Bringing clarity and structure to case intake, classification, and reporting
This project focused on simplifying a case management system that had become inconsistent and difficult to use. The goal was to improve clarity, reporting, and day-to-day usability for staff.
Assess the Structure
- Reviewed how cases were categorized and used
- Identified inconsistencies in classification and data entry
- Mapped how the system was functioning in practice
Restructure the Model
- Simplified case types and classification
- Moved primary categorization into the Type field
- Reduced overlap and ambiguity
Reinforce Consistency
- Aligned fields and workflows to the new structure
- Ensured the system supports consistent use
- Created a foundation that holds over time
Refine
Challenge
This system was originally built to support case intake and tracking, but over time it became clear that some of the structure was working against us.
The main issue was that Case Reason was carrying too much responsibility. It was being used to represent different kinds of things at once, including registrations, data corrections, and duplicate record consolidation. This made it harder to keep data consistent and harder to report on cleanly.
Insight
The problem was not volume or user error. It was that the structure itself was doing too many jobs at once. The same field was being used to decide routing, reporting, and meaning. Case Reason was acting as:
- a classification system
- a workflow signal
- and sometimes a catch-all for edge cases
That kind of overlap creates confusion, even with a small number of users.
Solution
Instead of trying to clean up usage, the structure of the system was refined to better separate responsibilities.
- Separated classification (Type) from request detail (Case Reason)
- Reduced Case Reason from multi-purpose use to a single, clear role
- Introduced Form Type to distinguish structured submissions
- Supporting structure was introduced where needed instead of overloading one field
- The structure was aligned with how cases are actually processed
The goal was to make the system clear by design, not dependent on perfect usage.
Result
With the structure clarified, the system now works as intended:
- Reports can now be filtered reliably by Type without manual cleanup
- New cases follow a consistent structure without relying on training memory
- Case data is more consistent without extra effort
- The system is easier to train and easier to use correctly
Most importantly, the structure now supports the work instead of relying on people to interpret it.