Software practice / Simulated SME process
Check before
you import.
Turn expert rules into a procedure someone can use.
Repair a rejected staff roster, then catch a change that passes validation but was never authorized. A focused practice sample for the people who administer learning systems.
Preview / existing employee
Review the change against its source.
- Work email
- Changed Requested
- Team assignment
- OPS → SUP Check the source
Validation checks structure.
The reviewer checks authorization.
- Audience
- New training-operations coordinators importing a staff roster.
- Performance task
- Correct a file from an approved source, review the changes and preserve unaffected records.
- My role
- Learning design, rule-to-practice mapping and language review.
The design decision
Check each change against its approved source.
The initial fictional request was to explain roster imports. I narrowed the performance task to two observable jobs: repair a blocked file from an approved source, then review a valid update before applying it. The simulated rule analysis separates what validation checks (structure) from what the coordinator must check (source, authorization and unaffected records).
A short reference handles the repeatable steps; two editable tasks let learners correct a blocked batch and catch a valid-but-unauthorized change. Row-specific feedback supports correction and retry, while edits clear readiness so the learner must validate and review again. These are design choices in the fictional sample, not evidence from a real product or learner pilot.
Repair a blocked batch
Use an approved people-data extract to resolve an invalid identifier and an unknown team code. A guessed identifier can have the right format and still identify the wrong record.
Inspect a valid update
Review changed fields for an existing person. An allowed team code can still be an unapproved assignment. People absent from this batch must remain unchanged.
Working with expert content
The questions change the design.
This is a simulated SME exercise. The product-operations role, initial memo, answers and proposed review changes were authored for this portfolio. No real expert interview or stakeholder approval is claimed.
| Question to resolve | Design consequence |
|---|---|
| Does validation prove that a change is authorized? | Separate the structural check from an explicit source review. The second task deliberately passes validation. |
| What identifies the same employee after an email change? | Keep the identifier visible in the preview and distinguish an update from an addition. |
| What happens if a row is missing or the file is edited? | Show retained records in the result; clear readiness after an edit and require fresh validation and review. |
Language and interaction
Keep the evidence close to the decision.
The approved source, team directory and current records stay available during practice. Field labels use the product’s exact terms; feedback explains them in plain language. Names and identifiers retain their source spelling and formatting.
Learners edit a small table, validate it, inspect a preview and confirm the changes. Errors identify the affected field and explain the consequence. There is no timer, required audio, drag-only action or file upload.
Review and evidence
What this sample can demonstrate.
The working sample demonstrates procedural decomposition, expert-question design, traceable rules, state-based feedback and a performance-support companion. It does not demonstrate an actual client engagement or prove that the training improves performance.
- Technical checks cover whole-file blockers, matching by identifier, source mismatches, unchanged records and invalidation of an earlier review after edits.
- The interface uses labeled native controls, explicit feedback, a focusable result region and horizontally scrollable tables where needed.
- The print reference is a separate reading layout; the HTML reference provides reflowing text.
Browser, zoom, screen-reader and intended-user review remain pending. Automated checks establish tested logic only. Read the accessibility notes.
What I would validate next
Test a fresh batch with the real system’s rules.
First, a product SME would verify the schema, matching behavior, error handling and authorization process. New coordinators would then attempt a different batch using its approved source. I would observe source use, field accuracy, detection of unauthorized changes and preservation of unaffected records, then revise the guidance around the errors they actually make.
Self-directed concept. RelayWorks and its rules are fictional. No product-SME validation, learner pilot or measured business results are claimed.