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A perennial challenge for engineering leaders is how to build and lead high-performing teams.
Velocity is a huge part of achieving this, but velocity itself can be difficult to understand and navigate as many factors in engineering affect it. This series looks at a variety of these factors and provides guidance on how to harness the information they can provide to accelerate engineering teams.
Episode 1: Recognizing and removing project bottlenecks
This conversation centered around looking at engineering velocity holistically and how to navigate bottlenecks from all angles, with our panelists – Victor Vu (Senior Software Engineer at Credit Karma), Sara Hicks (VP of Product Management at Mailchimp), Said Ketchman (Director of Engineering at The New York Times), and TJ McNichols (Director of EMEA Sales at Pluralsight) – and moderator – Smruti Patel (Head of LEAP Engineering and Big Data Platform at Stripe) – discussing their own experiences of doing so.
During this discussion, our panelists explored:
- Why speed and execution matters in engineering velocity
- How to set expectations, estimates, and deadlines with stakeholders on large, ambiguous projects before execution
- How to identify bottlenecks in projects that are under execution and blocked – the factors to consider, and what tools and metrics can be leveraged
- How organizational culture can help or hurt project delivery, the pitfalls to avoid, and the best practices to nurture
- How to balance autonomy of team members with smooth delivery of projects.
‘If an engineering organization of 100 developers can drive a 10% improvement in delivery efficiency, it can result in increasing the throughput by 10 more developers!’
Siva Hota and Siva Dosapati share their insights from driving efficiency at Indeed in this article, and how this can be done through the tracking of metrics. They discuss the different metrics that can be used to measure efficiency, which metric they chose at Indeed and why – as well as how they developed it, and the challenges they faced when rolling this out at scale.
‘Being a data-driven leader can help you to understand and analyze the larger context of development work, know what’s working (or not), and bring the right resources in to propel teams and individual engineers to do their best work.’
In this article, Jeremy Morgan deep dives into the power of data and how engineering leaders can harness it to create a healthy, high-performing team. Jeremy answers the following questions in great detail to give the reader a well-rounded understanding of data-driven leadership:
- What problems can leaders face without data?
- What is data-driven engineering leadership? And what is it not?
- Why does leading engineering teams with data, work?
- How can data optimize workflows and meetings?
- How can data boost team health?
‘The importance is in reducing friction in micro-feedback loops, how those improvements will compound to product delivery and DevOps performance, and creating a culture that empowers that.’
When Tim Cochran analyzed the habits of engineering organizations, he discovered that those that were high-performing had made use of feedback loops and measured them correctly. In particular, Tim explores the use of micro-feedback loops and their impact: ‘Fixing the small things has a massive amount of benefit and has compounding effects, including reducing the cognitive energy for developers’. Tim then delves into how to optimize micro-feedback loops, the importance of information discoverability within this, and measuring productivity.
A final takeaway
This series highlights how deconstructing engineering velocity is no simple task, and that there are several paths an engineering leader must take to nurture the efficiency and performance of their team. However, the practical advice and insights shared within these content pieces demonstrates that it can be done. By gaining a deeper understanding of their team through data and the tracking of metrics, engineering leaders can effectively steer their engineers to success.