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Idea Brief: Invoice Line Item Recode Tool

Created: 2025-12-15 Author: Claude Code

Problem Statement (What)

Coordinators and suppliers manually recode invoice line items when categorization is incorrect:

  • Line items are scattered across multiple items with wrong service types
  • No bulk operations available - must edit each item individually
  • No way to identify patterns of miscategorization
  • Time-consuming process prone to human error
  • No visibility into common recoding patterns

Current State: Edit line items one-by-one via modals; no batch processing or rule-based assistance

Possible Solution (How)

Xero-style recode interface with:

  • Table view - All invoice line items in one place with sortable columns
  • Multi-select - Checkbox selection of multiple items
  • Common rules - Pre-built queries (e.g., “All items with ‘Physio’ in description”, “Items with category X but amount > Y”)
  • Bulk recode - Apply new service category to all selected items at once
  • Filtering - Filter by date, amount, description, current category
  • Confirmation - Preview before bulk applying changes

Example:

// Before
- 50 line items across 5 invoices with wrong categories
- Manual edit each one: 50 clicks


// After
- Click "Common rule: Physio items → Allied Health"
- Auto-selects 12 matching items
- Click "Recode all" → Done

Benefits (Why)

User Efficiency:

  • Reduce recoding time from 30-45 minutes per invoice to 5-10 minutes (70% time saving)
  • One-click bulk operations vs. 50+ individual clicks

Data Quality:

  • Consistent categorization through rules engine
  • Reduced manual error rate (visual confirmation before apply)

Visibility:

  • Identify systematic categorization issues
  • Audit trail for all recoding actions

Owner (Who)

Will (Product Owner) - Decision authority on feature scope and rules engine

Other Stakeholders

Accountable: Tim (Engineering Lead) - Implementation oversight Consulted: Coordinators (end users), QA team, Finance (impact on reporting) Informed: Support team, Jira management

Assumptions & Dependencies, Risks

Assumptions:

  • Service categorization rules are defined and stable
  • Common recoding patterns are identifiable upfront
  • Bulk updates maintain audit trail via existing LogsActivity trait

Dependencies:

  • BillItem model and ServiceType taxonomy must be stable
  • Existing UpdateBillItem action can be leveraged
  • Activity logging infrastructure already in place

Risks:

  • HIGH → Bulk changes could affect financial reporting if rules are incorrect → Mitigation: Strict rule validation, QA review before launch
  • MEDIUM → Performance if recoding large invoice batches (1000+ items) → Mitigation: Batch processing, progress indicators
  • LOW → User confusion with new interface → Mitigation: Clear UI labels, tutorial/help text

Estimated Effort

Medium (2 sprints / 4-5 weeks)

  • Sprint 1: Backend rules engine + API endpoints (rules, filtering, bulk update)
  • Sprint 2: Frontend UI component (table, multi-select, rule builder)

Proceed to PRD?

YES - Clear user need, defined scope, leverages existing infrastructure. Ready for detailed specification.

Decision

  • Approved - Proceed to PRD
  • Needs More Information
  • Declined

Approval Date: 2025-12-15

Next Steps

  1. Create PRD with detailed requirements
  2. Design rules engine data structure
  3. Create Xero-style mockups
  4. Break down into user stories
  5. Create implementation plan

Notes: This aligns with TP-1864 (Invoices V2) modernization efforts. Consider integration with invoice approval workflows downstream.