Need a change
Current and proposed values show exactly what the request will update.
HICX · Supplier management
Mass edit.
One change.
Many suppliers.
A guided workflow for updating supplier data at scale, with a clear view of the impact before submitting for approval.
PRODUCT DESIGN CASE STUDYTL;DR
- Role
- UX / Product Designer · interaction & workflow design
- Team
- HICX · Supplier management
- Timeline
- During my HICX tenure · 2025–2026
- Result
- A four-step flow that turns bulk changes into an approval request.
01 / The problemA shared change.
A shared change.
Repeated work.
When the same change affects many suppliers, editing each record individually turns a single task into repetitive work.
A new regulatory requirement, for example, may require an organisation to change payment terms across an affected supplier population. Updating those records one by one takes time and creates opportunities to miss suppliers or enter inconsistent values.
A mass action reduces that repetition, but also increases the consequences of an incorrect selection. Users need to understand which records are included, what will change and which exceptions need attention.
The design challenge
Make a large data change manageable while keeping its scope, consequences and approval requirements visible.
Four steps to an
approval-ready request.
The flow separates each decision: identify the records, choose the field, set the replacement value and review the impact.
01Select recordsFind the relevant suppliers through advanced search.
02DefineChoose the data structure and attribute.
03New valueSpecify the shared replacement value.
04Review & createCheck changes and exceptions, then submit a request.
The final action creates a change request. Supplier data changes only after approval.
Start where users
find the right suppliers.
Advanced search is the entry point to mass edit. Users apply filters, inspect the matching suppliers and start a mass update directly from the results.
Advanced search turns a business criterion into a visible set of supplier records.
Connect discovery with action.
The result count and mass-update label connect the search to the next task. Users can inspect the population before entering the change flow, rather than reconstructing a supplier list elsewhere.
Choose the field
in its data context.
Supplier information can belong to different data structures. The user first chooses the structure, then the attribute available within it. This sequence helps distinguish the intended field before a replacement value is entered.
Reveal decisions in sequence.
The attribute depends on the selected structure. Presenting that dependency explicitly breaks a complex data model into two connected choices. The selected structure and attribute also determine the approval route, as explained in the interface.
Make the overwrite
explicit.
The next step defines one value for the selected population. The interface explains that existing values will be overwritten and that validation rules apply before the request is created.
Five selected.
Three changes.
The number of search results is not necessarily the number of records that will change. The review makes that distinction visible before submission.
Already up to date
The record already contains Net 15, so it requires no change.
Cannot be included
An open change request blocks the update. The reason is shown for follow-up.
Explain the exceptions.
The blocked supplier appears separately with a specific explanation: its existing change request must close before the value can change. Export and saved-search actions support follow-up, while the final button states “Create request for 3 records”.
Follow a mass update.
Walk through the payment-terms example, from five matching suppliers to a request for three changes.
Interactive screen walkthrough · Illustrative supplier data
Efficiency with
visible control.
One connected journey to find the right records, prepare a shared change and submit it for approval.
Reduce repeated decisions
The user defines a field and replacement value once for a supplier population. A focused sequence keeps each decision manageable.
Keep consequences visible
Record-level comparisons, validation results and explicit exclusions explain the final request. Approval remains a distinct step before data changes.
| Design challenge | Response in the design |
|---|---|
| Target the correct suppliers | Start with advanced-search filters and inspectable results. |
| Navigate a complex data model | Select the data structure before its attribute. |
| Understand a bulk overwrite | Show the replacement value, scope and current-to-new comparisons. |
| Reconcile different record outcomes | Distinguish changes, unchanged values and excluded records. |
| Preserve approval control | Create a request before applying any data change. |