- Best for
- Owners who know they should automate something, but don’t know what.
- Time to run
- One afternoon to list and score. One month to test.
- You finish with
- A ranked short list, and the first task switched on.
01 The problem
Most owners know there’s work in their business a machine could do. The hard part is picking it. The loudest task gets automated, not the most valuable one, and the project stalls when the tool needs more care than the task ever did.
Guessing has a cost: software you pay for every month, a team that stops trusting the next change, and the hours you meant to save still being spent.
02 The numbers
Three numbers decide whether a task is worth automating. You can collect all three in an afternoon.
| Measure | How to get it | Why it matters |
|---|---|---|
| Hours per week | Ask everyone who touches the task for one week of estimates. | What you’ll save. |
| Cost of a mistake | The last time it went wrong, what did it cost to fix? | The risk of letting software do it. |
| Judgment needed | Low, medium or high: does every case need a decision? | If every case needs a judgment call, it rarely pays off. |
Rule of thumbIf a task is frequent, boring and low-risk, automate it. If it is rare, risky or needs judgment, leave it with a person.
03 The steps
- 1List every repeat taskWho: you. Time: one hour. Done when every task the team does weekly is on one sheet.
- 2Score each taskWho: you and one team lead. Time: one hour. Done when hours, cost of a mistake and judgment are filled in.
- 3Pick the top twoWho: you. Time: the same day. Done when two tasks are chosen and the rest are parked on purpose.
- 4Test for a monthWho: whoever does the task today. Time: four weeks. Done when you have hours before and after, and a keep or drop decision.
Grab a notepad and ask each person on your team one question: what do you do every week that feels like copy-paste? Write down every answer. That list is your starting point, and it takes about fifteen minutes.
04 The template
A ranked list of tasks worth automating, with the payback for each.
BIZPLAYBOOKS

Kevin helps owners use AI to get time and money back, then turns what works into free playbooks.




