1. Root Cause Analysis: Why? Why? Why?
William A. Lindley
April 6, 2001

2. Why Do Root Cause Analysis?
“Just fix it, there is too much to do.”
“We don’t have time to think, we need results now.”
Reality - fix symptoms without regard to actual causes
Root Cause Analysis - structured and thorough review of problem designed to identify and verify what is causing the symptoms

3. Definitions
Cause (causal factor): a condition or event that results in an effect
Direct Cause: cause that directly resulted in the occurrence
Contributing Cause: a cause that contributed to the occurrence, but by itself would not have caused the occurrence
Root Cause: cause that, if corrected, would prevent recurrence of this and similar occurrences

4. How Is Root Cause Analysis Done?
Teams identify all possible causes
The actual root causes are identified and verified
Corrective action(s) are identified to reduce or eliminate the problem

5. Relationship between cause and effect
RCA Process
Relationship between cause and effect
Need for creative thought to identify all possible causes
Collect data about the problem
Analyze data
Verify causes

6. Root Cause Tools Cause and Effect Diagram
Scatter Diagram - prove cause-effect relationship
Control Chart - process stable?
Five Whys
Tree Diagram
Change Analysis
Barrier Analysis
Event and Causal Factor Analysis
Management Oversight & Risk Tree Analysis (MORT)

7. Cause Effect Diagram Visual display of possible causes
Cause categories include materials, machines, methods, and people
Reveals gaps in existing knowledge
Helps team reach common understanding of why loss exists

8. Cause Effect Diagram
Procedures
People
Problem
Equipment
Materials

9. Cause Effect Diagram Danger:
The Cause Effect Diagram is a list of potential root causes. This includes both probable causes, real causes and guesses.

10. After The Cause Effect Diagram
Identify likely candidates for root cause(s) by one of the following actions:
Look for causes that appear repeatedly within or across major cause or process categories
Look for changes or other sources of variation in the process or environment
Use consensus decision-making to select
Collect data to confirm a potential root cause as real

11. Scatter Diagram Test for possible cause and effect relationships
Some variation should be expected
Relationships being tested must be logical
Visual depiction of relationship

12. Patterns of Correlation
Quality Improvement Tools
Juran Institute, 1989

13. Correlation Coefficients
Quality Improvement Tools
Juran Institute, 1989

14. Scatter Diagram
Data shows strong positive
correlation.

15. Statistical Process Control
Process Variation - Common Cause & Special Cause
Is the process stable?
Points outside LCL/UCL warrant investigation
Alert for problems

16. Five Whys Describe the problem in specific terms
For each likely cause ask, “Why did this happen?”
Continue for a minimum of five times
Show logical relationship of each response to the one that preceded it
Stop when the team has enough information to identify the root cause

17. Tree Diagram State the problem
Causes are listed as branches to the right of the problem
Continue to clarify causes, drawing additional branches to the right
Repeat until each branch reaches its logical end

18. Schedule not communicated New trainer assigned late
Tree Diagram Example
Too much work
Not enough
students signed up
No reward
Schedule not communicated
No time
to learn
Trainer not
prepared
New trainer assigned late
Training
Class
Cancelled
Turnover
Flexibility
Materials not
completed
Changes up
to class date
Late changes
Current
Floating due date
Training Dept -
other projects
This project-
low priority
More info needed

19. Cautionary Note
“It’s impossible to solve significant problems using the same level of knowledge that created them!”
Albert Einstein

20. Cautionary Note - Part 2
Cause and effect analysis can’t get past existing knowledge - must have either observed (or considered) that the cause produced the effect in the past

21. Why not just ask “Why”?
Need to systematically organize and analyze data
First understand “What happened” then “Why”
Typically multiple root causes
Blame is an obstacle
Guidance needed to investigate human performance problems
Need to ask right questions to completely understand why
Some RCA techniques may provide easy answers that are either incomplete or wrong (but easy to find)

22. Event and Causal Factor Analysis
Used for multi-faceted problems or long, complex causal factor chains
Cause effect diagram that describes time sequence
Anything that shapes the outcome recorded
Identifies what questions to ask to follow path to root cause

23. Event and Causal Factor Analysis
Condition
Condition
Condition
Condition
Condition
Conditions that may
exist, but not identified
Condition
Condition
Condition
Found or existing state
that influences outcome
Event
Potential Event
Event
Event
Sequence of
happenings

25. Change Analysis Used when problem is obscure
Generally used for single occurrence
Focuses on things that have changed
Compares trouble-free process with occurrence to identify differences
Differences evaluated for contribution to occurrence

26. Analyze differences for Integrate information
Change Analysis Steps
Occurrence with
undesirable
consequence 1 5 4
Analyze differences for
effect on undesired
consequences
Identify
differences 3
Compare
Integrate information
relevant to the
causes of undesired
consequence
Comparable activity
without undesired
result 2 6

27. Change Analysis Steps Answer the following: What? When? Where? How?
Who?

28. Barrier Analysis
Systematic process to identify barriers or controls that could have prevented the occurrence
Physical
Administrative
Procedural
Determine why these barriers or controls failed
What is needed to prevent reoccurrence

29. Barrier Analysis Sequence of events: Barriers Analysis Start
Electricians
Follow
Procedure
System
Tagout
Tag
Hung
Electricians
Given Assignment
Reactor
Trip
Barriers Analysis
Tagout
Process
Step 1
Tagout
Process
Step 2
Communications
Process
Interface
Start
Procedure
Occurrence
Barrier
Holds
Barrier
Holds
Barrier
Holds
Barrier
Fails
Barrier
Fails
Barrier
Fails

30. Management Oversight and Risk Tree (MORT)
Used to prevent oversight in the identification of causal factors
Specific factors listed
Management factors that permit these factors to exist listed
Questions for each factor on the tree are included