Software development is a complex and multifaceted process that often involves multiple challenges, from requirement changes to addressing last-stage defects on a tight deadline.
To create software development processes that enable the timely delivery of high-quality products, dev teams must be on the same page, working toward the same goals and objectives, and collaborating to improve continually. For that reason, Key Performance Indicators (KPIs) are a vital element of software development. They act as a navigational tool to ensure that projects remain on track and meet their objectives.
KPIs provide an objective measurement of progress, enhance accountability, and help keep teams in alignment with the business’s goals. Once a team chooses a quantifiable goal to apply KPIs, members can benchmark their progress and ensure they’re on pace to complete the work. If a particular KPI reveals that they are not hitting a specified target, the team can focus on identifying and addressing the cause of the setback.
KPIs allow dev teams to make decisions based on data rather than instinct, enabling them to avoid costly mistakes and conserve resources to improve processes that objectively need work.
KPIs also equip managers with proof of progress to communicate with executives, clients, or other stakeholders. Additionally, they can be used to illustrate a need for more resources to implement process improvements.
Overall, KPIs matter because they:
You can tailor KPIs to measure anything you need to track, from code quality to customer satisfaction. The key to implementing valuable KPIs is to choose the ones that measure the most critical aspects required to reach short-term or long-term goals. In other words, if a KPI does not provide insight and help your team reach its goals, it’s not the right KPI.
Before selecting or developing KPIs, you need to understand what you want to measure and why. What are your goals? What can you measure to align with those goals? KPIs should also be realistically achievable.
To help you get started, here are some of the most important software development performance metrics to consider tracking depending on your software development methodology:
Sprint velocity is a metric commonly used in the Agile Scrum framework to evaluate team efficiency within a sprint. It involves calculating the average number of tasks, hours, days, or story points completed over a specific number of sprints. It does not measure work quality and should be considered within context.
As an example of how to calculate sprint velocity, imagine a team completes the following story points in three sprints:
In the above example, the average sprint velocity is 12. Sprint velocity should gradually increase if a team is actively making performance improvements until the team reaches a consistent rhythm. If something breaks the team’s rhythm such as turnover, velocity typically decreases, anytime velocity decreases the team should pause to determine the cause of lower sprint velocity and address internal or external factors contributing to inefficiencies.
Management can also use sprint velocity to predict how much work their team can complete in a sprint and avoid over-committing.
Lead time is another metric commonly found in Agile project management. Lead time measures the amount of time a team spends moving an assignment through a client’s kanban from project request to completion. A shorter lead time indicates efficient and refined workflows, while a longer lead time points to a challenge that needs to be addressed. Common issues affecting lead time include lack of prioritization and siloed systems.
Cycle time enables managers to assess developer’s productivity and can also help them understand a long or short lead time. By tracking cycle time, managers can see how long a developer takes to complete a task after it’s been assigned and determine if they face challenges with productivity. They can also identify whether certain tasks tend to take longer than expected and plan schedules accordingly.
Change failure rate (CFR) is one of the most important metrics used to measure software delivery performance, according to Google Cloud’s 2022 Accelerate State of DevOps Report. It calculates the percentage of application or system changes that lead to service issues and consequently require corrective actions, such as a rollback or hotfix.
You can calculate CFR by dividing the number of change failures by the number of changes made to deployed programs in a certain period and then converting that number to a percentage. In Google’s report, high performers had CFRs under 15%, while low performers had CFRs between 46 and 60%.
It’s ideal to keep CFR as low as possible. A high CFR calls for analysis and identification of root causes so teams can focus on improving processes.
Code churn illustrates the number of lines of code a developer adds, reworks, or deletes in a file within a particular time frame. Monitoring code churn helps managers pinpoint various issues, such as:
Generally, low code churn indicates an efficient developer, while high code churn can mean a team member has difficulty meeting deadlines and producing quality code. That said, code churn is typically higher at the start of a project as developers explore various solutions and decreases once they choose a path.
If you’re concerned about your team’s ability to hit deliverable deadlines, consider tracking its on-time delivery rate (OTDR) and benchmarking it against a target OTDR.
OTDR involves calculating the percentage of projects completed and delivered within a stakeholder-approved timespan. To calculate OTDR, divide the number of projects delivered on time by the total number of projects delivered within a specific time frame. Convert the result to a percentage.
Your findings can help you determine if your team is excelling at meeting deadlines or if you need to deep-dive processes and uncover reasons for an unsatisfactory OTDR.
Cyclomatic complexity is a quantitative code-quality metric. Essentially, it reflects program complexity by measuring the number of independent paths in its source code.
Low complexity typically reflects code structures that are easy to test and maintain. High complexity, by contrast, means there’s a higher risk of errors and bugs, and code maintenance may be problematic. Determining cyclomatic complexity involves:
By evaluating a program’s cyclomatic complexity, you can address potential errors before they impact deliverables.
You can rely on our expertise on software development KPIs because:
Facilitating progress requires more than collecting large volumes of data — your data must be analyzed and applied in a meaningful way to bring real results. At BTI, we understand how to turn raw data into usable information to catalyze process improvements with measurable benefits.
With our data mining services, we’ll examine your existing KPIs and analyze data from multiple sources to pinpoint inefficiencies or bottlenecks rapidly. Combining data mining with our experience in process improvement consulting, we’ll recommend actionable and strategic measures for optimizing your team’s workflows.
Contact us today to learn more about business process data mining.
