strategies based on total cost of ownership (TCO).
- Identify alternative suppliers for critical components to minimize risk.
6.
Reduction in Expedition Costs
- By forecasting needs and aligning logistics proactively, avoid urgent shipments (air freight, charter).
- Minimize “AOG” (Aircraft on Ground) scenarios due to parts unavailability.
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Linking Cargo & Freight Forwarders Data
Key Benefits:
- Proactive Logistics Planning
- Align parts procurement with real-time cargo capacity and freight schedules.
- Reduce reliance on expedited or chartered logistics.
- Visibility & Control
- Track shipment statuses and adjust based on criticality and delivery windows.
- Match shipping lead times with aircraft maintenance schedules.
- Cost Avoidance
- Identify inefficient routes or costly freight decisions.
- Optimize for bulk or consolidated shipments instead of fragmented urgent orders.
- Vendor Coordination
- Improve collaboration with freight forwarders on optimal transport modes and warehouse availability.
- Predict congestion or seasonal delays and reroute accordingly.
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Requirements for Implementing Spend Analytics
1.
Data Integration
- Integrate ERP (Oracle Fusion or EBS), MRO systems (like AMOS or Ramco), procurement systems, and logistics data sources.
- Real-time or batch data flow from freight forwarders, cargo divisions, and customs.
2.
Data Cleansing & Standardization
- Normalize supplier names, part numbers, units of measure, and currency.
- Ensure consistency in historical spend data across cost centers and GL codes.
3.
Category Taxonomy
- Develop a clear and standardized part classification schema (e.g., ATA chapter-based).
- Assign spend to categories like engines, avionics, consumables, etc.
4.
Analytics Tools & Dashboards
- BI platforms (Power BI, Tableau, or Oracle Analytics Cloud) to visualize spend patterns.
- KPI dashboards for lead time, cost per shipment, supplier scorecards.
5.
Cross-Functional Collaboration
- Align supply chain, engineering, finance, and cargo departments on data governance.
- Define ownership of insights and actions (e.g., procurement savings, logistics planning).
6.
Predictive Capabilities
- Use machine learning to forecast demand for parts and anticipated freight needs.
- Simulate cost impacts of sourcing vs. delivery trade-offs.
🛫 Example: Use Case in Qatar Airways
- Problem: Frequent AOG situations due to delayed delivery of critical engine components, requiring last-minute expedited freight at a premium.
- Solution:
- Use spend analytics to identify patterns in emergency shipments and their root causes.
- Integrate freight forwarders’ route data to anticipate delays or congestion.
- Create a predictive replenishment model to pre-position parts at hubs based on aircraft routing.
Would you like this formatted into a presentation slide or summarized for a report/proposal?