We’ve made a few important updates to improve groups—including more robust configurations, easier management, and clearer representation of memberships. There is no change to any of your metrics as a result of these changes.

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New Membership History

Set a Join and/or Departure date on a group member to limit their data to a specific window of time. Members with a Departure date can be found under the Past tab under Members.

Use this feature to more accurately reflect teams where members are changing over time. You can also exclude data for managers that were previously ICs while retaining the data before they changed roles. To compare AI coding tools, use this feature to limit data for each developer in the group to after they started using the tool.

History of members joining or departing a group is automatically retained for teams synced from your Git provider (e.g. GitHub Teams). You will now see Join and Departure dates displayed for members of these synced groups. There is no change to your metrics as a result of this change, unless you choose to manually modify Join and Departure dates.

Faster, More Efficient Group Management

We’ve implemented a faster, more efficient user interface for adding members to groups. You can now add members to groups from the Git Users page.

You can add multiple membership records for a single user, spanning different periods of time. Use this feature to capture users that joined, left, and then rejoined a group. There is no change to bulk add or delete members from a group, aside from a small change to the terminology (“delete” vs. “remove”).

Clearer Representation of Group Membership

Group membership counts—as shown next to each group for context—have been updated to include Git users marked as excluded (e.g. managers) or bots. Previously, these users were not included in the count.

Contextual member counts are no longer displayed for groups in KPIs, Leading Indicators, and Comparisons to avoid confusion. Instead, a count of developers—anyone who created a pull request in the last 90 days—is now shown for metric drilldowns when it is relevant, such as for New Deliveries per Developer, Code Review Participation, and Open Pull Requests per Developer.

As a reminder, you can exclude pull requests created by a user (e.g. managers, product managers, designers, and other Git users outside of engineering). Reviews and approvals from these users will still count towards the progress of your pull requests to preserve accuracy (e.g. calculating Time to Review), but they will not factor into contributor-based metrics (e.g., Developer, Reviewer, and Contributor counts). You can also exclude all pull request activity for a specific user. Their reviews and other pull request activity are not factored into any metrics.

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These changes aim to provide more accurate data and a more intuitive interface for managing group memberships. If you have questions, please reach out to us at support@software.com.

We recently released Leading Indicators to help you identify your top constraint. Now, we're giving you a powerful way to take action on those insights. Introducing Objectives—a new feature designed to help you set, track, and achieve improvement goals directly against your biggest bottlenecks.

Once you've identified your top constraint, you can set a clear, measurable objective against the corresponding Leading Indicator. From there, you can conduct data-driven reviews of your progress with insights on key trends and performance, helping you optimize your efforts and unblock your team.

Objectives create a clear path from actionable inputs (Leading Indicators) to better outcomes (your KPIs). By setting a goal against a specific constraint, you can confidently drive measurable improvements throughout your entire development process.

Ready to set your first objective? Schedule time with us to review your top constraint and define a goal together, or feel free to reach out to us at support@software.com.

We recently identified and addressed a discrepancy in our Deployment Frequency calculation on the KPIs page. Over the last week (approximately May 20th - May 27th), the metric did not include deployments that exclusively contained pull requests authored by excluded users and bots. This behavior has been changed, providing an accurate count of deployments.

We’ve made several improvements to make it more clear how we track Git users and added support for excluding pull requests created by specific users. 

Git Users include anyone in your GitHub, GitLab, Bitbucket, or Azure DevOps organization. You can view a list of Git Users in your organization’s Settings under the Git Users tab.

Git Users include both Current and Past users contributing to repositories in your organization. Past Git Users are included in your historical data.

You can manually exclude pull requests created by managers, product managers, designers, and other Git users outside of engineering. Reviews and approvals from these users will still count towards the progress of your pull requests to preserve accuracy (e.g. calculating Time to Review), but they will not factor into contributor-based metrics (e.g., Developer, Reviewer, and Contributor counts).

Pull requests created by bots are automatically excluded from your data. Their reviews and other pull request activity are not factored into any metrics. If we are unable to automatically detect bots in your Git organization, you can manually exclude all pull request activity from those users.

