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Digital.ai Release cuts costs and boosts revenue at major financial services company

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Case Study Digital.ai | Digital.ai Release cuts costs and boosts revenue at major financial services company 1 Digital.ai Release cuts costs and boosts revenue at major financial services company Software releases happen 2x per week instead of 4x per year Companies in all industries today are struggling to keep up with customer expectations, but demands are particularly rigorous in financial services. Before meeting Digital.ai, this financial services company, which manages assets of more than $6B, had been growing rapidly but was struggling with competitive pressure and inability to respond quickly to market need. Background: big chunks of code, chaotic release process The financial services company was growing rapidly and was facing competitive pressure. Their release process was characterized by: • Developers spending 3-4 months implementing a set of features and fixes, which they tested and cleaned up for 1-2 months, until finalizing a release. • For each release, a long meeting was held with developers, QA, database administrators and operators to create the release plan — an Excel spreadsheet that was sent out to all participants. • During the release, every participant worked off their own copies of the release plan, which often turned out to be different versions. • After every step, the person carrying out a task communicated the result back to the release manager, who was the only person with an up-to- date version of the release spreadsheet. • Frequently, team members had to check with each other or with the release manager to find out the status of a task they were waiting on. • Sometimes, tasks happened in the wrong order, or a team member ended up waiting for another task to complete — only to discover that it had actually been completed a while ago. To complicate matters further, the technical team was typically working on multiple releases at the same time. Key facts • Industry: financial services • Company: a Fortune 1000 company • Employees: 10,800 • Assets: $6.2B Technical environment • Virtualization/cloud: VMware, OpenStack, Amazon EC2, bare metal • OS: Solaris, RHEL, Windows • Middleware: Oracle WebLogic, standalone, JVM applications, IIS, Oracle DB • Provisioning and deployment: Puppet, Chef, Digital.ai Deploy, formerly XebiaLabs XL Deploy • Continuous integration: Jenkins • Process management: JIRA, ServiceNow Before Digital.ai Release, formerly XebiaLabs XL Release • Many bottlenecks in the release process • No way to proactively pinpoint problems in the release pipeline • No way to analyze past releases in order to optimize the process • Inability to release software at the speed required to be competitive After Digital.ai Release • Visualize the entire flow from development through to production • Cut costs by $500k annually due to less manual overhead • Accelerate time-to-release substantially • Generate approximately $4.2m in additional revenue in the process

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