Reimagining the Enterprise using AIOps
For Avis – Leading Global Car Rental Company
ABOUT CUSTOMER​
Avis Budget group Int is a leading global car rental company. They are the market leaders in the budget and mainstream car rental segment. The customer has over 2,900 offices in 112 countries across Europe, Middle East, and Asia. The company is headquartered in Bracknell, Berkshire, England and employs over 5,500 associates.
VALUE REALIZATION
- Reduced Alerts - ignio AIOps has enabled Silent Operations by intelligently eliminating alert noise.
- Reduced mean time to detect and mean time to resolve issues through intelligent triaging and autonomous resolution.
- Reduced incidents by predicting problems before they impacted business.
REACH US
Business context
For an enterprise that relies on its business applications to connect and serve customers, it is imperative to have robust and resilient IT operations supporting business applications. They cannot have support teams constantly firefighting and manually resolving issues. The time consumed and issues caused due to human errors can hurt the enterprise through loss of business and lack of customer support. Therefore, the customer needed an enterprise-wide Digital Transformation exercise to move from manual and reactive operations to autonomous and predictive one.
Lack of Business Aware Command Center
The Problem
The customer was using multiple monitoring tools for managing incidents and events for different lines of business. These monitoring tools worked on a specific set of parameters, and their operations lacked business awareness. This resulted in the support team having to work through a lot of noise and false alerts to isolate actual issues, triage them, and resolve them. Around 80% of the Command Center team’s efforts were spent in isolating the noise.
The Solution
ignio worked on integrating all the alerts received from multiple monitoring tools to reduce duplicates. Leveraging its AI/ML capabilities, ignio fine-tuned the prediction accuracy parameters through model-based, case-based, and rule-based reasoning. ignio further helps in triaging the issues and resolving them autonomously. If ignio is unable to resolve them, it collects the root cause analysis and other insights and pushes them to the manual queue to aid in quick resolution.Â
ignio AIOPs Overall Benefit
- Over 240870 requests handled by ignio till date
- 68% reduction in noise
- 99.99% availability for in-scope critical applications
- AI/ML infused through model-based, case-based, and rule-based reasoning to provide 90% prediction accuracy
- ~50-60% of incidents are solved by ignio autonomously
- 94% improved MTTD (Mean time to Detect) and MTTR (Mean time to Resolve)