Open source contributors are also automatically excluded from your data. An open source contributor is any user that is not an organization member and only contributes to public repositories.

If you have any questions, please reach out to us at support@software.com.

To ensure your lead time metrics reflect work that is actively in the review and merge pipeline, we've refined how draft pull requests are handled. All stages, including "Time to Approve," now consistently exclude drafts, giving you a cleaner signal on the efficiency of your active development efforts (note: there is no change to how “Time to Review” is calculated, which still starts when a pull request is opened or marked as ready for review).

These updates are designed to give you a truer, more actionable understanding of your team's development velocity. If you have any questions, please reach out to us at support@software.com.

We’ve released Leading Indicators—actionable data to help you identify and unblock your top constraint.

Software.com is divided into KPIs and Leading Indicators. Whereas KPIs are lagging metrics that focus on results and outcomes, leading indicators focus on inputs and actions, predicting future performance and trends.

Leading Indicators are designed to be actionable, helping you quickly pinpoint the biggest constraint in your development process. We highlight one high-impact area at a time, making it easy for you to take action without being buried in dashboards or noise.

Constraints vary by team and shift over time. Schedule time with us to review and identify your top constraint together, or feel free to reach out to us at support@software.com.

Our new KPIs report automates the most important metrics for development teams, such as New Deliveries, Rework (vs. New), Deployments, and Lead Time.

The KPIs report features several notable improvements vs. our previous reports:

• Improved terminology: we’ve updated the name of the “Features” metric to “New Deliveries” to avoid confusion with project management terminology. This change is purely naming-related and does not impact how the metric is calculated or displayed.
• Optimal values: based on data for over 700K developers and 10K companies, we’ve added optimal values for New Deliveries per Developer, Rework, and Lead Time.
• Deployments: if you’ve configured deployment methods for your repositories, you will see Deployments per Developer on your KPI report.
• Improved filtering controls: you can filter down to any group or any time period. You can also adjust the granularity to weekly, monthly, or quarterly or view as a table instead of graphs for easier reporting.

If you have any questions, feel free to reach out to us at support@software.com.

We’ve updated the name of the “Features” metric to “New Deliveries” to avoid confusion with project management terminology. This change is purely naming-related and does not impact how the metric is calculated or displayed.

We’re making an adjustment to improve the accuracy of our data — specifically, how we track the amount of code that is New, Churn, and Refactor. These updates provide a more accurate view of changes over time, especially for teams that ship new code iteratively.

You may see adjustments to your metrics and benchmarks—most notably, an increase in New Units per Developer (formally Features per Developer) and a higher percentage of pull requests categorized as New. Since these improvements apply to historical data as well, your data will be uniformly adjusted upward, maintaining all relative differences and trends.

By tracking a more detailed history of file line changes—including both their original position and where they appear after edits—we are now more precisely differentiating between newly written code and modifications to existing work. This added granularity gives a more refined view of how code evolves over time, ensuring that new work is accurately captured and modifications are correctly attributed.

You can learn more about how pull requests are categorized in our documentation. If you have any questions, feel free to reach out to us at support@software.com.

We’ve updated our algorithms to more precisely track your lead time and productivity metrics.

1. Lead Time Stages

   Lead Time is incrementally updated when a PR completes a stage, rather than waiting for the PR to complete all stages. For instance:

   • Previously, Time to Review was updated after a PR was merged.
   • Now, Time to Review is updated when a PR is reviewed.
   • This change ensures that your Lead Time metrics are more timely and reflect an ongoing historical trend.

2. Excluded Pull Requests

   Our algorithm automatically excludes pull requests that are not representative of development productivity, such as those authored by bots and backmerges from main. We also exclude pull requests that are part of your release process (e.g. promoting changes from a release branch to main). We’ve refined our algorithm to more precisely detect these pull requests, such as by detecting re-used branches. Depending on your development process, you may notice a slight increase in your pull request metrics.

If you have any questions about how our algorithms work, feel free to reach out to us at support@software.com.