Performance (Team)

Modified on Tue, 28 Jan at 10:50 PM

Target Audience

Team performance is a set of widgets designed for Scrum masters, Engineering managers & Engineering leads demonstrating a wide spectrum of metrics that collectively indicates the progress of code, progress of assigned issues, quality of code and efficiency of the team (building the codebase or working on requirements, etc).

PR age widget:

Overview:

This widget enables users to analyze the age of pull requests (PRs); By tracking PR age alongside related metrics (e.g., review time, cycle time), this widget offers a comprehensive view of the development process. It helps teams identify inefficiencies and implement targeted improvements.

Insights for users:

This widget provides actionable insights to streamline the PR lifecycle, enhance team collaboration, and accelerate feature delivery, teams can prioritize actions such as:

Prioritizing Reviews: Encourage reviewers to allocate time for timely feedback and approvals.
Enforcing SLAs for PRs: Implement service-level agreements to prevent PRs from stalling and ensure consistent progress.
Breaking Down Large PRs: Decide on splitting large, complex PRs into smaller, more manageable units to simplify reviews.
Promoting Early and Frequent Reviews: Foster a culture of early and continuous feedback to catch issues sooner and reduce the risk of delays.

Merged PRs:

Overview:

This widget provides insights into the team's pull request (PR) merging activity over time;

this trend should help the user validate the reasons for any unintended spikes, ensure PR review quality remains high, and ensure that the team is not overburdened by sudden spikes in workload.

Insights for users:

Merged PRs trend: Allows the user to analyze the merge trends e.g. the current example showcases a specific rising trend, indicating an accelerated pace of merging PRs.
Risk analysis with the merge trends:
1. Quality Assurance: A sudden surge in merges may lead to technical debt or insufficient testing. Ensuring code quality and testing coverage is critical.
2. Developer Burnout: If the team is rushing PRs due to pressure, a retrospective should be conducted to improve workload distribution.
3. Monitoring Performance: Post-release monitoring should be emphasized to catch regressions or performance issues caused by this influx.

Cycle time:

Overview:

This widget provides insights into how long it takes for issues to move from creation to completion. This enables the user to examine the root cause of the increased cycle time, ensure that it aligns with business goals, and optimize processes to prevent unnecessary delays while maintaining quality.

Insights for users:

Cycle time trend: Allows the user to analyze the cycle time trends e.g. the current example showcases a specific rising trend, indicating delays in completion of allocated work.
Risk analysis with cycle time trends:
1. Increased Workload: The team may be dealing with a larger volume of issues, leading to longer resolution times.
2. Complexity of Tasks: New tasks may be more complex than previous ones, requiring additional effort.
3. Process Bottlenecks: There could be delays in code review, QA, or deployment that are slowing down issue resolution.
4. Recent Staffing or Process Changes: A new workflow, team restructuring, or onboarding of new members could have impacted efficiency.

Code:

Overview:

This widget provides insights into technology/code flags associated with the PRs or code branches contributed by the team.

Insights for users:

Recurring code flags: The presence of recurring flags across multiple weeks suggests that these flags are an ongoing concern rather than isolated incidents.

Tracking Fixes and Improvements: If the number of flags related to a PRs remains constant, it may indicate slow progress in resolving these issues. If it fluctuates, it could suggest active debugging and resolution efforts.

Resource Allocation Needs: Persistent issues may indicate the need for dedicated efforts, such as assigning specific engineers, conducting PR audits, or optimizing existing processes.
Impact on Development Efficiency: Ongoing issues in the code base can slow down feature development and overall system stability. This may necessitate a shift in priorities to improve backend efficiency.

Potential Technical Debt: If the same flags appear frequently, they might be a result of accumulated technical debt (which may require refactoring e.g. database optimization, or infrastructure enhancements).

Effort:

Overview:

This widget provides insights into process flags associated with the issues assigned to members.

Insights for users:

Recurring Process Flags: The presence of recurring flags across multiple weeks suggests that these flags are an ongoing concern rather than isolated incidents.

Tracking Fixes and Improvements: If the number of flags related to a issues remains constant, it may indicate slow progress in resolving these issues.

Resource Allocation Needs: Persistent issues may indicate the need for dedicated efforts, such as assigning specific members to optimizing existing processes.
Impact on Process Efficiency: Ongoing issues from a process standpoint can slow down feature development and overall system stability. This may necessitate a shift in priorities to improve process efficiency.

Story points:

Overview:

This widget provides insights into the cumulative story points over time, likely representing the completion of work in an agile development cycle

Insights for users:

Growth in story points: A smooth curve indicates a consistent completion rate for story points, this could reflect stable team velocity and effective sprint planning (watch out for surges and drops).
Plateaus and declines: If there are no visible plateaus or declines in the curve, which suggests that work is progressing without significant delays or blockers.
Predicability of delivery: Users can use the trend to estimate future progress and predict project completion dates; this can help in planning releases, setting stakeholder expectations, and optimizing resource allocation.