D3 — Describe the problem
D3 is often labelled "root cause analysis" but that is misleading. D3 is the problem description that makes D4 root cause possible. If D3 is vague, D4 will find a plausible but wrong cause.
Key takeaways
- Use the What / Where / When / How Many frame.
- Anchor every element in a data source, not opinion.
- Include the boundary conditions — Is/Is-Not is where D3 becomes powerful.
- Update D3 as new data arrives during D4.
Is / Is-Not in practice
For each dimension (what / where / when / how many / who / how) write both the Is statement and the Is-Not statement. The contrast is the analytical value.
- Is: defect appears on cavity 3 of a 4-cavity mould, second shift.
- Is-Not: cavities 1, 2 and 4 are clean; first and third shifts are clean.
The Is-Not column often points at the root cause faster than the Is column — a cause hypothesis that does not explain the Is-Not must be discarded.
Quantify everything
- Defect rate: defective units / total produced in the same window.
- First and last observation date.
- Rate over time — flat, ramping or bursty pattern?
- Population scope — total suspect units by lot / date range.
D3 outputs going into D4
- Quantified Is / Is-Not table.
- Defect signature — measurable, reproducible description.
- Data timeline — when the defect started and how it evolved.
- List of candidate root cause paths worth investigating in D4.
Common mistakes
- Skipping the Is-Not column.
- Using adjectives ("a lot", "often") instead of numbers.
- Describing what the team thinks caused it, not what the defect actually looks like.
How Qhubio structures D3
Qhubio's D3 phase captures Is / Is-Not as structured fields and links the problem description directly to the evidence gallery — so D4 candidates are tied to real data.
- Structured Is / Is-Not table.
- Quantified defect signature captured once, reused in the report.
- Evidence (photos, measurements, extracts) linked at the phase.
Frequently asked questions
- Is D3 the same as root cause analysis?
- No. D3 is the problem description. Root cause analysis happens in D4 and depends on a clean D3.
- How much time should D3 take?
- As much as needed to make it precise. Most teams underinvest in D3 and then waste weeks in D4. A day well spent in D3 saves a week in D4.
- What if data is missing?
- Document what data you have, what is missing and how you are going to get it. A D3 with acknowledged gaps is stronger than one with invented certainty.
Related guides
Run this D-step inside a structured workspace
Qhubio is a structured 8D workspace: evidence-grounded phases, phase-gated approvals and audit-ready exports.