Procurement transformation in times of uncertainty
Company Size
1,000+
Region
- Europe
Country
- France
- Netherlands
Product
- Rosslyn Spend Management
- Rosslyn Spend Analytics
Tech Stack
- AI
- Machine Learning
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Data Mining
- Analytics & Modeling - Predictive Analytics
- Functional Applications - Enterprise Resource Planning Systems (ERP)
Applicable Industries
- Aerospace
- Transportation
Applicable Functions
- Business Operation
- Procurement
Services
- Data Science Services
- System Integration
About The Customer
Air France-KLM is a major European airline group, formed from the merger of Air France and KLM. The company operates a vast network of flights across the globe, serving millions of passengers annually. As a large organization, Air France-KLM has complex procurement needs, requiring efficient management of supplier relationships, cost control, and data analytics to ensure smooth operations. The company sought to enhance its procurement processes to better manage cash flow and secure stability, especially in the face of uncertainties brought about by the COVID-19 pandemic.
The Challenge
Jurriaan Lombaers, SVP & CPO at Air France-KLM, was tasked with leading the firm's procurement journey to drive greater consistency across the business. One of the main challenges he faced was defining what procurement excellence and consistency meant for the firm. Lombaers emphasized the importance of storytelling in procurement and the need for the team to have data readily available. He aimed for the team to spend 80% of their time creating value for the business and only 20% on gathering data.
The Solution
Air France-KLM turned to Rosslyn for help in improving its spend analytics and reporting capabilities. Rosslyn's analytics solutions enabled the airline to begin its journey towards achieving its new procurement objectives. The solutions use AI and machine learning to consolidate and enrich supplier data sets, revealing areas where money can be saved, productivity improved, and risk minimized. With a clean, enriched data set, the business could categorize data meaningfully, supporting the identification of procurement initiatives that could improve cost savings, business processes, and cost management.
Operational Impact
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