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Aude Product Documentation
  • Welcome to Aude
    • Why Continuous Performance Management?
  • Goals
    • Introduction
    • Personal Development Goals
    • Performance Categories
      • Microsoft's Growth Mindset Principles
      • Google's Ten things we know to be true
      • Amazon's Leadership Principles
      • Engineering Excellence
    • Defining Effective Goals and Criteria
  • Managing Aude
    • User Management
      • Managing Users
      • User Roles
    • Team Management
      • Creating and Managing Teams
    • Managing Data Sources
      • Data Sources & Integration Setup
      • Issue Tracking
        • Jira
      • Source Control
        • Github
      • Knowledge Management
        • Confluence
      • Messaging
        • Slack
          • Managing the Aude for Slack App
  • Onboarding
    • Building Better Engineering Teams Together
    • Getting Started with Aude
      • Connecting Your Engineering Tools
      • Connecting GitHub
      • Connecting Slack
      • Connecting Jira and Confluence
      • Define Your Leadership Principles
      • Invite Users
      • Setting Up Your Teams
      • Calibrating Your Performance Insights
      • Connecting GitLab (Installation Guide)
  • Information Security
    • Aude Data Retention Policy
    • Aude Service Level Agreement
    • Aude Data Portability Policy
    • Aude Data Protection Policy
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On this page
  • Review and Refine Initial Performance Data
  • What to Review
  • Signal Accuracy
  • Activity Classification
  • Context Awareness
  • Red Flags to Watch For
  1. Onboarding
  2. Getting Started with Aude

Calibrating Your Performance Insights

Review and Refine Initial Performance Data

After collecting your recent data, Aude generates initial performance insights for your review. This calibration phase ensures our algorithms align with your organization's values and working patterns.

Your feedback during this phase helps tune Aude's algorithms to your organization's unique characteristics. We recommend reviewing insights weekly for the first month to ensure alignment.

What to Review

Signal Accuracy

  • Are key contributors being recognized?

  • Are quiet achievers properly visible?

  • Do the insights match your ground-truth knowledge of team dynamics?

Activity Classification

  • Are technical discussions properly identified?

  • Is collaborative behavior correctly recognized?

  • Are code review interactions appropriately categorized?

Context Awareness

  • Are insights accounting for different working styles?

  • Is cross-team collaboration being captured?

  • Are project-specific circumstances considered?

Red Flags to Watch For

  • High performers appearing average

  • Collaboration happening in unmeasured channels

  • Over-emphasis on quantity vs. quality

  • Missing important team interactions

  • Misclassified technical discussions

Aude will provide you with links to a survey to provide feedback in a structured manner.

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Last updated 7 months ago