Which business workflows should be automated?
A practical framework for choosing automation candidates, defining controls, and avoiding automation of broken processes.
Good automation candidates are frequent, rule-based, measurable, and reversible. They use reliable data, have a clear owner, and create little value when performed manually. Examples include routing approved documents, creating reminders, preparing recurring invoices, flagging low stock, and moving accepted orders into fulfillment. A process should be understood and stabilized before software accelerates it.
What this means for a business
Map the trigger, required data, decision rules, exceptions, approval owner, system action, and audit trail. Start with one bounded workflow and compare results against the manual process. Automation can be deterministic, AI-assisted, or both. Use ordinary rules when the decision is exact; use AI only where interpretation adds value and confidence can be checked.
Real-world example
Instead of automatically ordering every low-stock item, the ERP can calculate replenishment needs and an AI layer can summarize unusual demand or supplier risk. Purchasing receives a prepared recommendation with evidence. A buyer still approves quantities when seasonality, cash flow, or customer commitments require judgment.
Limitations and what to consider
Do not automate unclear, rarely used, highly political, safety-critical, or irreversible work merely because it is inconvenient. Poor master data and undocumented exceptions create fast, consistent errors. Define ownership, fallback behavior, monitoring, and a way to stop or reverse the workflow.
Common questions
Should we start with AI or ERP?
Start with the missing foundation. If operational data is scattered, stabilize ERP and processes first. If records are sound but knowledge is hard to find, private AI may deliver an earlier win.
How do we measure value?
Measure cycle time, exception rate, rework, backlog, error correction, and employee handling time before and after the change.