Automation promises to remove routine work, but projects often start with the wrong process: too rare, too chaotic or too risky. A short checklist helps pick tasks where the effect is quick and visible.
Frequency comes first
The best candidates are tasks that repeat every day: copying data between systems, sending standard notifications, creating documents from templates, assigning incoming requests. A task that takes five minutes but happens fifty times a day is worth far more attention than a complex one that happens once a month.
The rules must be clear
Automation works when you can describe the process as "if this, then that". If every case is decided individually and depends on experience or mood, first agree on the rules with the team. Writing them down often improves the process even before any code appears.
Look at the cost of errors
Manual work is where typos, forgotten follow-ups and lost requests come from. Processes where an error costs money or a customer - wrong prices in an invoice, a missed call-back, a duplicated order - give the biggest return when automated, because a well-tested system makes the same step correctly every time.
Check the data
Automation can only be as good as the data it uses. If customer records are duplicated or fields are filled in inconsistently, start by cleaning and standardising them. Otherwise the automated process will spread the mess faster.
A simple way to prioritise
List your candidate tasks and give each a score from 1 to 5 for frequency, clarity of rules and cost of errors, then subtract a score for complexity of implementation. Start with the top two or three. Measure the time spent before and after, and use these numbers to decide what comes next.
The short version
Automate frequent tasks with clear rules where errors are expensive, and make sure the data behind them is clean. Start with a couple of quick wins and let the measured results guide the next steps.