Not every manual process deserves automation — and trying to automate everything at once is how projects stall. Here's the framework we use with clients before writing a single workflow.
Step 1: Map the process as it actually happens
Not as it's documented — as it actually happens, including the workarounds. Talk to the people doing the work, not just the people managing it.
Step 2: Score each workflow on three dimensions
- Volume — how often does this happen? Weekly beats monthly, daily beats weekly.
- Time sensitivity — does delay directly cost you money or leads (like lead response), or is it more forgiving (like quarterly reporting)?
- Error cost — what happens when a human makes a mistake in this process? Missed deadlines, compliance risk, and lost revenue rank highest.
Step 3: Prioritize by ROI, not novelty
The flashiest AI use case is rarely the highest-ROI one. Document collection automation is unglamorous — and it's often the single highest-ROI workflow for an accounting firm during tax season.
Step 4: Build in monitoring from day one
An automation without monitoring is a liability waiting to happen. Every workflow we build includes error handling and alerting so a broken integration gets caught in minutes, not weeks.
Step 5: Review quarterly
Your business changes. Your tools change. AI models improve. A workflow built a year ago probably has a better version available today.
Want a second set of eyes on your workflow priorities? Book a free AI Operations Audit and we'll map it with you.