10 Metrics Every CTO Needs to Know

This post is part of our historical archive. It represents the beliefs, actions, products, and services of Code Climate as of its publication date. Today, Code Climate focuses on providing enterprise leaders the software development data, context layer, and playbooks needed to build the AI-native software organization their enterprise needs.

Nov 21, 2022 - 1 min read

The most successful engineering leaders incorporate objective data into their leadership strategies. Numbers can’t substitute for a CTO’s experience and instincts, but when it comes to decision-making, leaders can use metrics in software engineering to inform their decisions and align with stakeholders.

Different leaders optimize for a different set of metrics depending on company priorities and the needs of their engineering teams. Yet, if you’re introducing metrics to your team, or refining your approach to metrics, there are key measurements worth considering.

At Code Climate, we’ve worked with thousands of organizations, from startups to enterprises, and we know that there are a few key metrics that have proven time and again to be valuable, even if they’re just a starting point!

Whether you’re just starting to incorporate data into your leadership, or are refining your approach to measurement, these 10 metrics are important ones to consider.

They can help you:

• Get a handle on your organization’s Time to Market,
• Ensure your team is adhering to CI/CD best practices,
• Measure the quality of your code, and
• Assess the efficacy of your planning processes.

To find out which 10 metrics you need to know, how to apply them effectively and resolve bottlenecks, download the ebook.

Why a Strategy Matters

At the heart of every successful software engineering team is a drive for three things:

1. A culture of continuous improvement
2. The ability to move from idea to impact quickly, frequently, and with confidence
3. A software organization delivering meaningful value

These goals sound simple enough, but in reality, achieving them requires more than just wishing for better performance. It takes data, action, and, most importantly, a cultural shift. And here's the catch: those three things don't come together by accident.

Step 1: Define Your Purpose

The first step in any successful engineering insights strategy is defining why you're doing this in the first place. If you're rolling out developer productivity metrics or an insights platform, you need to make sure there’s alignment on the purpose across the board.

One way I recommend approaching this is through the "Five Whys" technique. Ask why you're doing this, and then keep asking "why" until you get to the core of the problem.

Step 2: Understand Your People

Once the purpose is clear, the next step is to think about who will be involved in this journey. You have to consider the following:

1. Who will be using the developer productivity tool/insights platform?
2. Are these hands-on developers or executives looking for high-level insights?
3. Who else in the organization might need access to the data, like finance or operations teams?

Step 3: Define Your Process

The next key component is process—a step that many organizations overlook. It's easy to say, "We have the data now," but then what happens? What do you expect people to do with the data once it’s available?

A common mistake is organizations focusing on metrics without a clear action plan. Instead of just looking at a metric like PR cycle times, the goal should be to first identify the problem you're trying to solve.

Step 4: Program and Rollout Strategy

The next piece of the puzzle is your program and rollout strategy. It’s easy to roll out an engineering insights platform and expect people to just log in and start using it.

Step 5: Choose Your Platform Wisely

And finally, we come to the platform itself. It’s the shiny object that many organizations focus on first, but as I’ve said before, it’s the last piece of the puzzle, not the first.

Looking Ahead

To build a successful engineering insights strategy, you need to go beyond just installing a tool. An insights platform can only work if it’s supported by a clear purpose, the right people, a well-defined process, and a program that rolls it out effectively.

Remember, a successful software engineering insights strategy isn’t just about the tool. It’s about building a culture of data-driven decision-making, fostering continuous improvement, and aligning all your teams toward achieving business outcomes.