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Measuring Success in Software Development: A Guide for Leaders

Discover how to measure software delivery performance with key metrics that optimize workflows, enhance team productivity, and drive better decisions.

In order for organizations in any industry to be successful today, they need to balance a host of responsibilities: providing high-quality digital experiences, keeping up with the latest tech, delivering value efficiently, and maintaining customer satisfaction, all while shipping secure, vulnerability-free code.

To manage this huge task, leaders need a reliable, scalable way to measure their success — because accurate metrics can lead to actionable insights. Tracking the right metrics can help software development teams optimize workflows, minimize disruptions, identify and resolve bottlenecks, enhance productivity, and improve developer experience. Put together, these pieces can ultimately help you make better, more informed decisions and meet your business goals.

But with all the challenges facing today’s software teams, how do you know which metrics to track? And how can you implement these measurement frameworks without adding even more bottlenecks to your team’s workflow?

Common challenges in SDLC measurement

There are numerous challenges when it comes to software development lifecycle (SDLC) measurement. From a leadership standpoint, reliably measuring the business value of the software development process requires better visibility across the software supply chain and a deeper understanding of business metrics.

From a development team perspective, there are even more day-to-day hurdles:

  • The complexity of fragmented toolchains and processes, siloed work environments, and lack of team collaboration often get in the way of making lasting improvements in software delivery.
  • Delays in the code review process — despite the fact that code reviews help teams identify bugs, maintain compliance, and improve security — make it difficult for teams to find the right balance of speed and security.
  • Shrinking IT budgets mean teams have fewer resources to put toward measurement.
  • Teams are still trying to identify if their AI investments are worth it, while also grappling with issues related to AI-generated code, such as code quality and security concerns.
  • They simply don’t know which key performance indicators are worth measuring and how individual metrics are connected.

Read the full ebook to learn how engineering leaders can overcome these challenges and effectively measure the value of their team’s software delivery. Explore industry-wide metrics such as deployment frequency and change failure rate, individual team performance stats, and strategies on how to best implement these measurement frameworks for long-term operational efficiency and continuous improvement, from the first line of code to production and beyond.

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Measuring Success in Software Development: A Guide for Leaders

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Key takeaways
  • Modern software teams face complex challenges in measuring success, from fragmented toolchains to resource constraints. Effective measurement frameworks help balance speed, security, and quality while providing visibility across the supply chain.
  • The right metrics enable teams to optimize workflows, resolve bottlenecks, speed up time to market, and improve developer experience. Leaders need reliable data to compare performance across teams and benchmark against industry standards.
  • Implementation strategies for measurement frameworks should focus on long-term operational efficiency, from initial code development through production, while adapting to new challenges like AI-generated code.