If you had to help your software engineering team deploy 3x more frequently, boost quality by 50%, while working with 10% less budget, what would you do? That’s the question many CTOs face today, and one I’ve tackled myself several times throughout my career holding C-Level and VP level engineering positions at companies like Oracle, Dell, IBM, Wrike and Wunderkind. I had to find ways to reduce cycle time, decrease tech debt, improve DevOps all while cutting cost.
Understanding how a software engineering team builds and deploys software is the key to understanding how that same team can improve performance and quality, optimize resources, and foster a culture that promotes developer productivity.
We all know that software engineering is the lifeblood of any modern company, but in most organizations, little to no effort is dedicated to analyzing data and determining what works well and what doesn’t. Many organizations measure their performance by simply measuring the amount of code that released. Instead, maybe they should measure the potential code that could have been released and assess how efficiently it could have been developed and deployed.