Introduction
CORN — Context, Observation, Result, Next Steps — is a structured, behavioral feedback model. It helps you anchor feedback in a specific moment, describe objective behavior, make the impact clear, and finish with concrete actions. CORN is closely related to SBI (Situation, Behavior, Impact), COIN (Context, Observation, Impact, Next Steps), and CORE (Context, Observation, Result, Expectations). All share the same core principle: focus on observable behavior and the outcomes it creates, not on personal judgments.
Origins
Modern behavioral feedback models grew out of leadership development and coaching. SBI from the Center for Creative Leadership established the foundation: describe the specific situation, the observable behavior, and the impact. HR and coaching circles later emphasized forward planning through COIN, adding explicit next steps. Radical Candor popularized CORE as a preparation lens for hard conversations: state the context, observation, result, and the expectation or next step.
CORN is a practical synthesis of these ideas. It keeps SBI’s discipline around describing a concrete moment and camera-true behavior, and it borrows the forward-looking close from COIN/CORE so the conversation ends with a clear action. Labels vary across models, but the intent is consistent: stay behavior- and outcome-focused and make the next move explicit.
SBI
Same backbone as CORN: Situation = Context, Behavior = Observation, Impact = Result. If you use SBI, add a short Next Step to turn feedback into a concrete plan.
COIN/CORE
COIN/CORE and CORN all aim for a clear next move. CORN keeps Result to focus on impact, then closes with explicit, time‑bound Next Steps. Pick the acronym you prefer; the quality of the conversation matters more than labels. With Radical Candor, prepare CORN and quickly check alignment before proposing solutions.
Why It Works
CORN works because it reduces ambiguity and focuses attention on what people can change. Anchoring feedback in a specific moment narrows the scope and helps both parties talk about the same event, which lowers defensiveness. Describing behavior in camera-true terms keeps the conversation objective and avoids debating intent or personality.
Explaining the result makes consequences tangible so the “why” is clear: it affected a customer’s experience, a timeline, or team trust. Ending with next steps converts the feedback into a shared plan, which increases follow-through. The structure is short and repeatable, so it fits naturally into 1:1s, reviews, incident retros, and everyday coaching.
How to Use CORN
Steps
Context grounds the conversation in a single moment. Name the meeting, artifact, or date so both of you are talking about the same event. Avoid vague ranges like “recently”; specificity keeps the scope tight.
- Example: “Sprint planning on March 12…”
Observation describes what would be visible or audible to a recorder. Quote the words, point to the action, or reference the exact artifact. Leave out labels, mind-reading, and speculation about intent. Precision here prevents unproductive debates.
- Example: “…story ABC-142 was estimated without backend input.”
Result explains the effect. Tie it to a customer outcome, a timeline, a quality metric, or team dynamics. When possible, quantify it (e.g., “95th percentile latency increased from 1.2s to 1.8s,” “we missed the date by 3 days”). The goal is to make the “why it matters” unmistakable.
- Example: “…we under-scoped database work and missed the delivery date by 3 days.”
Next Steps turn the insight into action. Co-create a small, time-bound change with a clear owner, or ask a question to invite their solution. Good next steps are specific and testable: “By Friday, publish the checklist,” “Before the next demo, add backend review to estimation,” or “Let’s walk the logs together next time.”
- Example: “Add backend review to the estimation checklist; I’ll tag the right owners before sizing.”
Examples
Praise
- Context: “On Tuesday’s client call…”
- Observation: “…you paused and summarized the client’s concern before proposing options.”
- Result: “…they felt heard, which kept the conversation constructive and led to a clear decision.”
- Next Steps: “Please keep applying that ‘summarize first’ step in complex calls; consider sharing the technique in our next enablement session.”
Correction
- Context: “During yesterday’s incident review…”
- Observation: “…you dismissed QA’s findings as ‘edge cases’ without examining the logs.”
- Result: “…the team lost valuable time and QA felt discouraged from raising valid signals.”
- Next Steps: “Next time, let’s inspect the logs together before categorizing severity; I’ll schedule a short walkthrough of our triage flow.”
Precision
- Context: “Sprint planning on March 12…”
- Observation: “…story ABC-142 was estimated without backend input.”
- Result: “…we under-scoped database work and missed the delivery date by 3 days.”
- Next Steps: “Add backend review to the estimation checklist; I’ll tag the right owners before sizing.”
