“Just add AI” disappoints when it improves a process that isn’t the constraint. This page explains the proof-first method behind the baseline: make the real workflow visible, find where it quietly waits on a few experienced people, and define one controlled change you can measure before any pilot, ROI discussion, or broader rollout. Advisor-led, lowest-risk first.
Create a practical, shared view of how the workflow really runs today, not how it is supposed to run on paper.
This helps leadership see where work slows, who gets pulled in, and where experienced people become the safety net.
Method steps
Follow the steps from boundary setting to validation, then review the example flow.
The person accountable for the workflow day to day, or closest to where work stalls.
Staff involved in intake, checking, follow-up, exception handling, and release-related decisions.
A leader or manager who can confirm scope, validate what matters, and identify where rescue work happens.
Define the start point, end point, and the specific workflow being examined. For seafood processing, start with receiving intake and end at release readiness.
Capture the normal sequence of work as it usually happens on an average day.
Identify where work moves between people, functions, or tools, and where a decision is needed before it can continue.
Document where the workflow slows down, depends on memory, or relies too heavily on one experienced person.
Surface what often goes unspoken because it is informal, accepted as normal, or only visible under pressure.
Review the draft with the right people to confirm accuracy, remove ambiguity, and agree on what the workflow really looks like today.
This sequence is here to make the current state visible enough to support the next artifact, not to overcomplicate the story.
Product details, supplier paperwork, and lot information arrive through different channels.
Teams verify what belongs together and what still needs clarification.
Missing or questionable items are flagged and routed.
Hold, release, escalation, or rework decisions are prepared for review.
The lot, paperwork, and decision trail are clear enough to move.
After the current-state picture is validated, leadership can decide which bottlenecks should be ranked, which exception patterns matter most, and what evidence would be needed before any broader process change or AI-supported workflow support is considered.