We talk to a lot of businesses that have tried automation before. They bought the tool, hired the consultant, kicked off the project. Six months later, nothing changed — or worse, they added complexity without removing any work.
Here’s why that keeps happening, and what to do differently.
Problem 1: Automating the wrong thing
The most common failure mode isn’t technical — it’s picking the wrong process to automate.
Teams often start with whatever feels most painful. But “painful” and “automatable” aren’t the same thing. A process that’s painful because it requires nuanced judgment is a bad automation candidate. A process that’s painful because it’s repetitive and rule-based is a great one.
What to do instead: Map your workflows and look for high-volume, low-variability tasks. Those are your quick wins.
Problem 2: No one owns it
Automation projects love to live in limbo. IT thinks the business team owns it. The business team thinks IT is handling it. The consultant delivered a prototype and moved on.
Without a clear owner who understands both the process and the technology, things drift.
What to do instead: Assign a single owner per automation. They don’t need to be technical — they need to care about the outcome and have authority to make decisions.
Problem 3: Over-engineering from day one
We’ve seen teams spend months building elaborate automation systems with every edge case handled, every exception covered, and every integration polished — before they’ve validated that the core automation even works.
Then the business changes, requirements shift, and all that upfront work is wasted.
What to do instead: Build the simplest version that handles the 80% case. Run it for two weeks. Learn what actually breaks. Then iterate.
Problem 4: Ignoring the humans
Automation doesn’t exist in a vacuum. Real people use it, work alongside it, and depend on it. If you build an automation that changes someone’s workflow without involving them, expect resistance.
We’ve seen beautifully engineered automations sit unused because the team didn’t trust them, didn’t understand them, or felt threatened by them.
What to do instead: Involve the people who do the work from day one. Show them what it does. Let them test it. Make them partners, not passengers.
Problem 5: No way to measure success
“We automated it” is not a success metric. How much time did it save? How many errors did it prevent? What’s the cost of running it versus doing it manually?
Without clear metrics, you can’t tell if the automation is working — and you definitely can’t justify expanding it.
What to do instead: Define your baseline before you start. Measure after. Compare. Be honest about the results.
The pattern that works
The automation projects that succeed tend to follow the same pattern:
- Pick a specific, measurable problem
- Build the simplest thing that could work
- Get it in front of real users fast
- Measure, iterate, expand
It’s not glamorous. But it works.
If you’ve got a process you think could be automated but aren’t sure where to start, let’s talk. We’ll help you figure out what’s worth automating — and what isn’t.