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 released Time-Based Comparisons, which let you compare productivity before/after a key event. Examples of major events that you can measure with this feature include acquisitions, layoffs, leadership changes, and adopting new tools.

To get started, go to the Comparisons tab and click Create Comparison. When setting up the comparison, select Before vs. after an event, which will allow you to define a new key event and select the groups that you want to compare.

If you have any questions or would like help setting up a time-based comparison, feel free to reach out to us at support@software.com.

Our new Jira integration provides you with a more complete picture of lead time, all the way from issue in progress to changes deployed. When you connect Jira, we automatically link your team’s pull requests to issues, giving you visibility into time spent on changes even before the first commit.

✨  What’s new?

• Measure lead time from issue in progress to deploy, for end-to-end visibility into team efficiency.
• Get a more complete view of development time, the time between starting an issue to opening a pull request.
• No configuration required. We automatically link Jira issues and pull requests if a pull request name contains a project prefix and number associated with a Jira issue (e.g. JRA-123).

⚡ Get started with Jira

You can connect Jira from the Atlassian marketplace in just a few minutes, or learn more in our documentation. You will be able to choose your workspace and review permissions before installing the app.

We’ve redesigned our Slack app from the ground up to elevate your team’s collaboration and productivity. With new features — like reminders for blocked pull requests and previews of upcoming deployments — you can keep your team on track and stay on top of work that’s in-flight.

It’s also now easier than ever to try out our Slack integration. Starting today, you can find our app in the official Slack marketplace.

✨ What’s new

• Deployment previews: When you’re ready to ship, send a preview of your upcoming deployments to team members in Slack.
• Digests: Share updates with your team and see how your team is tracking against your working agreements.
• Reminders: Get automated reminders when pull requests waiting on review, approval, merge, and deployment do not meet your working agreements.
• Async reviews: Start group code reviews and create new Slack channels for your pull requests to collect and share feedback during the code review process.
• Standup bot: Automate daily standup by generating a message that recaps your recently closed and currently open pull requests.

⚡ Get started with Slack

You can learn more about our app for Slack in the marketplace.

We’re starting off the year with new insights into lead time to help you understand how long it takes you to make product changes. With the lead time dashboard, you can answer questions like:

• How are we performing relative to before?
• Where are there bottlenecks in our development process?
• Which changes took us the longest to make?
• Is this increase in our lead time caused by longer review and deploy times or an increase in our work load?

✨  What’s new?

• Breakdowns of lead time by stage, team, repository, and label to help you identify bottlenecks.
• Comparisons to previous period to see how your team is trending.
• Related metrics, such as review turnaround time and time to deploy, to see what’s impacting lead time.
• Insight into which changes took the longest to make, organized by pull request.

👋  Get in touch

We’d love to hear your feedback on our new lead time insights. Otherwise, stay tuned — we have some exciting updates in the weeks ahead.

Our latest update helps you stay on top of work that’s ready to be deployed and prevent large backlogs of changes. With new deployment metrics and more powerful Slack notifications, you can make your team’s deployments faster, easier, and more frequent.

✨  What’s new?

• Keep a pulse on the overall health of your deployment process with new summary metrics. Get insight into how long it takes to deploy changes, the number of recent deployments, and the success rate of those deployments.
• Track upcoming deployments with a summary of pull requests ready to ship, organized by repository and sorted by the maximum age of changes waiting to be deployed.
• Notify your team team of changes that need to be deployed with deployment previews in Slack.
• Prevent changes from becoming stale by setting up notifications when changes are not deployed within some number of days of being merged.
• View recent deployments to keep track of previously released changes.

🔷  Get started with previews in Slack

When you send a preview of a deployment to Slack, we’ll share a summary of the pull requests ready to ship and their authors. Head over to your Upcoming Deployments and select View to open an information panel, where you can then select the channel you want to notify.

👋  Get in touch

Need help connecting Slack or configuring deployments? You can find some time to chat with us and we’ll walk you through how you can use the Ready to Deploy feature to improve your team’s velocity.

We’ve listened to your feedback over the last several months. We’re updating our pricing to be simpler and more flexible. Our Pro plan now starts at $99/mo for organizations of up to 20 developers.

When you upgrade, you'll unlock instant access to your team's lead time trend over the last three months. We've also added features to supercharge your team, like a Slack weekly digest and notifications to remind you about slipping work. 

Additional integrations, such as CI/CD tools, start at $33/mo and can be added to your plan for more advanced insights into your deployments. You can learn more about our updated plans on our website.

✨  Why the change?

• It’s simpler. Instead of charging per developer, we charge a base platform fee based on the size of your engineering organization.
• It’s predictable. With a flat monthly platform fee, you have room to grow your team without worrying about any surprise bills from us.
• Pay only for what you need. Optional add-ons, like Deployment Insights, help you get more out of our platform when you connect more integrations.

You can also schedule time with us if you’d like to learn more about how Software can help your team with faster code reviews and more frequent deployments.

Chances are you've felt pain around deploying changes to production. Deployments cause stress and anxiety for everyone involved, especially when they happen infrequently. 

Today, we’re releasing Ready to Deploy — a feature that provides visibility into apps with a backlog of changes waiting to be deployed. We built this feature to help ease deployment pain for engineering teams. You can see all of your team’s merged pull requests, organized by repository and sorted by how long they’ve been awaiting deployment.

✨  What’s new?

• Undeployed PRs: see the number of pull requests ready to deploy for your team.
• Merge to deploy: see which repositories have the longest average time between merging and deploying pull requests.
• Time to deploy goal: set a goal for time to deploy to prevent changes from piling up right before pushing to production.
• Visibility from open to deploy: track work in progress all the way from code review (using the Open Pull Requests view) to deployment (using the Ready to Deploy view).
• Advanced filters: filters allow you to change the data range and choose whether to include or exclude pull requests created by bots (e.g. Dependabot).

💭 How does it work?

1. Go to our Ready to Deploy feature to see your data. It works out-of-the-box with our existing GitHub integration if you’re using GitHub Actions, deployments, or releases.
2. We automatically detect how you deploy each repository, but you can also manually assign specific workflow runs, check runs, deployments, and releases as production deployments for each repository.

👋   Latest from the community

• Omar Bahareth, CTO at Ejaro, wrote Engineering Management: An Overview, a deep dive into the most important responsibilities of engineering managers.

Our team aims to make deployments fast and frequent, minimizing the risk of bugs each time we push new changes live. We built the Deploy feature to help teams measure performance and improve stability of their mainline systems. In addition to key metrics like deployment frequency, you can also see which repositories take the longest to deploy or fail to deploy most often.

✨  What’s new?

• Time from open to deploy: average time from opening to deploying a pull request
• Deployment frequency: count of production deployments per developer per day
• Time between deployments: average time between successful deployments
• Deployment run time: average time elapsed per deployment
• Slowest deployments: repositories that take the longest to deploy
• Deployment success rate: count of successful production deployments vs. the total over time
• Least successful deployments: repositories that fail to deploy most frequently
• Deployment batch size: average number of code changes per deployment

💭   How does it work?

1. Go to our Deploys feature to see your data. It works out-of-the-box with our existing GitHub integration if you’re using GitHub Actions, deployments, or releases.
2. We automatically detect how you deploy each repository, but you can also manually assign specific workflow runs, check runs, deployments, and releases as production deployments for each repository.

👋   Latest from our team

• Brett wrote a guest post for InsideBigData: Why You Should Add DevOps Metrics to Your Data Fabric.