Most automation projects that fail don't fail for technical reasons. Here are the mistakes we see most often, and how to avoid them.

1. Automating a poorly defined process

Automating a fuzzy process just makes it fuzzy faster. Before automating, the process needs to be clear, documented, and followed consistently by the teams currently running it manually.

2. Forgetting the edge cases

80% of a process often follows a simple rule. The remaining 20% (exceptions, edge cases, human decisions) is usually what causes a poorly prepared automation to fail. It's better to identify them from the start and explicitly decide to exclude them from scope, rather than discover them in production.

An automation that handles 80% of cases and fails silently on the remaining 20% is more dangerous than a fully manual process.

3. Building in no visibility

An automated process with no logs or alerts becomes a black box. When something goes wrong, nobody notices until the consequences become visible elsewhere. Planning a minimum level of traceability from the first version avoids this trap.

  • Log every run and its decision
  • Automatically alert on failure or unusual behavior
  • Keep a simple way to fall back to manual processing

4. Underestimating change management

An automation that replaces a task someone used to do changes their day-to-day work. Without clear communication about what's changing (and what the team will do instead), adoption fails, even if the technical system works perfectly.

In summary

The technology is rarely the limiting factor. A clear process, anticipated edge cases, visibility, and a team on board from the start make the difference between an automation that gets adopted and a script that runs in general indifference.