The step got faster and the process got slower
In a supplier's demo, each incoming case (an invoice, a customer email, an order) arrives, the system reads it, matches it against the records, and closes it. Then the next one, and the one after that. The supplier is not cheating. Those cases really do clear, and they really are the bulk of the volume. What nobody opens is the other folder: the cases the system passed over. There is a familiar…
The speed of automation increased while the time it took to process cases slowed down. The system reads each incoming case (invoice, email, order), matches it against records, and closes it. However, it overlooks the cases it passes over. The argument is that the hours saved by automation do not show up in delivery because nobody decided in advance where they should go.
Automation can add work, as cases it cannot handle return to a person, who must check a sample of the automation's decisions due to a lack of oversight. Additionally, some automated decisions are incorrect and require customer intervention, which is the most expensive moment to address. An example is invoice matching, where the system fails to handle invoices with quantity differences, different currencies, or orders changed by telephone.
These irregular cases were previously mixed in with simpler ones, but now they arrive alone, twice a day, without any context. This leads to increased time per invoice and less context for the person handling them. Another example is inbound customer email, where automation handles standard requests well, but challenging emails with multiple questions or incorrect information remain.
Adding a daily sample check on automated replies further increases human processing time. The main issue is that step-level metrics only count what the automation handled, neglecting what was handed back, the sample checks, and cases returned from customers. Measuring these additional costs before implementing automation would have revealed that the share of cases leaving the automated path remains small, and those cases are not significantly harder than the average case.
Three key metrics to track are the time it takes for one case to be completed, including exceptions, sample checks, and returned cases; the share of cases that leave the automated path; and rework, or how many finished cases are reopened and how late they are reopened. Assigning one person to track these metrics daily will provide a clearer picture of the actual impact of automation on the overall process.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
