Take the guesswork out
Measure your progress on predefined values through various cloud stages.
To begin with, the model should perform a comprehensive review of the enterprise’s current cloud landscape. It should assess whether cloud adoption has met the earlier defined value or not. This as-is performance across a variety of technology, processes, and business segments will form the basis of value realization.
The metrics and industry benchmarks should serve as a mirror of the enterprise’s cloud performance. They should take out the guesswork from cloud value realization and ensure enterprises achieve predefined values across various stages of the cloud life cycle.
In areas where the enterprise lags its peers, it can proactively intervene, and course correct. In others where it leads, it can continue the best practices to sustain this advantage. The model should also help enterprises to define realistic value for future cloud adoption initiatives. Benchmarks should assist in course correction and make the journey fact-based and pragmatic.
The metrics and benchmarks should be very detailed, covering the entire technology and process ecosystem. In addition to typical metrics such as mean time to resolve, percentage of successful changes, asset scanning, and automated CI/CD, it should have next-generation metrics around infrastructure-as-a-code adoption, cloud training depth, next-gen support model adoption (for instance, SRE/DevSecOps), talent models, and return on investments.
The model should help enterprises adopt cloud across the organization. It should address multiple business and technology objectives such as debt reduction, cost optimization, higher efficiency, and business agility. These are achieved throughout the full cloud spectrum spanning migration, modernization, and data center exits.