Maximize Engineering Productivity: Measure What Matters

Maximize Engineering Productivity: Measure What Matters

Maximize Engineering Productivity: Measure What Matters

As tech startups take off, they must quickly scale their operations and add new features. Even though growth is essential, you must balance it with keeping code quality high and avoiding technical debt, which can be easy to neglect in the rush to grow. If you don’t stay on top of keeping any high-performance engine clean, it will start to break down. It’s shocking how quickly things can go sideways in software engineering, damaging team performance and creating headaches for everyone, including customers.

Measuring engineering productivity is crucial in determining whether your team is on track. By keeping track of different engineering metrics, you can find issues in the engineering process, speed up development, and try other methods, tools, and techniques to improve the engineering process.

Measuring the right things

Measuring the right things is essential to driving desired results. It helps identify areas where you need improvement, guides decision-making, and ensures your teams focus on the right things. Measuring the wrong things can be dangerous, leading to misguided decisions and a lack of focus on the right areas.

Finding the right metrics is critical for tech startups. As tech startups ramp up, they need to scale their operations, add new features, and maintain code quality. If you have the proper measurements, it’s easier to get a good idea of how your engineering team is doing. This can lead to technical debt piling up and the development process slowing down.

Measuring engineering productivity is crucial for tech startups. You can learn more about your engineering process by keeping track of different engineering metrics and using this information to make gradual improvements. For example, if your team is dealing with a lot of technical debt, you can add automated quality gate checks to ensure your product doesn’t degrade.

It is important to note that measuring the wrong metrics can be worse than not measuring at all. For example, the LOC (lines of code) produced daily is dangerous and a poor measure of productivity. LOC-based performance can make people care more about quantity than quality, leading to more technical teams focusing on the wrong areas and not making the most of their development process. Also, it’s been shown that defect rates are highly correlated with LOC, so it’s a balancing act where you want engineers to produce maximum business value with less code.

In conclusion, measuring the right things is essential for tech startups. Good measurements give teams information about your engineering practice health and help teams focus on the right things. Metrics make it easier to tell how well the engineering team is doing and how far they have come. Measuring the wrong things can lead to misguided decisions and a lack of focus on the right areas, resulting in technical debt and slower development processes.

What engineering metrics should be tracked?

It depends on your objectives, but here are four key metrics for engineering productivity that will help you get started:

  1. Cycle Time: This measures when an engineer starts work to when it’s delivered. It helps you measure your team’s momentum.

  2. Deployment Frequency: Track how often you deploy new changes to your production environment. You can also measure deployments to different branches, such as feature branches, hotfix branches, or QA branches.

  3. Number of Bugs: Keep track of the bugs your team has to resolve within 28 days of completing a feature. This will help you understand the quality of your code better.

  4. Review to Merge Time (RTMT): This measures the time between when an engineer asks for a pull request and when it’s merged. It helps you understand how long a change sits in the review state.

These metrics will give you a better understanding of your engineering process. You can then use this data to improve the process to advance engineering productivity. For example, if your team has a lot of technical debt, you could add an extra task that requires developers to write up new features when they finish them.

You can keep your engineering team’s productivity high by tracking key data and making small changes. This allows you to build better and more reliable products faster.

Wrap Up

In conclusion, tech startups need to measure engineering productivity to ensure their engineering process runs smoothly. Keeping track of the right metrics will help you identify issues, speed up development, and try new methods and tools to improve the engineering process. Measuring the wrong things can be dangerous, leading to misguided decisions and a lack of focus on the right areas. Ultimately, your team can get the most out of their engineering process if they measure the right metrics.

Warm regards, Matt


By the way, this is all part of establishing sound engineering practices. There is also the challenge of measuring solution design practices (e.g. UX/UI).

What if there was a way to set up a good product development process across your product and engineering practices with no risk and without having to hire expensive executives, give up equity, or give up control?

If it sounds like something you’d find valuable, it’s why I started Truth Shield. Feel free to hit me up for a chat to see if our program would be a fit for you.

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