We want to deploy AI where it will deliver the highest operational impact, but every department manager claims their workflow is the most critical. How do we audit our internal data to identify our true automation priorities?

Question

Tyler Smith · Accepted Answer

Do not rely on department head opinions to choose your automation targets. Department leaders advocate for pet projects or squeaky wheels. To find the real operational leverage points in your company, look directly at the data trails left by administrative friction.

Pull raw data from where operational pain actually lives: your customer support desk, field tickets, billing dispute logs, and employee exit interviews. You can run a lightweight scraper or data extraction script over your last six months of support tickets and invoicing errors. Categorize the repetitive complaints, recurring status questions, and manual administrative re-entries.

You are looking for three specific signals:
- High-volume, low-complexity queries: Routine requests like shipment status updates, invoice re-sends, or appointment reschedules consume enormous human labor while providing zero strategic value.
- Recurring internal data handoffs: Look for bottlenecks where an employee in one department manually retypes data from an email or spreadsheet into an operational system.
- Billing and operational exception logs: Identify the manual reconciliation steps your finance team executes every month to correct human entry errors.

Bring this compiled data into your next quarterly planning session. Use the Identify, Discuss, and Solve (IDS®) discipline to target the single largest concentration of wasted labor hours as a company Rock. When you base your automation roadmap on empirical friction data rather than manager preference, your first operational deployment will generate immediate, measurable capacity relief across your entire business.