Brainstorming and Validating Potential Causes

The best cause analysis begins not with answers—but with the right questions, asked in the right way. Fishbone brainstorming isn’t about filling a diagram. It’s about uncovering the truth behind failure.

When a defect appears, a delay occurs, or a process collapses, teams often rush to assign blame. But I’ve seen that same mistake repeated in hundreds of investigations. The real power lies not in the fishbone itself—but in how you populate it.

My rule: never assume a cause is valid until you’ve tested it. If you can’t trace it to data, it belongs in a discussion—not a solution. This chapter walks you through how to conduct effective fishbone brainstorming, separate fact from assumption, and validate potential causes using structured RCA workshop methods.

Planning the Fishbone Brainstorming Session

Set the Stage for Evidence-Based Thinking

Start by selecting a facilitator who isn’t emotionally tied to the outcome. This role demands neutrality and discipline. The goal isn’t consensus—it’s clarity.

Invite participants who understand the process: operators, engineers, supervisors, and support staff. A diverse team reduces blind spots and increases credibility in the final analysis.

Before the session, distribute a brief problem statement: “The machine halted production for 47 minutes on March 12 due to a sensor fault.” Keep it specific. Avoid vague terms like “issues” or “problems.” Precision prevents drift.

Choose Your Categories Wisely

Use the 6M framework—Man, Machine, Method, Material, Measurement, Mother Nature—for manufacturing. For services, switch to 4S: Surroundings, Suppliers, Systems, Skills. For software, 8P: People, Processes, Policies, Programs, Partners, Performance, Product, and Pressures.

Don’t pick categories blindly. Adapt them based on context. In a software deployment failure, “Method” becomes “Deployment Process.” “Material” shifts to “Code Dependencies.” The category must reflect the reality of your environment.

Every category should be a potential filter—narrowing the scope so that brainstorming doesn’t become chaotic.

Conducting Effective Fishbone Brainstorming

Use Structured Techniques, Not Free-For-Alls

Open the session with a clear instruction: “We are not here to solve the problem. We are here to list every possible cause.” This shifts focus from judgment to exploration.

Use the “silent brainstorm” technique: give each participant 5 minutes to write down causes on sticky notes—no talking. Then group them by category. This avoids dominance by one voice and surfaces quieter insights.

Rotate the task: ask different people to lead each category. This builds ownership and prevents the facilitator from steering the conversation.

Ask “Why?” to Push Beyond Surface Causes

When a cause is listed—“Operator error”—ask: “Why did the operator make that mistake?” If the answer is “They were rushed,” follow up: “Why was the schedule tight?”

This is where root cause brainstorming becomes actionable. You’re not just listing causes—you’re probing for layers. A cause that feels obvious at first glance often hides a deeper systemic flaw.

Ask five iterations of “Why?” until you reach a cause that can’t be broken down further. This is a proven RCA workshop method for identifying true root causes.

Flag Speculation with a Color Code

Not all causes are equal. Mark speculative ones with yellow post-its. Tag them with: “Needs verification.” For example: “The sensor failed because of a power surge” — needs data from the electrical logs.

Use red for unverifiable claims: “It must’ve been poor training.” These should not be treated as viable without evidence. Red flags are not failures—they’re warnings.

Only red, yellow, and green categories will be reviewed. Green means “data-backed.” Yellow means “testable.” Red means “discard or reframe.”

Validating Fishbone Causes with Data

Build a Cause-Verification Matrix

After brainstorming, create a simple matrix to evaluate each candidate cause. Use these four criteria:

• Does evidence support it? (Yes/No)
• Is it directly linked to the effect? (Yes/No)
• Can it be tested? (Yes/No)
• Is it unique, or does it overlap with another cause? (Yes/No)

Assign a score: +1 for each “Yes.” A cause must score at least 3 to proceed. Anything below is either invalid or needs refinement.

Use Data to Confirm or Reject Causes

Go to the source. If a cause points to “Faulty software update,” pull the deployment logs. Check timestamps, error codes, and rollback triggers. If the log shows the update completed successfully and no errors occurred, the cause is invalid.

When a cause is tied to a human action—“The technician skipped the calibration”—verify the maintenance log. Did they sign off? Was there a shift change? If not, the cause may be misattributed.

Real cases show that 70% of apparent “human errors” stem from flawed processes, not people. The data reveals the truth.

Test Interdependencies

Causes aren’t isolated. A temperature spike might be due to cooling failure, but that failure might stem from poor maintenance schedules. You can’t validate one cause in a vacuum.

Draw dotted lines between causes to show relationships. Ask: “If this cause is removed, does the effect still happen?” If yes, it’s likely not a root cause. If no, it’s a candidate.

This interplay is why RCA workshop methods emphasize cross-functional review. A technician may not see a procedural gap, but a quality auditor will.

Common Traps in Fishbone Brainstorming

Assuming the Obvious Is True

The most dangerous assumption? “It must be operator error.” This is where bias creeps in. I once worked on a project where the team blamed the operator for a system crash—until we checked the logs and found it was a memory leak in the software, triggered by a scheduled task.

Never let the easiest explanation override the data. The goal isn’t to assign blame—it’s to prevent recurrence.

Overloading the Diagram

More branches don’t mean better analysis. I’ve seen fishbones with 40+ causes. That’s noise. The number of causes isn’t a measure of quality.

Focus on causes that are: verifiable, actionable, and directly related to the effect. If you can’t act on it, remove it.

Skipping the Verification Step

Too many teams stop after brainstorming. They move straight to countermeasures. That’s a recipe for repeated failure.

Validation isn’t an afterthought. It’s the core of fishbone brainstorming. If you can’t prove it, don’t treat it as a root cause.

Checklist: Validating Fishbone Causes

The following checklist ensures your RCA is grounded in evidence, not opinion.

• Each cause is tied to a specific event or data point.
• Every speculative cause has a verification method.
• Causes are ranked by impact and verifiability.
• Interdependencies between causes are mapped and tested.
• Only green (verified) and yellow (testable) causes are retained.

Use this checklist after your brainstorming session. It’s your final gate before moving to corrective actions.

Frequently Asked Questions

How do I ensure fishbone brainstorming stays focused?

Start with a precise problem statement. Assign a facilitator to keep the team on track. Use time-boxing: 15 minutes per category. If the discussion drifts, pause and ask: “How does this connect to the effect?”

What if team members keep repeating the same cause?

Don’t dismiss it. Ask: “What specific aspect of that cause are we seeing?” This uncovers whether it’s a mislabeled symptom or a real pattern. If it’s repeated, it may be a red flag worth deeper investigation.

Can fishbone brainstorming work in service environments?

Absolutely. Adapt the categories: for customer service, use People, Process, Policy, Partner, Environment, and Performance. The method is the same—only the context changes.

How many causes should I keep for analysis?

There’s no fixed number. Focus on 3–7 causes that are verifiable and have high impact. If you have more, prioritize using the verification matrix. Less is more when it comes to actionable root causes.

How do I handle disagreements during validation?

Use the “data-first” rule. If one person says “It’s a procedural gap,” another says “It’s a staffing issue,” demand evidence. Pull the policy document. Check the staffing schedule. Let the data resolve the conflict.