Tips for Understanding Developer Productivity

🛠️ Measuring Developer Productivity: It’s Complex but Crucial! 🚀 Measuring software developer productivity is one of the toughest challenges. It's a task that requires more than just traditional metrics. I remember when my organization was buried in metrics like lines of code, velocity points, and code reviews. I quickly realized these didn’t provide the full picture. 📉 Lines of code, velocity points, and code reviews? They offer a snapshot but not the complete story. More code doesn’t mean better code, and velocity points can be misleading. Holistic focus is essential: As companies become more software-centric, it’s vital to measure productivity accurately to deploy talent effectively. 🔍 System Level: Deployment frequency and customer satisfaction show how well the system performs. A 25% increase in deployment frequency often correlates with faster feature delivery and higher customer satisfaction. 👥 Team Level: Collaboration metrics like code-review timing and team velocity matter. Reducing code review time by 20% led to faster releases and better teamwork. 🧑💻 Individual Level: Personal performance, well-being, and satisfaction are key. Happy developers are productive developers. Tracking well-being resulted in a 30% productivity boost. By adopting to this holistic approach transformed our organization. I didn’t just track output but also collaboration and individual well-being. The result? A 40% boost in team efficiency and a notable rise in product quality! 🌟 🚪 The takeaway? Measuring developer productivity is complex, but by focusing on system, team, and individual levels, we can create an environment where everyone thrives. Curious about how to implement these insights in your team? Drop a comment or connect with me! Let’s discuss how we can drive productivity together. 🤝 #SoftwareDevelopment #Productivity #TechLeadership #TeamEfficiency #DeveloperMetrics

A lot of leaders ask me about using velocity to measure development team performance. I *love* story points and velocity, but they're useful for other things--not truly understanding the ability for teams to deliver. The question to ask is, "What is my team's ability to *ship software*?" I encourage leaders to focus on the four DevOps Research and Assessment (DORA) metrics around Software Delivery Performance if they want to understand how their development organization is operating: Lead Time for Changes How long does it take to go from code committed to code successfully running in production? Deployment Frequency How often does your organization deploy code to production or release it to end users? Change Failure Rate (aka "How often do we break stuff?") What percentage of changes to production or released to users result in degraded service (e.g., lead to service impairment or service outage) and subsequently require remediation (e.g., require a hotfix, rollback, fix forward, patch)? Time to Restore Service (aka "How long does it take to fix it?") How long does it generally take to restore service when a service incident or a defect that impacts users occurs (e.g., unplanned outage, service impairment)?

Critique this (real) team's experiment. Good? Bad? Caveats? Gotchas? Contexts where it will not work? Read on: Overview The team has observed that devs often encounter friction during their work—tooling, debt, environment, etc. These issues (while manageable) tend to slow down progress and are often recurring. Historically, recording, prioritizing, and getting approval to address these areas of friction involves too much overhead, which 1) makes the team less productive, and 2) results in the issues remaining unresolved. For various reasons, team members don't currently feel empowered to address these issues as part of their normal work. Purpose Empower devs to address friction points as they encounter them, w/o needing to get permission, provided the issue can be resolved in 3d or less. Hypothesis: by immediately tackling these problems, the team will improve overall productivity and make work more enjoyable. Reinforce the practice of addressing friction as part of the developers' workflow, helping to build muscle memory and normalize "fix as you go." Key Guidelines 1. When a dev encounters friction, assess whether the issue is likely to recur and affect others. If they believe it can be resolved in 3d or less, they create a "friction workdown" ticket in Jira (use the right tags). No permission needed. 2. Put current work in "paused" status, mark new ticket as "in progress," and notify the team via #friction Slack channel with a link to the ticket. 3. If the dev finds that the issue will take longer than 3d to resolve, they stop, document what they’ve learned, and pause the ticket. This allows the team to revisit the issue later and consider more comprehensive solutions. This is OK! 4. After every 10 friction workdown tickets are completed, the team holds a review session to discuss the decisions made and the impact of the work. Promote transparency and alignment on the value of the issues addressed. 5. Expires after 3mos. If the team sees evidence of improved efficiency and productivity, they may choose to continue; otherwise, it will be discontinued (default to discontinue, to avoid Zombie Process). 6. IMPORTANT: The team will not be asked to cut corners elsewhere (or work harder) to make arbitrary deadlines due to this work. This is considered real work. Expected Outcomes Reduce overhead associated with addressing recurring friction points, empowering developers to act when issues are most salient (and they are motivated). Impact will be measured through existing DX survey, lead time, and cycle time metrics, etc. Signs of Concern (Monitor for these and dampen) 1. Consistently underestimating the time required to address friction issues, leading to frequent pauses and unfinished work. 2. Feedback indicating that the friction points being addressed are not significantly benefiting the team as a whole. Limitations Not intended to impact more complex, systemic issues or challenges that extend beyond the team's scope of influence.

The only effective way to measure developer productivity is by measuring developer experience. Nothing else really works. Number of pull requests or deployments are at best fuzzy and at worst misrepresentative. A better signal: whether developers *feel* productive or not. Then layer on the sentiment of peers and managers. Cycle times and lead times don’t tell you how effective teams are – more so just how they shape their work. A better signal: asking developers about their workflows and points of friction that slow them down. I know not all agree with this but I've worked with hundreds of 250+ eng organizations where DevEx is the only approach that has worked.