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25% improved customer experience and ~$2m in potential savings for Call Center Operations of an Airline

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Overview.

Our client is an international airline that operates 1,000+ flights every week to 120+ destinations, has 13,000+ employees, and is rated among the Top 5 in AirlineRatings.com's Top 20 airlines (2022).

Challenges.

The airline had decided to move from Sabre to the Amadeus platform, and Amadeus asked Coforge to assess and implement a seamless transition to the new platform.

  • Part of the migration assessment involved a study and report on the resources required in their captive Contact Center for pre and post-cutover as the airline migrated to the new platform 
  • Based on preliminary information, Coforge suggested, to the airline management, that they could maximize the impact of the migration by increasing the scope under review

Solution.

The team used multiple steps, including a study of downstream processes and a robust analysis framework (ProcessGym®) for a detailed end-to-end Contact Center study from a people, process, and technology perspective: 

  • Data door approach – for example, Baseline created, factoring in call volume impact of blanket commercial waiver policies, pandemic rules, etc. 
  • Process door approach – for example, changes in IVR Options and e-service, website self-service options improvements 
  • Tech door approach - for example, Upgrade and automate chat processes, "One CRM" implementation across all centers 
  • Best practices from other airlines - for example, 360 insights gathered from other airlines to assess realistic performance level achievement timeframes

The Impact.

The business impact on Call Center Operations after implementing changes was as follows: 


  • Overall optimization of 15% to 20% 
    • 2 Short period of stabilization of operations after migration 
    • Based on budget numbers, savings of $1.5M to $2M per year 
  • Customer Experience improved by 25% 
    • Service Levels improved by 10-12% 
    • Overall Average Handling Time (AHT) reduced by more than 15% 
    • Call wait time reduced by 15-20% 
  • Efficiencies of 5% to 7% from better forecasting 
    • Robust forecasting mechanism for better staff optimization 
    • Further 5-7% efficiency expectation 

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