Upward feedback
- Context: “In last Thursday’s roadmap review…”
- Observation: “…we moved three Q1 items to Q2 without checking dependencies.”
- Result: “…the data team flagged two risks late, and we’ll need a replan.”
- Next Steps: “Can we add a dependency check before approving moves? I can draft a checklist for next week’s review.”
Recognition (metric)
- Context: “On the March 5 release…”
- Observation: “…you introduced lazy-loading on the gallery page.”
- Result: “…95th percentile load time dropped from 2.3s to 1.6s, and support tickets decreased.”
- Next Steps: “Please document the approach and share it in the frontend sync; we can apply it to the profile page next.”
Pitfalls
“Just praise” or “just criticism” without specifics
Generic statements like “Nice work!” or “Do better next time” don’t teach anything. Make feedback useful by tying it to a concrete moment and behavior, then state the effect. If you can quantify the result, do so; specificity turns praise into a model and criticism into a clear change.
- Bad: “Nice work!”
- Good: “On the March 5 release… lazy-loading… 95th percentile load time dropped.”
Vague context
Phrases like “last week” or “recently” invite confusion and debate. Name the exact meeting, date, artifact, or message so both parties are looking at the same event. Precision in context sets the stage for precise observations.
- Vague: “last week”
- Specific: “In last Thursday’s roadmap review…”
Judging intent or personality
Labels such as “You don’t care” or “You’re careless” trigger defensiveness and derail the conversation. Stick to observable behavior and its impact. If intent is relevant, ask about it—don’t assume. This mirrors CCL’s guidance on exploring the gap between intent and impact.
- Don’t: “You don’t care.”
- Do: “You skipped the dependency check in Friday’s handoff…”
Overloaded next steps
Too many actions dilute ownership and accountability. Agree on one or two specific, time-bound changes and set a follow-up. Small steps compound, and they’re more likely to stick.
- Bad: “Fix everything ASAP.”
- Good: “By Friday, publish the checklist.”
Mixed messages (the “feedback sandwich”)
Combining praise and criticism in one breath blurs the message and can erode trust. CORN favors kindness and clarity over sugar-coating: deliver one message per conversation—either reinforcement or correction—and if both are needed, separate them into distinct CORN cycles. Before proposing solutions, check for alignment on context, observation, and result; agreement on the problem precedes effective action.
- Bad: “Great job, but…”
- Good: “Deliver one clear message per CORN cycle.”
Precision
Precision comes from grounding each element in something verifiable. Tie results to metrics or concrete consequences so the impact is unmistakable. Keep observations camera-true and free of labels; quote or point to the artifact rather than interpreting it. Make next steps small, time-boxed, and owned; then close with a question to invite perspective and co-create solutions. Finally, follow up so insights become learning, not just a momentary conversation. Make context unambiguous by naming the exact artifact—doc, PR, email, meeting, or date—so there’s no confusion about the moment. Quote or paraphrase precisely without editorializing. Quantify impact whenever possible to tie results to metrics or concrete consequences, and limit the conversation to one behavior at a time; schedule follow-ups for additional topics. Time-box next steps with clear owners and deadlines, and invite perspective with one good question to keep the tone collaborative. Precision improves with practice. Build a short habit of drafting three CORN notes—one reinforcement, one correction, and one learning—and deliver at least one. Before you give feedback, run a quick checklist: context named, observation camera-true, result concrete, next steps specific and time-bound. Afterward, debrief briefly to note what was clear, what was verbose, and one simplification for next time. Over time, maintain a healthy ratio of reinforcement to correction while keeping each message single-purpose.
When to Use
CORN fits everyday coaching and formal feedback alike. Use it in 1:1s, performance reviews, sprint ceremonies, incident reviews, and cross-functional collaboration. It is also effective for upward feedback when kept descriptive and impact-focused.
Conclusion
CORN is simple, disciplined, and adaptable. Choose a specific moment, describe camera-true behavior, make the impact tangible, and agree on a small next step. Keep reinforcement and correction separate to preserve clarity. Use artifacts and metrics to increase precision, and invite perspective to build shared understanding. Practiced consistently, CORN turns feedback from a stressful event into a regular, effective part of how your team learns and performs. Feedback lands best when it is anchored in a specific moment, describes camera-true behavior, makes the impact explicit, and ends with a small, owned action. Separate reinforcement from correction to keep each message clear. Use metrics and artifacts to increase precision, and invite perspective to build shared understanding. Practice short routines to make clarity habitual; consistency matters more than clever phrasing.