Building Smarter Workflows: Our Approach to Automation
December 15, 2020
We believe good automation doesn’t just save time—it eliminates friction.
When automation is done well, it removes repetitive tasks, reduces human error, and allows people to focus on work that requires judgment and creativity. Done poorly, automation creates confusion, blocks users, and sometimes makes problems worse. The key difference is in how intentionally the system is designed.
Start With the People
Every process begins with people, and automation should reflect that. It’s tempting to think of automation as a technical exercise—“when X happens, do Y.” But behind every workflow are real users who interact with the system daily.
When designing an automated process, it’s worth asking:
- What do users expect to happen at this step?
- Does the automation make their work easier, or does it surprise them with hidden rules?
- Will they know how to recover if something doesn’t go as planned?
Clarity matters. A flow that updates records silently without any communication can feel mysterious, even untrustworthy. Building in prompts, error handling, and clear outcomes ensures people stay confident in the system.
Build for Exceptions
Real-world processes rarely move in a straight line. Deals stall, approvals get delayed, data is entered incorrectly, and customers change their minds. Automation that only works under perfect conditions is fragile.
That’s why exception handling is so important. Examples include:
- Catching missing required fields and alerting the right person rather than letting the process fail.
- Designing approval flows that can be re-routed if someone is out of office.
- Allowing for manual overrides when an unusual but legitimate case arises.
By planning for what might go wrong, workflows can bend without breaking. The best automation anticipates detours.
Measure and Iterate
Automation isn’t “set it and forget it.” Processes evolve, and the systems that support them should evolve too. Every automation should have a feedback loop—some way of checking if it’s still serving its purpose.
That might look like:
- Tracking how often certain error paths are triggered.
- Gathering user feedback after new automation is rolled out.
- Reviewing whether automation is saving time or simply adding steps elsewhere.
Measuring effectiveness ensures the automation continues to improve instead of becoming invisible technical debt.
The Bigger Picture
Automation isn’t only about speed—it’s about creating a system where work flows naturally, errors are caught before they spread, and people can trust that the right things are happening at the right time.
When workflows are designed thoughtfully—with people, exceptions, and iteration in mind—they create consistency and confidence. Instead of forcing users to adapt to rigid processes, automation adapts to the reality of how work gets done.
Good automation doesn’t just keep the system moving. It makes the system feel seamless.