Software Development KPIs: How To Measure Your Team's Efficiency

Effectively measuring the performance of a software development team with the right software metrics is a necessary step to achieving the software project goals.

Appropriate software development metrics will help you assess performance and provide meaningful insights needed for improvement. On the contrary, adopting ephemeral metrics is not only difficult, but it can also be counterproductive, dangerous, and misleading.

Useful Metrics & Which Ones To Choose From?

When we think about productivity, we often try to measure it by focusing on performance rather than results. It's a way of telling our teams that they value the amount of functionality we provide to our end users versus the actual value they provide. However, we also often make the mistake of putting individual measures ahead of collective ones. We reward individual performance for the overall result more.

Velocity is an agile KPI that is used to track the amount of work completed during a sprint. It is usually measured in hours or story points. Project managers use team velocity to calculate how quickly software development teams can clear the backlog. When these metrics are misused, teams attempt to increase their velocity by inflating estimates and completing as many stories as possible, forgetting the real goal: solving the customers' business problems.

Additionally, according to a recent BCG survey, 70% of digital transformation projects fail due to three major factors: unrealistic expectations, a lack of technical documentation, and a failure to consider customers.

These three aspects are strongly influenced by how we manage and control the processes involved in the value stream. Knowing how to structure the control process and measure the performance of our team plays a fundamental role in reducing the risk of failure.

When we say the metric is good, we must consider the overall outcome rather than a single output. A popular concept in DevOps culture summarizes this phenomenon: "the wall of confusion." This refers to a situation where, in the value stream, one group relays its completed task to the next group, completely ignoring the ultimate value. This frequently occurs when developers figuratively throw their completed tasks “over the wall" to their operational colleagues, who in turn have difficulty integrating with them and getting the final version of the software to work in production.

Instead, focus on the following criteria when measuring performance.

1. Delivery Lead Time

Lead time measures the time it takes for code to go into production. This metric is based on lean theory and tracks the time it takes to respond to a customer request. In complex systems, such as software development, it is contextualized as a product development metric.

Delivery lead time measures a project's ability to deliver software. Product delivery in agile product development mainly consists of a design phase and a delivery phase. The design phase is a phase where technical architects and software engineers define the technical details of the product. Depending on the project, these details may include screen designs, databases, sketches, system interfaces, and prototypes.

Software delivery is the entire process of delivering a software product to customers, from design, development, product license purchase, and installation. In the delivery phase, things are a little clearer, cycle times should be predictable and results should have little variability. The entire workflow is done seamlessly and as quickly as possible. Therefore, the metric for lead time to look for is a product deployment which is measured as the time taken between committing the code to the repository and successfully running the function in production.

High-performing teams are able to keep product delivery times as short as possible to enable quick feedback and rapid course corrections.

2. Deployment Frequency

Deployment frequency is simply the rate at which an organization successfully releases software to production. This metric supports the core value proposition of agile methodology, that the modern software delivery organization's goal is to continuously deliver software to maximize end-user value.

The term "deployment" refers to the introduction of software artifacts into a production environment, which in turn is similar to a product release. Engineering teams measure deployment frequency simply by counting how many times they are deployed over a period of time. This meter is very easy to measure. Teams can measure deployments on a weekly or daily basis.

3. Time To Restore Service

The mean time to restore is the average time it takes to recover from a deployment failure, incident, or service outage. It measures the time between the detection of an event or fault and the restoration of full system functionality.

In complex and uncertain environments, failures are constant. They happen all the time, with varying degrees of severity. The majority of the time, they are not even recognizable to the end user. Errors that prevent your end users from using your service are the most common errors you need to account for in this metric.

Restoring service to the user should be your primary goal in the event of errors. You want to measure your performance by how long it takes your team to solve a problem in production. It is a valuable metric that helps you understand your team's capabilities and how quickly they react to problems and setbacks.

Due to the complexity of these systems, this not only measures how quickly you respond to service outages but also how well your system is designed. Installing a patch on poorly designed systems makes this metric very long, whereas with a well-designed infrastructure you can fix the problem very effectively. The efficient teams I've seen in the industry are able to restore service in less than an hour on average.

4. Change Fail Rate

Change the failure rate measures the percentage of deployments that fail in production and eventually require some type of repair (post-deployment repair, patch, or rollback). It measures the quality and stability of your team structures. The best-performing teams have a change failure rate of around 10%.

Building effective software development teams require a great deal of discipline and a good performance-tracking system tailored to what is truly valuable to the end user. By looking at these metrics, you are on your way to improving these teams and serving your customers well.