Use these OKR Closing and Outcome templates at the end of your OKR cycle. Closing an OKR cycle is a great way to cool down and reflect on the work you and the team did in the last quarter (or year). Closing a goal or KR is a two-step process.
Step 1: Choose a goal outcome
A goal or key result can have the following outcomes:
- Goal outcome: Completed
- Goal outcome: Partial
- Goal outcome: Missed
- Goal outcome: Dropped
Step 2: Add a closing note
The closing note is a brief summary of a reflection of how the team did in the last quarter. below are some templates to help you get started
KR OR Goal Ourcome: Completed
Closing Summary
What went well
What can be improved
Action items
How to score stretch and committed OKRs
When closing goals and OKRs at the end of the quarter. it is important to consider how committed vs stretch goals should be rated.
| % Complete of a Stretch Goal | Outcome |
|---|---|
| > 70% | Completed |
| 40%-70% | Partial |
| < 40% | Missed |
| % Complete of a Committed Goal | Outcome |
|---|---|
| 100% | Completed |
| 60%-99% | Partial |
| < 60% | Missed |
Before you start
What are OKRs?
OKR Meaning
History of OKRs
Benefits of OKRs
Are OKRs right for me?
OKR Mistakes to Avoid
A Brief Guide to OKRs
Aligning with OKRs
Strategic Planning
OKRs in Strategy
SMART, MBO, BHAG
Role of an OKR Champion
Take the OKR Quiz
The North Guide to OKRs
Getting started with OKRs
How North works
A typical OKR Cycle
Planning your OKRs
Weekly OKR Check-In
Stretch vs Committed OKRs
Aligning vs Cascading OKRs
Aligning OKR Teams
OKRs vs KPI
OKR vs KPI: with Examples
Input vs Output metrics
Good and Bad OKRs
OKRs and Agile
OKR Templates
Learning resources
Vision & Mission Templates
Google OKR Template
OKRs for Product teams
OKRs for CEOs’ teams
OKRs for Sales teams
OKRs for Marketing teams
OKRs with Google Workspace
North Features
Getting started with North
Org and Team goals
Goal Initiatives
Goal Check-ins
Give Awards
Goal Alignment
Our take on Product
OKRs for AARRR Metrics
On Product discovery
Communicating well
Metrics for Product teams
Telling stories with data
Data visualisation
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