I find myself explaining the value of adopting outcome-based engineering analytics every day, using the Accelerate book as the definitive reference for why they are important. It’s also common that busy executives (not necessarily from Engineering) still aren’t familiar with the theory and findings that were published in Accelerate (2018).
This post is an attempt to condense those findings. However, I still highly recommend that you read the book.
“Accelerate does a fantastic job of explaining not only what changes organizations should make to improve their software delivery performance, but also the why, enabling people at all levels to truly understand how to level up their organizations.”Ryn Daniels, Infrastructure Operations Engineer at Travis CI and author of Effective DevOps
Key findings from the Accelerate book
For the research supporting the book, the team collected survey responses from:
- Over 2,000 unique organizations;
- Of all sizes, such as small startups (of under five employees) to large enterprises (with over 10,000 employees);
- Operating in all industries, including finance, healthcare, and government.
The authors discovered that:
- There are four key metrics – defined below – that are good classifiers of software delivery performance;
- Higher software delivery performers in those metrics are twice as likely to exceed organizational business goals (profitability, productivity, and market share);
- Culture and technical practices have an impact on software delivery performance, and both are measurable.
The key metrics are defined as:
- Deployment frequency: How often your organization completes a deployment to production or releases code to end-users of your primary application or service.
- Lead time for changes: How long it takes a commit to get into production on your primary application or service.
- Time to recover: How long it takes your organization to recover from a failure in production (e.g., service impairment or unplanned outage).
- Change failure rate: Percentage of deployments causing a failure in production (e.g., service impairment or unplanned outage) and that subsequently require remediation.
You can read more about each metric and how it can be used in practice in our blog series about the Accelerate metrics.
Finally, there are 24 key practices that are linked with the four key metrics, and consequently drive software delivery performance. The practices are classified into five categories: Continuous delivery, Architecture, Product, Lean management, and Cultural. You can explore more about each practice on the authors’ website.
The authors validated these findings whether an organization uses a traditional “waterfall” methodology, or has been implementing Agile and DevOps practices for years.
Other interesting findings
- The five factors most highly correlated with burnout are organizational culture (negative), leaders (negative), organizational investment (negative), organizational performance (negative), and deployment pain (positive).
- High performers spend 50% less time remediating security issues than low performers.
- There is no significant difference depending on the type of architecture teams are building or integrating against.
- The ability to take an experimental approach to product development is highly correlated with the technical practices that contribute to continuous delivery.
- Employees in high-performing teams are 2.2 times more likely to recommend their organization as a great place to work.
You might also be interested in a subsequent study from the same authors that shows the cost-saving in saved engineering time by adopting these practices and excelling at the key metrics:
If you are interested in measuring these metrics for your team, get started for free.