A leading provider of private integrated healthcare delivery systems in the US was struggling with a poor infrastructure discovery process and imperfect application affinity mapping. Consequently, it was unable to assess the impact of critical incidents, leading to a loss in business.
As part of the engagement, Trianz implemented several best practices, from the client’s processes as well as the tools perspective, and also reduced the incidents tally to close to zero without production outages.
The Business Challenge
The organization needed to implement an Endpoint Inventory solution to address is problems of poor infrastructure discovery and application affinity mapping. The objective was to accurately assess the impact of critical incidents which were otherwise leading to a loss in transactions, and consequently, of business.
- Tivoli Application Dependency Discovery Manager [TADDM]
- Tivoli Asset Discovery for Distributed [TAD4D]
- BigFix and BigFix Inventory
- Developed an execution roadmap sequencing the implementation of technology stacks based on the client’s business priorities
- Conducted workshops with business and IT stakeholders to understand challenges/ business needs
- Assessed existing processes, tools, integration points, and data sources
- Designed the TADDM architecture which consisted of five Secondary Storage Servers and 14 Discovery Servers
- Standardized the process for managing incidents and service requests
- Implemented monitoring solutions, further reducing the duplicate events count and improving operational efficiency of software products
- Enabled migration from TAD4D to BFI, including bundling rules and software exclusions
- Initiated business applications’ health monitoring through application affinity mapping in TADDM
- Improved accuracy of sub-capacity reporting in BFI for invoicing
- Automated discovery of 33K servers and 45K network components once every week
- Achieved sustained process improvements, higher customer satisfaction and lowered operating costs through a step-by-step, metrics-oriented improvement approach
- Reduced scan errors from high volume to less than 3%
- Streamlined the administration and support process for day-to-day engagements