9 Software Development KPIs that high-performing teams track

Why do Software Development KPIs matter?

The most important thing to have for a successful and efficient team in any field is “direction”. And there is no absolute “right” or “wrong” in it. It's all a relative and contextual concept. And Software Development KPIs (Key Performance Indicators) act as that “north star” which keeps the team heading in the right direction.

Software development KPIs are often confused with metrics. Metrics are numbers representing a fact whereas KPIs are things that matter to an organization. Choosing KPIs without evaluating the effects it brings to your team will do more harm than good. As an example “lines of code (LOCs)” could be a metric but should never be a “KPI” for a software development team.

Measuring the right engineering KPIs helps you ensure you have a high-performing and efficient engineering team which is a real competitive advantage. The definition of “high-performing” and “efficient” varies based on the nature of the business and a lot of other factors. Figuring out these KPIs helps you separate the important from the noise. In this blog, we go over how should you select a KPI for your team and also list the top 9 Software Development KPIs that have worked for other engineering teams.

How to and how not to select a KPI?

1. Always keep team efficiency in consideration and not developer productivity.
Software development is inherently a team concept and selecting KPIs to track at an individual level, will never work in the longer run.

2. KPIs should never be quantitative.
It should focus more on the quality dimensions of your work. Tracking the “count of commits” cannot be a KPI, but “customer satisfaction”, an indicator of the quality of the team’s output is a great candidate

3. First identify important processes then select KPIs.
KPIs are performance indicators of what matters to your engineering teams. Identifying processes that matter to you first and then figuring out the KPIs helps in achieving this. Some engineering processes to consider are planning, execution, code quality, deployment cycles, testing, team health, and user satisfaction.

4. Never “copy-paste” KPIs not even from this blog.
Keeping in mind the nature, culture, and where your organization is headed is very important for selecting the right KPIs. The best way is to learn from what others do and don’t but never replicate them just because it’s working for them.

5. Don’t track KPIs your team doesn’t believe in.
In deciding what software development KPIs are important for your team, you are also figuring out your priorities and telling the team this is important for us. Having wrong KPIs is worse than having no KPIs at all.

6. Start small.
You can’t start by saying these 25 engineering KPIs are important for us. Essentially it's deeming everything important, which cannot be true. It’s okay to take time in figuring out what’s important but not doing it will dilute the value of these KPIs.

9 effective Software Development KPIs

These are some KPIs we have seen work beautifully for software development teams. (order doesn’t indicate importance or its effectiveness)

1. Induction time in a team
The time it takes for a new team member to start making meaningful contributions to the team’s deliveries. This helps in understanding how big is the learning curve for this team, and also indicates how efficient the team is in educating new members about the architecture, tech stack, and development practices of the team. A lower number indicates a smaller learning curve and that new members can start contributing quickly impacting the overall productivity of the team and also the satisfaction of the new team member.

2. Testing effectiveness
This can be measured using a combination of several metrics like the ratio of bugs found in non-production vs production environments, the percent of user scenarios tested in non-prod environments, and testing branch coverage. The primary intention of this KPI should be to ensure that the measures used by the team to test changes before going live are effective and that the overhead of production defects is not slowing the team down.

3. Effective development
It doesn’t matter how many code changes were made, what matters is the effectiveness of the code. Effectiveness is when minimal rework is needed and the team doesn’t keep on adding code debts while adding new changes. Rework sometimes is also an indication of unclear requirements or frequent ad-hoc enhancements. Another good measure to track the effectiveness of your code is what percent of code developed is making an impact on your customers. Tracking this as a KPI helps in setting the notion that effective work is valued over more work.

4. Customer satisfaction
All work done by the engineering team finally delivers new features or better experiences to the end-user. Measuring end-user satisfaction becomes a good measure to indicate whether your engineering team is working with the right mindset. A few ways to track this could be by measuring the frequency of usage of features or can also come from a feedback survey after a new feature launch. Depending on the type of your product and the customer support your org offers, indicators like the frequency of customer-reported bugs and the speed with which customer requests are delivered also play a major role in measuring satisfaction. You can track the velocity of feature requests by looking at their cycle time (from grooming to production deployment). Another very effective indicator is NPS (Net Promoter Score) which is a score of how likely an end-user will recommend your product to someone else. This is tracked using customer surveys and feedback forms.

5. Cycle time
A software development KPI that is widely used and correctly so as it is a clear indicator of speed of delivery. Cycle time primarily helps you understand the agility of your teams and what are the areas where most of your time is spent. For example, if the time it takes to test in a staging environment is more than the development item it is a hint for you to automate/optimize your testing frameworks.

The best way to track the cycle time of any task is right from its inception (planned) to its realization (production deployment). An example of cycle time that paints a complete picture of your development processes could look like this

True engineering cycle time from planned to production deployment
Tracking cycle time as a KPI helps you understand the efficiency of different processes. Sometimes cycle time of different stages may not be accurate to the minute but a comparative view and the overall split across different processes helps you optimize the right areas.

