DORA metrics, productivity, and team performance

Cycle time: the DORA metric that actually changes behavior

Cycle time is the DORA-adjacent metric leaders love and misread constantly. Here's how to measure it, what it hides, and how teams game it.

Change failure rate: the DORA metric everyone quotes and nobody measures right

Change failure rate is the DORA metric leaders love to cite and teams love to game. Here's how to measure it honestly — and why flaky tests corrupt it.

Change failure rate: the DORA metric everyone measures wrong

Of the four DORA metrics, change failure rate is the one teams most often measure wrong — and the one most contaminated by flaky CI. Here's how to get it right.

Change failure rate is lying to you if your tests are flaky

If flaky tests trigger rollbacks or reruns, your change failure rate is counting noise as incidents. Here's how to fix the signal before it reaches leadership.

Git metrics that actually tell you something useful

Most teams collecting git metrics end up measuring the wrong things. Here's how to cut through the noise and focus on signals that actually reflect engineering health.

Building culture with cycle times

Engineering Metrics: How cycle time can be a cornerstone in building a robust engineering culture.

Code Readability

Engineering Metrics: How does it impact the broader development process?

Quality gates in pull requests

Engineering Metrics: Quality gates play a pivotal role in ensuring that the code meets the desired standards before it's merged.

Different ways of measuring code complexity

Engineering Metrics: Add a sentence here that will hook readers

Which git metrics should I be looking at?

Engineering Metrics: With a plethora of metrics available, which ones truly matter?

What is tech debt?

Engineering Metrics: Imagine borrowing time from the future to meet present needs.

How engineering leaders maintain sync with stakeholders

Engineering Metrics: This bridge is built on trust, transparency, and most importantly, metrics.

Preventing performance review bias

Engineering Metrics: Unconscious preferences can skew perceptions, biases can lead to unfair and unrepresentative assessments.

Why does deploy frequency matter?

Engineering Metrics: Let's explore the significance of deploy frequency and its implications in the software development landscape.

Efficient pull requests: the pathway to enhanced software quality

Engineering Metrics: We dive into best practices for pull requests, emphasizing the importance of a meticulous yet swift code review process.

Benefits of engineering intelligence

Engineering Metrics: The phrase "what gets measured gets managed" holds profound significance.

Building a data-driven engineering culture

Engineering Metrics: Let's explore the steps and strategies that can help teams harness the power of metrics to drive excellence.

Beyond story points and ticket status

Engineering Metrics: Traditional project management tools, which often revolve around story points and ticket statuses, might not be the best indicators of genuine progress.

The power of sprint velocity

Engineering Metrics: What is sprint velocity, and how does it fit into a broader, data-driven engineering culture?

Measuring your software delivery pipeline effectively

Engineering Metrics: Sofware delivery pipelines encompass both the 'how' - the stages like coding time, pickup time, and review time, and the 'what' - outcomes.

What is merge time?

Engineering Metrics: Among these guiding stars, merge time shines brightly, offering a glimpse into the efficiency of the engineering process.

How to accelerate engineering velocity?

Engineering Metrics: How can velocity be accelerated? Let's delve into the strategies, metrics, and tools that can supercharge your engineering velocity.

Measuring engineering performance without damaging culture

Engineering Metrics: Let's explore how engineering leaders can harness metrics to boost performance without compromising team culture.

Understanding engineering effectiveness

Engineering Metrics: Let's delve into the world of engineering metrics and explore how they can be harnessed to understand effectiveness without damaging the culture.

The 4 pillars of engineering productivity

Engineering Metrics: Enter the four pillars of engineering productivity: code velocity metrics, throughput metrics, quality metrics, and goals.

Engineering Productivity: how to measure and improve it

Engineering Metrics: Metrics like cycle time, lead time, and lines of code offer invaluable insights into the efficiency of the development process.

Improve productivity with just these 5 metrics

Engineering Metrics: While there are numerous metrics that engineering teams can track, focusing on the right ones can make all the difference.

How to improve cycle time and estimation

Engineering Metrics: As your organization grows, understanding and optimizing the performance of your engineering team becomes a non-negotiable.

Why start measuring engineering metrics and impact today

Engineering Metrics: As the digital realm evolves, understanding and optimizing the performance of your engineering team becomes a non-negotiable.

Enhancing engineering impact with metrics

Engineering Metrics: Organizations can enhance engineering impact through the strategic use of metrics, process optimization, and fostering a culture of continuous improvement.