360 feedback
A short, structured way to gather feedback from colleagues: five open questions, optional quality ratings, and a coach to read it with you.
What a round looks like
You pick a handful of colleagues. They each answer five questions about how you collaborate, optionally rate you on a set of qualities, and have ten working days to reply. Once responses arrive, an AI summary pulls out the themes, and you read everything together with your coach.
The frame is you and how you collaborate, not your performance in a single role. Two of the five questions touch on roles, but as evidence rather than verdict. For role-specific signal, see Role Ratings .
The full cycle: Request → Collect → Review → Reflect → Share (optional). The five green steps below walk through it. The other sections give background.
Your coach
Every round has a coach: a colleague paired with you ahead of time who reads your feedback alongside you and helps make sense of it.
Setup. An admin pairs people in Settings → 360 Feedback → Coaches. Each person has one default coach, auto-attached when you start a round. You can swap the coach on any round; that also updates your default. More on pairing and reassigning: Coaching pairs .
The coach can: read every response, read the AI summary with you, keep private coach notes visible only to them, and click "Prepare session" to pre-fill a coaching agenda.
The coach cannot: submit their own evaluation, or read responses before they arrive.
Optional: quality ratings
Below the open questions, the form has a short list of qualities (e.g. Ownership, Prioritization, Collaboration), each rated on a five-point frequency scale from Rarely to Almost always, plus Not sure. The recipient sees the aggregate as a radar chart and a compact table.
Quality ratings complement the prose: a fast contribution path for colleagues who freeze at a blank text box, and a way to track patterns across rounds. Workspaces can shape their own list or turn the section off. Full mechanics in Qualities in 360 feedback .
Step 1: Request feedback
Pick colleagues: choose 3 to 5 people you have worked closely with. Your team leads are auto-added and can't be removed.
Optional: add one custom question tied to your development goals, e.g. "How can I improve my communication in team meetings?"
Set a due date. Default: ten working days.
Click Request Feedback .
What happens next: each colleague gets an Asana task plus an email with a private link to the form (no Moral Fabric account needed). Your coach gets a heads-up task, and you get a prep nudge.
The workspace admin needs to configure a 360 Asana project beforehand. If sending fails, that's why.
Step 2: Colleagues fill out the form
The form takes 5 to 10 minutes and asks the same five questions in every round, plus your custom question if you added one:
What do you like most in your collaboration? (required)
What could improve in your collaboration? (required)
In which role(s) do you see them most engaged, and why? (required)
In which role(s) do you think they could be more engaged, and why? (required)
Optional. Any other thoughts on their performance? When are they at their best? When do they struggle? What would help them shine?
For questions 3 and 4, the form shows a picker with your actual roles, which makes the answers specific and actionable. Writing tips for responders: see "For feedbackers" below.
A per-workspace "values" question is on the way, and the default questions will become editable per workspace. Until then, use the custom question slot to ask in your own words.
Step 3: Review your feedback
Open your request under app.moralfabric.org/feedback/requests to see the status (responded vs. pending) and each individual response as it arrives.
Once at least one response is in, click Generate Summary. The AI analyzes all responses and produces:
- Major themes across responses
- Strengths multiple peers agree on
- Areas for growth
- Suggested coaching questions for the next session
- Self-vs-peer alignment, if you wrote reflections (see Step 4)
Regenerate the summary as more responses come in. It draws on evidence-based 360° practice (DDI's multi-rater research, HBR on self-managing teams, the London Deanery coaching guides); the info icon next to "AI Summary" in the app shows the full attribution. Treat it as a draft to talk through, not a verdict.
Step 4: Reflect with your coach
After the round closes, meet with your coach to:
Read the responses and AI summary together.
Discuss what resonates and what surprises you.
Identify 2 to 3 action items for the next quarter.
Record your takeaways in My Reflections in the app (visible to you and your coach).
If you fill in reflections, the AI summary runs a self-vs-peer alignment pass: confirming strengths, surfacing blind spots, and pointing out hidden strengths the team sees that you don't.
Scheduling tip: when you request feedback, the app offers to create a calendar event with your coach for the day after the deadline.
Reflections are coming earlier in the flow. For now, jot your expectations in your own notes app before responses arrive, and paste them in once the section opens.
Step 5: Share your feedback (optional)
By default only you and your coach can see your feedback. From the feedback view you can:
- Share with others (e.g. your team lead) via the Share Feedback button. A shared viewer sees the responses and summary, but no coach tools.
- View who has access at any time.
- Change your coach if needed.
Who sees what
You (recipient)
All responses, AI summary, your reflections
Your coach
Same as you, plus private coach notes
A shared viewer you added
All responses + AI summary; no coach tools
Anyone else
Nothing
Workspace admins can see metadata (who asked whom, when) for safeguarding. They can't read response content. Full access model: Who can see your data .
When it pays off
- Before a 1:1 or a season change. It pulls a real conversation onto the table.
- After a stretch project. Specific moments are still fresh; answers carry weight.
- When something feels off and you can't name it. Open questions surface what you didn't expect to hear.
Run a round when you're genuinely unsure. Signal-to-noise is much higher than when you already know the answer.
For feedbackers: giving good feedback
-
Not sure what to say? Question 5 is optional. Even a few sentences on the required questions is valuable. -
Can't give useful feedback? Skip it: open the form, click Skip this feedback , and pick a reason. No need to fill anything in. -
Consider meeting in person. If you have substantial feedback, a 15 to 30 minute chat before the reflection session beats a wall of text. -
Be specific. Instead of "you're a good communicator", try "I appreciated how you summarized the project status clearly in Monday's meeting." -
Be balanced. Both appreciation and suggestions for improvement are valuable.
For coaches: facilitating a good reflection
Listen 80%, talk 20%. Hold space, don't fill it. When you speak, ask questions.
Ask, don't tell. "What do you make of that?" beats "Here's what I think."
Start with their reaction. Ask what surprised or resonated before diving into details.
Let silence do the work. Pause after a question; thinking takes time.
Don't add your own feedback. This session processes peer input. Save your observations for another time.
Follow the energy. If something clearly landed, stay there: "Can you say more about that?"
Look for patterns together. One comment is noise; three comments is a signal.
End with action. "What's one thing you'll do differently?" No action items, no change.
Acknowledge hard feedback. If something stung, name it: "That sounds difficult to hear." Don't rush past it.
Be a mirror, not a judge. Reflect back what you hear; don't evaluate whether feedback is "right."
Querying feedback from AI tools
If your workspace is connected via MCP , you can ask things like "What themes show up across the last three feedback rounds I ran?" or "Cross-reference the qualities people rated me on against the projects I led this year." The AI sees what you'd see.