6. Production Stability and Observability
No system is perfect and bugs in software development are inevitable. You need to make peace with the fact that perfecting the development process is not going to help. Having the right observability mechanisms in place to minimize the impact is the best way to tackle this. Focussing on both the speed and stability of your processes is key (heart of DORA metrics ideology). Some software development KPIs that help you understand the stability are:

1. CFR - Change Failure Rate - percent of deployments that cause a production defect, helps you in understanding how frequently your team occurs an overhead of fixing defects.
2. MTTD - Mean Time To Detect - the average time it takes for a defect to be identified in production - this represents the effectiveness of your monitoring and observability mechanisms.
3. MTTR - Mean Time to Recover - mean time it takes for you to fix production defects once you have detected them - communicates the speed with which your team can figure out and fix an issue to minimize impact to end users.

7. Team health and satisfaction
Richard Branson says “take care of your employees and they will take care of your customers”. With everyone still recovering from post-pandemic burnout, this is more important than ever. Ensuring the team is not burning itself out and is happy with the type of work they are doing is the fundamental pillar of having an effective and productive team. Some indicators that help in keeping a track of this are

1. Everyone wants to work on developing new features and the latest technologies. If your team constantly works on solving bugs and maintenance of existing systems it is bound to cause dissatisfaction among the team members.
2. Development experience - Is it too difficult to even test one single line of change to your system? Equipping developers with tools and flexibility for quickly testing changes or running small POCs is essential for having a happier team.
3. Time spent in meetings vs actual work - Often software development teams are faced with “meeting fatigue” where they spend more time in meetings than productively working. Which contributes to burnout and context switches that often could be avoided. Understanding how many meetings teams attend or the percentage of the time they spend in meetings could help you understand the team’s sentiment towards meetings.

8. Documentation and Knowledge sharing
For any software development team to effectively work, knowledge has to be shared widely across the team. It could be in the form of code documentation or component specs, or design documents. In the current scenario, the question is not “if” a team member is going to switch to a different team or org, it’s more a question of “when” - 0% attrition is not possible period. The best way to deal with this is by reducing knowledge silos within your team so that even if a team member decides to leave the “show can go on”. Engineering KPIs covering this aspect include

1. Percent of your code base that is documented. How frequently are component diagrams or API specs updated could be a few indicators to denote code/design documentation practices.
2. The number of meetings it takes for a new joinee to understand the system. A high number of meetings would mean there doesn’t exist enough documentation as self-serve for the new team member.
3. Percentage of your codebase that is known to only one team member. (higher percent = more knowledge silos within the team).

9. Task planning and predictability
Which tasks need to be done, by when, and who’s going to work on them - are key questions that need to be answered in planning a project. All team members may not necessarily be involved in making this decision, however, the team needs to work predictably for the organization's growth. These are a few KPIs that work:

1. Work breakdown structure - Project management is completely based on how well you break down a task into more manageable tasks - this helps in establishing clarity in what needs to be done and better estimating the time it may take.
2. Predictability - This indicates what percent of the committed work is completed in a time frame. There are multiple things like ad-hoc requests or production bugs that could affect predictability.
3. WIP count - Working on multiple things together is optimal, but working on too many things together is never desirable. You can understand the sanity of your planning process by looking at this for a development team.

4 dangerous Software Engineering KPIs to avoid

You should try to avoid these 4 indicators at all costs. They tend to do more harm than good for your development team.

1. Active coding days
This metric in no way represents the quality of the work done by an individual. Everyone’s work pattern could be different, some could take 3 days to understand a requirement and logically map out what exactly needs to be done, but then complete the actual task in a day. Assuming every team member should code daily is a baseless assumption. There are many other things a team does like reviewing, designing, testing, releases, planning, grooming, and helping junior team members amongst others. Tracking coding days as a KPI renders all these other functions useless. And not the right culture you want to imbibe in a high-performing team.

2. Lines of code
This age-old metric is without doubt the worst way to track the productivity/output of an engineering team. Tracking a KPI like LOC indicates that for a task if a team takes 100 lines of smart code is worse than 1000 lines of bad code. No software development team should ever focus on LOCs as a KPI.

3. Sprint velocity
Another very commonly misused metric is velocity. Velocity can be a good indicator of how many planned tasks were completed and also assist in future sprint planning. But never an indicator of a team’s productivity or effectiveness. Velocity becomes a dangerous KPI when it is used to push developers and compare teams. Two teams even in the same organization can have very different estimating standards and tracking that as a KPI of a team’s productivity opens the gate for gaming the system. Tracking velocity as a KPI often results in the team working for a better KPI rather than better work.

4. Stacking developers against each other
It's very common to confuse software development KPIs with metrics to track individuals under the name of “developer productivity”. Engineering KPIs should represent the overall state of a team or a project, never individuals. Above all, comparing a developer with another is the worst thing one can do to improve team productivity. Your team has to contribute towards better engineering productivity using these KPIs and not feel threatened by them.

Going through the process to select the right software development KPIs that matter to your team might be slightly time-consuming but with the right mindset, this is extremely helpful in the long run. Right performance indicators would act like guiding beacons for your engineering team in turbulent times and help you ensure you are headed in the right direction.

AnalyticsVerse helps software engineering teams transform their development processes by tracking the right software engineering KPIs.