Study 03 · Process improvement · C
A slow approval process.
A clearer decision.
A fictional technology team receives hardware requests across several countries. Explore 24 invented records, see where its queue appears to stall and review a controlled improvement hypothesis. This uses a scenario related to—but entirely separate from—my earlier Optum experience.
Define → Measure → Analyse
What is slowing the work?
Select a cause to examine the supporting subset. The dataset is published, so the figures can be checked independently.
INVESTIGATION
Full synthetic sample
The labels highlight candidate points of friction. They do not prove root cause: this would require observation, interviews and a process walk-through.
Use a Pareto view to prioritise questions; use Five Whys to test a cause; map the handoffs; and track progress through a visible queue. Use DMAIC as a structured improvement cycle, not a qualification claim.
SOURCE DATA · FILTERABLE
| Request | Market | Issue | Days |
|---|
24 fictional request records
Improve → Control
The proposal is a testable hypothesis,
not a claimed result.
Make intake complete
Define minimum device requirements and stop incomplete requests entering the approval queue unnoticed.
Name each owner
Assign triage, technical review and exception responsibilities with visible handoffs.
Review exceptions
Document why country-specific alternatives need separate assessment and approval.
Measure again
Compare equivalent samples and check whether rework, elapsed time and unowned requests change.
Career evidence · A
Connection to actual experience
My October 2026 CV supports earlier international hardware assessment, PADU classification, technology sourcing and cross-functional coordination at Optum/UnitedHealth Group. The request records, figures and suggested improvement above are invented and are not representations of those employers’ internal workflows.