1. Identify repetitive work
For several days, record specific tasks, how often they happen, how long they take and where the data comes from. Focus on tasks with a clear beginning and end.
2. Find where mistakes occur
The best candidate isn't always the most time-consuming process. Sometimes fewer mistakes or faster access to information create the greatest value.
3. Start with the smallest useful version
One automated report or data validator lets you test assumptions before building a larger system.
4. Plan for exceptions
A good process can stop and request a decision when data is incomplete. Automation without exception handling may spread errors faster than people do.
5. Measure the outcome
Compare the time saved, quality of results and maintenance effort. Only then choose the next step.