If you take a look at a 50 person sales team, you’ll likely find it to be very data-driven. The team will typically track dozens of pipeline metrics and variables to help:

focus on the right leads and allocate them to the right AE
create playbooks that increase conversion rates and decrease sales cycle times
establish best practices, letting everyone learn from the best AEs
forecast revenue performance and profitability

If you talk to engineering teams of a similar size, chances are that they don’t use a lot of data to inform decision-making and create alignment in the team. They usually track low-level metrics about their app performance or errors, and agile teams have burn-down charts. But because the data lives in different systems (e.g. Jira, Github, and CircleCI), most engineering leaders are missing out on a lot of the data that they’d need to reliably measure and improve the velocity and quality of their teams and processes.

Software developers are good at math and used to handling large amounts of data, so it’s strange that engineering teams tend to be less data-driven than other departments, isn’t it? Also, engineers are amongst the highest-paid employees and I have yet to meet a tech company that says “we have too many great engineers”. If companies have huge incentives to improve their development process, why is it that engineering teams tend to be less data-driven than you’d expect?

The reason, I think, is that building software to bring data-driven processes to engineering teams (and earning their trust) is very hard. Previous attempts failed or didn’t get a lot of adoption, usually because of some combination of these issues:

Poor data quality. If the solution doesn’t connect with all relevant data sources, misses important metrics, or something is flaky, engineering leaders will quickly lose trust.
Big brother is watching you. Some tools of the previous generation focused on measuring the performance of individual team members, which made it hard to get the buy-in from the team.
So what? Even if you were able to get the data you needed, it frequently wasn’t clear what to do with it. Providing a lot of data is comparably easy. Getting actionable insights is much harder.

Enter Athenian.

Founded by Eiso Kant a little over two years ago, Athenian addresses these issues and empowers engineering organizations to continuously improve with the right data at hand. By integrating with GitHub, Jira, and CI/CD tools, Athenian gives engineering leaders end-to-end visibility into their entire development process. With Athenian, engineering teams can easily get answers to questions like:

How fast do we ship, and where are our bottlenecks?
What’s the quality of the code that we ship, and how fast do we resolve bugs, incidents, etc.?
How are we allocating our engineering efforts, e.g. between fixing bugs, paying off tech debt, and developing new features? Are we aligned towards common goals and objectives?
Are we building a high-performing engineering culture and organization? How can we improve?

Athenian is Eiso’s third startup. His second one, source{d}, was geared towards developers, too (and was a forerunner to today’s renaissance of NLP for code). Eiso is joined by an amazing team including Paul Bleicher, one of Sqreen’s first hires. It’s hard to find a team that is more passionate about empowering developers and more ambitious. That makes us extremely bullish that Athenian is the company that will lead engineering teams out of the dark ages and into a brighter, data-enabled future.

We’re excited to partner with Nathan Benaich, Renaud Visage, Julien Lemoine, Harry Stebbings, Jean de La Rochebrochard, and other friends to join Athenian on this mission.

Why We Invested in Athenian