Complexity-Aware Casework Reporting

Category: Forensic laboratory tooling  |  Status: Method validated against production data; tool not yet built

A reporting and analysis layer over a forensic LIMS that produces management-facing reports accounting for how hard each case actually was, rather than counting every case as equal.

The idea

Conventional laboratory productivity reporting weights one case as one case. A forty-item homicide and a single-item drug case score identically. Every manager knows this is wrong, and a typical response is to debate it in meetings without data.

The approach here is complexity stratification: bin cases within a unit by difficulty, and compare like with like. The framing matters, and it is deliberate — stratify, never weight. This does not add a black-box scoring system that decides some cases are worth more than others. It removes an invisible weighting that is already present in any report that treats all cases as equivalent.

What has been proven

The method was tested against real production LIMS data, not a model:

  • The core premise held. Across every examiner in a discipline with enough cases to test, cases in the hardest band took materially longer than those in the easiest band — with no exceptions, at a median ratio of roughly 1.5×.
  • The underlying schema was mapped well enough to establish which disciplines can be stratified on the available data and which cannot yet — and, importantly, why, so that nobody over-claims what the method can currently support.

What it is for

It answers management questions that currently get argued from anecdote: is this unit's caseload genuinely harder than that one's, where is turnaround time actually being spent, and is a shared queue being worked evenly. It is aimed at those questions specifically — not at being another backlog dashboard, which most laboratories already have.

Current status

Discovery and the semantic model are complete and validated against real data. 

The value of this project right now is the proven method, not software. The method and its queries are portable to any laboratory running a comparable LIMS; measured baselines from any particular agency stay with that agency.