The Three Hardest Things About Production RPA

The three hardest things about running RPA in production have nothing to do with the automation logic.

1. Detection: Knowing When Something Went Wrong

First: knowing when something went wrong. The automation runs. It does not crash. But it clicked the wrong field and the data went to the wrong place. Nothing in the logs says "error." The output is wrong but the process completed "successfully." How do you find out? Usually when a customer calls.

2. Investigation: Figuring Out What Happened

Second: figuring out what happened. You know something is wrong. The automation ran 200 times today. Which run had the issue? What step? What was on the screen? Without a way to replay what happened visually, your engineer is doing forensic work. They are manually clicking through the same application trying to reproduce a problem they cannot see.

3. Resilience: Preventing Recurrence

Third: making sure it does not happen again. You found the issue. A popup appeared that was not there during testing. You handle it. Two weeks later, a different popup. A month later, the UI changes. The fixes accumulate. Every one is small. But they never stop. And each one requires a human to investigate, understand, and deploy a fix.

The automation itself is usually simple. Click here. Type that. Navigate there. The difficulty is everything around it: detecting problems, investigating root causes, and building ongoing resilience against an environment that is constantly changing.

When evaluating RPA solutions or building your own, do not focus only on "can it automate this workflow." Anything can automate a workflow in a demo environment. The questions that matter for production: How does it detect failures that do not produce error codes? How do you investigate what happened on a specific run? And how does the system adapt when the environment changes without requiring a human to notice and fix it every time?