Before choosing software or planning an automation project, examine the last ten real requests that moved through the workflow. Ten cases will not answer every question, but they usually reveal where information goes missing, where work waits and which exceptions matter. The goal is not to prove that automation is needed. It is to identify the smallest operational constraint worth solving.
Why Real Requests Beat a General Workshop
Teams often describe a process as one clean sequence. Real work is less tidy. An email arrives without an attachment, a spreadsheet uses a different field name, an approval waits for the only person who understands the exception or a correction is made without a visible history. Reviewing completed cases replaces assumptions with evidence.
Choose Ten Representative Cases
Select recent examples from one recurring workflow. Keep the starting point narrow: one inbox, form, request type, team or operational handoff. Remove or mask personal and commercially sensitive information before sharing examples outside the business.
- Include ordinary cases that the team considers straightforward
- Include incomplete requests and known exceptions
- Include at least one corrected, delayed or duplicate case
- Use the original inputs together with the final accepted outcome
- Ask the process owner to explain why each exception was handled differently
Record the Work, Not Just the Outcome
For each request, note what arrived, what was missing, who touched it and what had to happen before the work could continue. A simple evidence sheet is enough. You are looking for recurring friction rather than a perfect process model.
- Input channels, attachments and required information
- Manual copying, reformatting or duplicate data entry
- Questions sent back to the requester
- Handoffs, owners and time spent waiting
- Checks, approvals and corrections
- The final record, task, report or decision package
Look for Four Types of Friction
1. Repeated Capture
The same information is copied from emails, documents or spreadsheets into another tool. This can indicate an opportunity for structured extraction, validation or controlled data transfer.
2. Missing or Conflicting Information
Work cannot begin because required information is absent, uncertain or inconsistent across sources. A focused system can make these states visible and prepare a clarification or review task without making the underlying business decision.
3. Unclear Ownership
Requests wait because nobody knows who should act next, priorities are held in individual inboxes or responsibility changes by exception. Routing rules and an explicit review queue may be more valuable than automating the work itself.
4. Invisible Corrections
A team member fixes a value, resolves a duplicate or overrides a rule, but the reason is not recorded. Traceable corrections and approval history can improve control before any further automation is considered.
Describe the Problem Without Naming a Platform
A useful problem statement describes the recurring input, the constraint and the required outcome. For example: ‘Requests arrive through one shared inbox, pricing cannot begin until six required fields are confirmed, and incomplete cases need to reach one reviewer.’ This is more actionable than deciding in advance that the business needs an AI agent, a new portal or a full system replacement.
Define the Smallest Valuable First Build
- Turn copied inbox requests into a structured review queue
- Validate one intake form before creating an internal task
- Synchronise approved fields between two agreed systems
- Alert an owner when a request remains unassigned
- Produce one dependable operational report from existing records
The first implementation should have clear boundaries, representative test cases and a person who can approve uncertain outcomes. Start in a sandbox, with historical examples or beside the live process when production access would add unnecessary risk.
Decide With Acceptance Criteria
Agree how the team will judge the result before building. Can every captured value be traced to its source? Are missing fields visible? Can a reviewer correct the output? Are exceptions routed to the right owner? Does the change remove a meaningful handoff or reduce avoidable rekeying? These questions turn a vague automation idea into a testable operational improvement.
What to Do After the Test
If the ten requests reveal a recurring constraint, accessible examples and a measurable outcome, the workflow may be ready for a focused first implementation. If they reveal unstable rules or no clear owner, fix that foundation first. A Synlara Quick Scan converts the evidence into a workflow map, ranked opportunities and a recommended first scope without forcing a platform decision.
