How We Use CloudBees Engineering Efficiency to Identify Bottlenecks and Reduce Cycle Time

Written by: Dorra Bouchiha
4 min read
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In my first blog, Three Questions Every Engineering Leader Should Be able to Answer, I talked about key pieces of information engineering leaders should have related to how their teams are performing in relation to business priorities. Armed with data and insight, engineering managers can help their team deliver value to the customer quickly and predictably. 

As an engineering leader, it is also important that I help my team get better. Every team I worked with, aspires to be high performing. However, it is not always clear what it means to be high performing, how to improve and most importantly, how to measure the improvement. Many technology executives and practitioners have their own ideas, based on their experiences and instincts, but the discussion is often subjective and anecdotal - rarely grounded in data and metrics. 

Regardless of how you define high performing, I believe that one of the most important ways to achieve it in agile teams is with an emphasis on continuous learning and continuous improvement. Regular and meaningful retrospectives are the opportunity for the team to acknowledge what they did well and identify what they can improve on. However, without accurate data, it is often difficult to measure the improvement and tie any change back to a tangible outcome. 

Let me share with you how CloudBees Engineering Efficiency helped my team identify a bottleneck, find the right improvement and recover our velocity. 

My team initially prototyped the idea to build CloudBees Engineering Efficiency to prove feasibility and build an MVP. Once all stakeholders were aligned and committed to building the product, the team started a phase of rapid development focusing on moving quickly to deliver on small things with a good level of experimentation. We onboarded early adopters which allowed us to start learning and iterating.  Once the product was good enough to on-board additional customers, and we approached the official launch date, the team deliberately switched to becoming more conservative with our changes requiring additional reviews and validating all UX/UI changes before merging a PR. The change was intentional in order to maintain a high level of quality and a great user experience. The new process meant that developers were getting on video calls with the designer and demoing the UI for every change that affected the user experience.    

This shift in process resulted in a slower pace and overall feeling that changes were taking much longer. It was very frustrating to the team. Leveraging the information presented by the Cycle Time screen, the team backed that feeling with actual data. At the retrospective the team brainstormed ideas to recover our velocity while improving quality. The consensus was to add  pull-request preview environments that will spin up a UI instance for every pull request. The automation posts a unique URL for every preview environment that can be shared with the designer and the product managers and would allow them to test, validate and provide feedback directly on the PR. There was no longer a need for an additional video call or to rely on screenshots/screen recordings when reviewers are in different timezones to the authors!   

As a team, we were convinced that this process improvement will help us recover our velocity of delivery. Fortunately for us, we had the right tool and the right information to have an evidence-based discussion with product management to validate the proposed process change. We deployed our preview environment capability around the third week of November and had it running for every PR. The drastic improvement in cycle time is correlated with the PR preview environment we implemented. 

With CloudBees Engineering Efficiency, it is now easier to get the information I need to have data-informed conversations on team health, identify bottlenecks, and opportunities for improvement, and assess the impact of a process change. As an engineering manager, the Cycle Time screen is my absolute favorite. It provides the quantitative data that complements nicely the intuitive and subjective retrospectives to help teams progress in their journey towards becoming high performing. 

Sign up for a one-on-one demo, if you want to see how CloudBees Engineering Efficiency unlocks engineering productivity data to give you the insights to keep your teams focused on delivering value quickly and predictably.

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