Businesses can grow quickly–in fact, that should be the goal. But business growth and scaling operations can come with some challenges–especially when your core business is software.
As organizations grow, they have to constantly evaluate and adjust their processes to scale successfully. Processes that might work for a small company may not cut it for a larger one.
One of the best things a scaling business can do is get comfortable with engineering metrics. It’s through constant analysis and working to optimize these metrics that teams will:
- Help developers become more productive
- Drive predictable software delivery
- Positively impact the business
In this post, we’ll explore 8 core engineering metrics and their role in business success. We’ll also explore tools and strategies to use metrics to strengthen your development teams.
Let’s jump in!
What Are Engineering Metrics?
At the most basic level, engineering metrics quantify and provide a standard of measurement for software delivery–including team collaboration, processes, and business alignment. Metrics benchmarks help teams contextualize these metrics, define “good,” and chart their path forward.
Any given software project has many moving pieces, tracking metrics can help you determine:
- Level of effort and investment to deliver a project on time and in scope
- What, if any, tradeoffs need to happen to make good on promises made to the business
- Any risk indicators–like quality, DevEx, or unplanned work–that may get in the way of delivering
Bottom line: engineering health is business health and engineering metrics have a direct relationship to business performance. Improved engineering metrics are a great predictor of the future success of a company.
What Are the Most Useful Engineering Metrics?
There are lots of engineering metrics available. A great foundational set of metrics are DORA metrics. And every organization likely has different goals, so it’s important to select the most appropriate metrics for your team and what you’re trying to accomplish.
Measuring the right leading and lagging indicators will help you accelerate delivery, maintain a positive culture, and translate development activity to business value. So, what metrics should development leaders benchmark, set goals against, and work to improve? Let’s look at eight metrics that provide a great starting point.
1. Cycle Time
Cycle time–one of the four DORA metrics–is one of the most important metrics for any software development team. It measures the time it takes for a piece of work to go from first commit to deployed in production. In other words, it tracks how quickly a development team brings value to the end user. Keeping cycle time low should be a core focus for every software engineering organization.
Short cycle times lead to higher revenue and a more efficient organization overall. Monitoring cycle time provides development leaders with a clear view of potential bottlenecks that might clog the delivery pipeline.
2. Deploy Frequency
Deploy frequency–another DORA metric–measures how often your team releases code to production. The most mature and healthy organizations deploy multiple times per day or on demand. The best way to improve deployment frequency is to produce smaller pull requests (PRs) more often. Not only does this approach drive better deployment frequency (and overall efficiency), it also:
- Makes testing more manageable
- Increases overall quality–further increasing value delivery to customers
- Reduces Change Failure Rate (CFR) and Mean Time to Restore (MTTR)
*Note: CFR and MTTR are also DORA metrics that are useful to track. They are good indicators of quality and stability. If you’re deploying smaller pieces of code more often there’s less of a chance of something breaking. And when something does break, smaller deployments make it easier to find and fix the problem.
3. Rework Rate
The rework ratio indicates the amount of code that needs to be rewritten after the team delivers it to the end user. For LinearB, rework–unlike refactor–is defined as code that needs to be rewritten after fewer than 21 days have elapsed since deployment.
More often than not, rework is a result of poor quality or poor communication and planning/scoping.
4. High-Risk Branches
This metric indicates that there is a large PR, a high degree of rework, a big percentage of refactor work, or some combination of all three. Besides the obvious quality considerations, high-risk work tends to move slowly through the development pipeline and often requires extra reviews from the team–further compounding any resource constraints that may be present.
One of the best ways to combat high risk work is to use automation that helps find the right reviewer, flag any deprecated components, and provide reviewers with additional context to reduce cognitive load.
Want to eliminate risky behavior around your PRs? Book a demo of LinearB today.
5. Investment Profile
Are your teams focused on high impact, high value work that will move the business forward? Is this in line with industry benchmarks? Investment Profile can tell you. While producing new value for customers via new features and enhancements is a top priority, so is maintaining security, core infrastructure, and application uptime.
Engineering teams need to balance these priorities and make sure that the most precious resource–developer cycles–are spent according to the needs of the business.
LinearB provides a dedicated dashboard for Investment Profile that includes customizable benchmarks that take into account industry best practices as well as your engineering organization’s needs.
6. Context Switching
One of the best ways to increase your team’s productivity and efficiency is getting developers into a flow state and keeping them there. Fun fact: it takes an average 23 minutes to refocus after an interruption. Context switching–where developers are shifting between multiple tasks unrelated to each other–kills focus and makes it impossible to get into a flow state (where developers do their best work). The best way to minimize context switching and minimize interruptions is to provide developers with tools to help them automate tedious tasks, prioritize their day, and offload simple code reviews and approvals.
7. Work In Progress (WIP)
WIP shows you the open items assigned to a developer and how work is distributed across your team. Developer burnout comes from cognitive overload–usually stemming from too much context switching. This context switching starts with too much WIP. Just like the context switching metric, too many open items makes it very difficult to focus and complete tasks.
If you’re a Kanban team, you know that controlling WIP and keeping it consistent is a primary focus to maintain healthy teams and efficient operations.
LinearB not only provides visibility into WIP, it also provides automated alerts and burnout indicators for when a member of your team has too much on their plate.
8. Days Worked
Keeping team members happy and fresh is necessary–that means ensuring they’re taking care of themselves by taking time to rest. The days worked metric measures how many days a member of your team was active during an iteration and helps you take action (like reminding them to take a break) to avoid burnout.
Want to learn how to run a data-driven dev team? LinearB provides several more metrics that are beneficial for engineering leaders.
How to Get the Most Out of Engineering Metrics
Keeping track of all these metrics can be a time-consuming process–especially if you’re doing it manually. It can be even more time consuming to figure out how to action any insights you gain from engineering metrics. And time is a luxury that most teams don’t have. So what can you do to solve this issue?
LinearB SEI+ provides valuable operational and business alignment insight to development teams, allowing them to perfect their software delivery process and deliver more value, more quickly. But beyond that, it includes powerful workflow automation that makes it easy to actually do something with these metrics and benchmarks–driving sustained improvement in efficiency and overall team health.
The platform combines core operational data, engineering resourcing and cost telemetry, external metrics from CI/CD and APM tools, and project forecasting intelligence to provide you with a holistic view of the SDLC–as well as how to improve it.
The Benefits of Engineering Metrics
Engineering metrics provide valuable benefits for software development teams.
- They can increase team productivity by surfacing bottlenecks
- They can help increase the overall quality of the products you ship
- Metrics can even help you reduce costs by alerting you early on about problems that may impact various stages of the software development life cycle
Implementing the right engineering metrics provides development leaders and business executives a shared language that both parties can align on–helping foster a better relationship between these groups, enabling engineering to meet business needs, and making it easier to prove engineering contribution to the bottom line.
