Accelerate 📗
Our review and analysis of the seminal research by Nicole Forsgren, Jez Humble, and Gene Kim.
Every two months we read a book in our community book club, read it on our own, and review it together in a lively online event.
Last month it was the turn of Accelerate — the foundational research on software engineering performance by Nicole Forsgren, Jez Humble, and Gene Kim.
(shameless plug: you can join the community by becoming a paid member of Refactoring!)
This pick brought back memories.
I read Accelerate in 2019, during a particularly challenging time at my startup. The org had grown quite a bit after we had raised our Series A, and for the first time we were able to split engineers into long-lived, semi-independent teams working on separate product areas.
However, instead of going faster, things started feeling slower. Also, not uniformly so: I felt that some teams were doing better than others, but I couldn’t quite put my finger on why.
So at the time I picked up Accelerate with promise, as I saw one of the authors was Gene Kim. Gene had already written The Phoenix Project, which back then was my favorite engineering book (and still kind of is?!)
Accelerate turned out to be special indeed, marking a before-and-after moment in how I thought about engineering work. It is special in a variety of ways, but first of all because it is based on an astounding six years of research, where the authors surveyed 20,000+ engineers and managers, across 2,000+ organizations.
It was the largest research ever performed on DevOps and software delivery practices, by orders of magnitude.
Such research was also incredibly conclusive. It found clear patterns that correlate good practices to good software delivery performance, and, in turn, good software delivery to business success.
Today, seven years after publication, the foundations laid by Accelerate about how we think at engineering performance, and how we measure it, are still rock-solid and undisputed. So, this review has a two-fold goal: we are going to review the main findings and teachings of the book, but also look at their legacy, and how we have built on top of them since then.
Here is the agenda for today:
📊 More than just metrics — if you think Accelerate == DORA metrics, you are simply missing out.
🪴 Cultural capabilities — looking into transformational leadership and generative culture.
🔄 Process & management capabilities — how to make your work flow well, create tight feedback loops, and minimize waste.
⚙️ Technical capabilities — how to enable elite software delivery that will drive immense business value.
💡 Key findings — my favorite takeaways from the book, like the speed vs stability paradox, and the link between engineering and business excellence.
Let’s dive in!
📊 More than just metrics
Ask anyone about Accelerate, and chances are they will mention the DORA metrics.
These four KPIs define how teams can measure software delivery performance, and became instantly famous after the book’s publication. They are:
🚀 Deployment Frequency — how often you release to production.
⏱️ Lead Time for Changes — the amount of time it takes a commit to get to production.
📉 Change Failure Rate — the percentage of deployments causing a failure.
🛠️ Time to Restore Service (MTTR) — how long it takes to recover from a failure.
One of the reasons why the metrics caught on is because they provided, for the first time, a research-backed way to evaluate software delivery across two dimensions:
Throughput → via Deployment Frequency + Lead Time for Changes.
Stability → via Change Failure Rate + MTTR.
But here’s the thing: if you think Accelerate is only about metrics, you're missing 90% of the picture.
Last week I interviewed Abi Noda, founder of DX, on the podcast (the episode will come out on Friday). We briefly touched on Accelerate and Abi said there's a kind of a running joke among the insiders — people who've been around during the whole Accelerate work. And the joke is that, when the book got published, it’s like everyone just read the page with the four metrics and then put down the rest of the book.
Obviously in the book there's a definition of these four key metrics that have statistical power behind them. But really the book is about: how do you transform an organization? What are the best practices that organizations should be focused on at that time in the industry? And the metrics are just a way of sort of demonstrating and verifying the value of adopting those practices.
— Abi Noda, CEO of DX
So, the core of Accelerate is not the metrics: it's the engine that enables them.
The book meticulously identifies and validates 24 key capabilities that are statistically shown to improve software delivery performance. The metrics are the outcome, while the capabilities are the drivers.
And the research proves this connection with extreme rigor. It moves the conversation from "what good looks like" to "what specific actions demonstrably lead to good."
So, I don’t want to discount DORA metrics, which have been incredibly consequential to our industry (to learn more about them, you can check out our full guide), but today we’ll focus on capabilities, which to me are the real star of the book.
24 is a big number, so, with some degree of simplification, let’s start by organizing capabilities into three buckets: cultural, process, and technical.
These buckets work as levels of a pyramid, each one supporting the health of the ones above:
Good culture is what makes people work well together and feel good about their work environment. It keeps retention high, stress low, and enables the creation of good process 👇
Process exists to make work flow well through the system. Good process is about tight feedback loops and minimizing waste.
Good culture and good process naturally lead to the technical practices that enable elite software delivery, like continuous deployment and empowered teams.
🪴 Cultural capabilities
Accelerate identifies five key cultural capabilities displayed by elite teams:
🧭 Transformational Leadership — having leaders who inspire and motivate their teams, possess a strong vision, stimulate their staff intellectually, and provide individual consideration and support. These leaders foster the trust and psychological safety needed for a generative culture to thrive 👇
🌱 Westrum Generative Culture — high-performing orgs exhibit a generative culture characterized by high cooperation, shared risks, treating failure as a learning opportunity, and encouraging novelty. Information flows freely, and messengers aren't punished for delivering bad news. The concept of generative culture is so important that we covered it in a dedicated newsletter edition.