What, why, and how should you be measuring as an engineering leader?
Data-driven leaders are empowered to make decisions based on facts, rather than instincts. They use metrics to gain visibility over their teams, spot problems, and celebrate and communicate success with the wider business.
But getting started with data-driven leadership isn’t easy. It’s natural to feel overwhelmed by the number of things you could be measuring. In this series, we explored how engineering managers, directors, and VPs can leverage metrics to build happier, more productive teams across all levels of an organization.
How can you make sure you’re measuring the right things? In this panel discussion, we brought together a group of leaders to share how they use data to get the best out of their systems.
Featuring Dalia Havens (VP of Engineering at Replicated), Cat Swetel (Technology Leader at Agile Alliance), James McGill (VP of Engineering at Code Climate), and Juan Pablo Buriticá (engineering leader), the panel discussed:
- The fundamentals of engineering metrics at every level
- Which metrics are useful and which should be avoided
- Actions and strategies to evaluate your measurements from a leader's perspective
- How to interpret your metrics to ensure that you’re not jumping to false conclusions
How are other engineering leaders using metrics? We asked Cody Lee (Engineering Manager at Splice), Leslie Cohn-Wein (Engineering Manager at Netlify), Abi Noda (developer experience expert), and James McGill (VP of Engineering at Code Climate) for their perspectives on what works when it comes to metrics.
Drawing on years of experience, they shared why they use metrics (to foster continuous improvement and become better-informed), examples of metrics that have worked for them (measuring cycle time and user satisfaction), and how they analyze their data (looking for trends and always considering the wider context).
Data-driven tech leaders use metrics to empower their engineers and improve productivity. But how can you foster this style of leadership? In this article, Carlos Coelho shares how he started using metrics to increase his team’s knowledge, accelerate their delivery time, and build better software.
From collecting their initial metrics to diving deeper into their development data, Carlos explains how measuring different aspects of the development process gave him more insight into his team’s performance, and revealed easy steps he could take to improve their processes.
Too often, daily standups feel like a waste of time. By introducing metrics to your meetings, you can keep your conversations focused on tangible updates and actions, rather than vague, high-level descriptions of people’s work.
In this article, Khan Smith shares his advice for using metrics to run more impactful standups, from looking at data to identify important issues before your meetings, to asking your team for measurable updates so that you can uncover more risks before they develop into problems.
How can engineering managers use data to improve their team’s workflow and surface more risks in daily meetings? In this roundtable discussion, we brought together a group of engineering managers to share their experiences of working with metrics.
After a short presentation from Khan Smith (VP of Product at Code Climate), the group discussed how they use metrics (for example, to measure the development cycle); how they run daily standups (asking what folks worked on yesterday and today, and if there are any blockers); and how those standups might be improved through metrics (looking at open PRs and tickets beforehand to understand the status of projects).
How can metrics help engineering directors keep track of complex projects across multiple teams? In this roundtable discussion, a group of engineering directors came together to share how they use metrics to improve the performance and satisfaction of their teams.
Following a presentation from James McGill (VP of Engineering at Code Climate), attendees shared what metrics they use across all their teams (including lead time, deployment frequency, and wait time at different stages); examples of when these metrics lead to improvements in the team (looking at cycle time can help to identify bottlenecks), and when they might have had a less positive effect (focusing too much on velocity can cause stress for engineers).
Engineering VPs are faced with the challenge of communicating the state of their department to non-technical folks on the executive team and board. Using metrics can help them to talk about their work in a quantifiable way, advocate for their teams, and push for engineering’s seat at the table.
In this roundtable discussion, we brought together a group of engineering VPs to share their best practices for using metrics at this level. After a presentation from Brian Helmkamp (CEO of Code Climate) around what CEOs want to hear from engineering, attendees reflected on their own approaches to data-driven reporting.
Setting Objectives and Key Results (OKRs) can help engineers stay focused on clear goals while allowing managers to keep track of progress by looking at measurable results. But introducing OKRs to a team can be hard, as folks often struggle to agree on goals and metrics for success.
In this article, Daiany Palacios shares advice for getting started with your team. By starting off with a ‘good enough’ approach – prioritizing general alignment around goals before slowly introducing metrics once the framework is in place – you can avoid demotivation among your engineers, and take time to make sure you’re measuring the right things.
A final takeaway
Whether you’re an engineering manager, director, or VP, identifying the right things to measure can be a challenge. But getting your head around metrics is essential if you want to solve more problems and celebrate more successes in your teams. As Brian Helmkamp summarized, ‘All metrics are flawed; some are useful. With the right data, you can back up your conclusions and requests, cultivate a culture of transparency, solve problems quickly, and celebrate accomplishments and progress.’
By taking time to think about your goals, developing the skills to analyze your data, and building metrics into your everyday planning and startups, you can kickstart your journey to becoming a data-driven tech leader. Good luck!