DevSecOps as a Service

Objectively Measure and Improve Developer Productivity

Dec 13, 2024

Developers are the most important asset in any company. It is critical that their bandwidth is managed efficiently and the business outcomes produced by them are maximized.

In order to achieve high developer productivity, it is important to –

Why is it important to measure Developer Productivity?

Measuring developer productivity gives an idea of where the bottlenecks are and what needs to be improved. It helps an organization to evaluate progress over time and improve the operational efficiency of the engineering team. We cannot improve something that is not measured.

But this is not easy to achieve, and the measurement of developer productivity and the rating of developer performance is still subjective in many organizations.

How to measure Developer Productivity

Productivity of a software developer can be measured in several ways as follows:

  • Time spent on tasks: This is a common metric for measuring developer productivity.
  • Number of bugs fixed: This is an important metric for measuring developer productivity as it directly measures the number of bugs fixed by a developer.
  • Feature implementation speed: This is a common metric for measuring developer productivity.
  • Lead time: This metric measures the time from the initial customer request to the delivery of the product.
  • Cycle time: This metric measures the time between when work starts and when it is delivered.
  • Deployment frequency: This metric measures how often development cycles are completed.
  • Throughput: This metric measures the number of work items completed by a team in a given length of time.
  • MTTR: This metric measures the ability to deal with problems such as production bugs and make effective changes.

At Kaiburr, we have worked with 40+ industry experts and engineering leaders to build an objective rating mechanism for developers. We use factors like developers with low pull request rate, most bugs, low quality code, vulnerable libraries, high cycle time. Some of these factors are explained in depth in the following section –

Pull Requests pending for Longer Duration:

This metric identifies developers requiring most time to close their pull requests. This would help to identify developers facing most bottlenecks and help identify resolutions so their code can be merged faster thereby reducing the overall cycle time and lead time.

Some common reasons for longer duration of Pull requests is –

  1. Developers assigned to the technology stack that they are not familiar with.
  2. Reviewers choked for bandwidth.
  3. Higher ratio of developers to reviewers.
  4. Pull requests with too many lines of modified code.

Stories with too many Pull Requests:

This metric identifies developers and stories requiring too many pull requests to complete.

Some potential reasons are –

  1. Requirements that are too complex.
  2. Stories that are too large.
  3. Legacy application requiring re-work.

Stories with Most Bugs:

This helps to identify developers and requirements leading to more bugs so the root cause can be identified to improve quality.

Some causes are –

  1. Ambiguity in requirements.
  2. Legacy code base.
  3. Developer not skilled in the tech stack.

Developers producing Poor Quality Code:

This helps to identify developers and commits causing most code quality issues so they can be addressed early.

Some reasons are –

  1. Developers not trained on coding best practices.
  2. Developers assigned to programming languages where they lack expertise or experience.
  3. Lack of code quality checks on every commit or PR.
  4. Lack of code reviews on every PR.

Developers introducing Most Vulnerabilities:

This helps to identify developers and commits causing most vulnerabilities so they can be addressed early.

Some reasons are –

  1. Developers not trained on application security.
  2. Lack of stricter guidelines on third party library use.

Pull Requests that are too large or with too many Issues:

This helps to identify pull requests that require –

  1. Too many comments.
  2. Too many commits.
  3. Too much duration to approve.
  4. Too many lines of code modified.

Pull Requests missing Story Id:

This is important to have proper traceability from requirements to releases. Many compliance regulations require only approved requirements to be released and this is critical to validate it.

Lead Time for Changes:

It is the time taken to get features to production from the time developers started working on them.

The discussed metrics help an organization to analyze current situation and identify the areas where improvement is required.

Reach us at contact@kaiburr.com to start measuring developer productivity objectively in your organization and help your teams achieve high performance.