SMART goals are popular because vague intentions are difficult to execute. Yet not all work is predictable. A target such as “publish ten pages by Friday” may help an experienced editor but push a new researcher to prioritize speed over accuracy. Good goal setting starts by understanding the work rather than applying one formula automatically.
The core idea
Evidence reviewed by the CIPD suggests specific, challenging targets can support relatively straightforward tasks, while complex tasks that require learning and adaptation may benefit more from learning or behavior-focused objectives. Goals also need resources, commitment, review and feedback.
How to apply it
- Define the outcome in observable terms: what must be different when the work is complete?
- Judge task complexity. Is the approach familiar, or will people need to experiment and develop capability?
- For predictable work, choose a measurable result with an appropriate deadline.
- For unfamiliar work, consider a learning goal such as testing three approaches and documenting findings.
- Schedule feedback checkpoints and revise objectives if reality changes; do not use a target to conceal an unrealistic workload.
A workplace example
A software team learning a new accessibility standard could be harmed by a purely numerical target of “fix 100 issues.” A stronger first-stage goal is to assess critical components, study remediation patterns, verify fixes using assistive technology and create repeatable coding guidance. Speed targets can follow once the process is understood.
What to watch out for
The letters in SMART are a memory aid, not a guarantee of better performance. Poorly designed measures can encourage shortcuts or gaming. Check whether meeting the measure would genuinely improve the outcome, and use team goals when success is shared.
Practice and reflect
Rewrite one current objective as either an outcome goal or a learning goal; explain why you chose that format.