Automation promises to free people from repetitive work and to make processes faster and more reliable. Many enterprises have pursued it enthusiastically, with mixed results. The common pattern of disappointment is automating a broken process, which simply makes the mistakes happen faster. This article takes a thoughtful view of enterprise process automation, focusing on where it genuinely helps and how to scale it without creating a new kind of mess.
Improve before you automate
Automating a flawed process locks in its flaws. The most valuable automation follows an honest look at the process itself, removing unnecessary steps and fixing problems first. Often the biggest gains come from the process improvement, with automation amplifying the result.
Asking whether a step should exist at all, before automating it, prevents the common waste of building automation around work that could simply be eliminated.
Choose the right candidates
Good candidates for automation are repetitive, rule based, high volume and stable. Processes that require judgment, change frequently or handle many exceptions are harder to automate well. Choosing candidates carefully keeps the effort productive and avoids fragile automation that constantly breaks.
Starting with a few high value processes, learning from them and expanding deliberately is more effective than trying to automate everything at once.
Design for exceptions and change
Real processes have exceptions, and automation that cannot handle them creates new problems when it hands off messily to people. Designing how exceptions are managed, and how people and automation work together, is essential to a smooth result.
Processes also change, so automation needs to be maintainable. Automation that is hard to update becomes a liability when the underlying process evolves, as it inevitably will.
Govern automation as it scales
As automation spreads, a collection of unmanaged automations can become as opaque and risky as the manual processes they replaced. Governance that tracks what has been automated, who owns it and how it is maintained keeps the estate healthy.
Visibility into the automation landscape, including its dependencies and failure points, prevents the situation where no one quite knows what is running or what would happen if it stopped.
Key takeaways
- Improve and simplify processes before automating them.
- Choose repetitive, stable, rule based processes as candidates.
- Design for exceptions and keep automation maintainable.
- Govern automation as it scales to avoid a new kind of complexity.