Answer the four questions you have right now

Organizations that learn from data improve faster and more effectively than peers who make decisions based solely on intuition and anecdotes.

Data-Enabled Engineering (DEE) is a methodology that improves on anecdotal decision-making with data and metrics

We believe in data enabling the world of software engineering: empowering teams by giving them insights on their processes from planning to production.

Measure the impact of changes, discover hidden productivity issues, and clearly communicate with all stakeholders on what happens in every part of your organization.

Data-Enabled Engineering helps you answer questions that improve your development processes:

  • How fast are we shipping new features?
  • How quickly are we fixing high priority bugs?
  • How much time did we spend fixing tech debt?
  • Increase visibility
  • Learn about team processes
  • Analyze work distribution
  • Fix bottlenecks

"This difference in deployment speed makes all the difference in delivering value, delighting your customers, and keeping up with compliance and regulatory changes."

Nicole Forsgren, VP at GitHub and coauthor of Accelerate
Adopting data and metrics as part of your engineering culture is a muscle: you have to train it over time

The use of data to measure and improve organizational processes is well established in most other functions: sales, marketing, product, and more. But software engineering has lagged behind, even though we are the ones building it for the other areas!

In recent years, elite performing software companies have started to internally build ways to dig into these metrics. And the result is that software is getting shipped faster, with fewer bugs, and with happier teams.

Athenian was birthed to make Data-Enabled Engineering accessible to everyone.

  • Deploy features faster
  • Fix high priority bugs quicker
  • Recover from incidents faster
  • Lower your change failure rate

“If you can't measure it, you can't manage it.”

Peter Drucker, the father of business studies

DEE is a philosophy part of your engineering culture, supported by tooling.

Data and metrics are only as useful as what you choose to do with them. That's why we're strong believers in DEE as an educational tool to help everyone in your team strategize, and improve.

Beyond numbers in a dashboard: DEE is a cultural methodology that uses metrics as a proxy to help you understand if you're continuously improving. Nothing is more motivating than seeing tangible process: shipping awesome features faster, and fixing nasty bugs quicker.

For example, VPs and CTOs can use insights such as work breakdown between features, bugs and tech debt to determine where to invest more. And Managers can understand how Pull Request Size impacts the code review process.

  • Data-Enabled meetings
  • Improving processes and teams
  • Metrics planning and reviews
  • Objective data as a companion

"To successfully adopt a data-enabled engineering culture, it can not focus on individual engineers - it needs to focus on the way we build software, not who is building it."

Eiso Kant, Founder of Athenian

Let's take an example of an Athenian customer: Gustavo at Magnetis

Magnetis is an online investment platform in Brazil, and Gustavo is a Lead on one of the teams.

Gustavo was first attracted to the idea of DEE to discover why some weeks they would get features out, and others they struggled.

"Once we had Athenian in place, one of the first things we did was question ourselves why our metrics were like they were, without any judgment if they're good or bad."

Using Athenian, one of the areas of interest he identified was that Review Time had been increasing. The team started digging into the pull requests with a high review time, and noticed there was a lot of back-and-forth between team members.

So what did they do? They improved on planning before development. The problem wasn't in the reviews themselves - people were rightfully having discussions. They just weren't aligned on what had to be done in the first place.

Within 3 months Gustavo's team became the best performers at Magnetis as they continued to improve on other processes. And his team of engineers was much happier because their work was reflected in the product more quickly, with a better collaboration process.

After this initial success, the other engineering teams at Magnetis started adopting DEE too.

  • Decreased Lead Time and PR Cycle Time
  • Increased Release Frequency
  • Decreased Wait Time for 1st Review
  • Decreased Mean Time To Restore

"Through Athenian my team became the best performing team at Magnetis, the next step is to now level up the entire organization 💪 !"

Gustavo Aguiar, Technical Lead at Magnetis
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