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OKR recommendations

ClarityLoop can generate OKR recommendations based on recent feedback, growth opportunities, and performance patterns as well as Career frameworks. These recommendations help individuals set meaningful objectives without starting from scratch, ensuring that goals align with real work and development areas.

How OKR recommendations work​

  1. Open the OKR page.

    • Go to OKRs from the sidebar.

  2. Select "Generate Recommendations".

    • Click the "Generate Recommendations" button.
    • The system will analyze available context, such as feedback insights, completed work, and growth opportunities.

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  1. Review and customize.

    • The AI will suggest draft objectives and corresponding key results.
    • Adjust, add, or remove items based on your specific needs.

  2. Finalize and save.

    • Once you're happy with the recommendations, click "Save".
    • The OKR is saved as a draft until you decide to publish it.

How the system generates recommendations​

The AI considers:

  • Recent feedback: Patterns like consistent strengths or recurring growth areas.
  • Growth opportunities: Insights from 1:1 discussions or historical performance.
  • Values demonstrated: Feedback linked to company values.
  • Career Frameworks: What it takes to reach the next level.
  • Ongoing work: Work items in tools like Jira, GitHub, and Confluence that show patterns of progress or blockers.

Example:

  • Feedback: "Alex has demonstrated strong cross-team communication."
  • Suggested objective: "Enhance cross-team collaboration for better delivery alignment."
  • Suggested key results:
    • "Host three cross-team syncs by end of Q3"
    • "Reduce communication gaps reported in retros by 20%."

Best practices​

  • Review suggestions carefully: Use recommendations as a starting point, not the final decision.
  • Focus on measurable results: Ensure key results are clear and trackable.
  • Link recommendations to growth: Connect objectives to feedback insights whenever possible.

FAQs​

Who can use the recommendation feature?
Anyone creating OKRs can access recommendations, but the insights available depend on the data linked to their work.

What if the recommendations aren’t relevant?
You can modify, delete, or manually create objectives if suggestions don’t match your needs.

Does the system learn over time?
Yes. As more feedback, insights, and OKRs are added, the recommendations become more tailored.

Next steps: