quality management beyond the pmbok ® christopher e. maddox, pmp vice president, program management...
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Quality ManagementBeyond the PMBOK®
Christopher E. Maddox, PMP
Vice President, Program Management
Legacy Pharmaceuticals International
Project Management Institute Baltimore Chapter
20 January 2011This Presentation © 2011 Christopher E. Maddox. For use only by PMI members for non-profit educational purposes without express written consent of the copyright holder. Dilbert cartoons © United Features Syndicate and are used under Fair Use doctrine for educational purposes.
An Opening Thought
•Review Quality Management Definitions and Tools
•Quality and Risk•The Economics of Quality•Understanding Causes and Effects•Statistical Tool Cautions and Tips
Objectives
QUALITY“the degree to which a set of inherent
characteristics fulfill requirements”
GRADE“category assigned to products or services
having the same functional use but different technical characteristics”
Quality Management Definitions
PMBOK® Guide 4ed p190
WHICH IS HIGHER QUALITY?
Quality Management Definitions
Hyundai Accent Mercedes Brabus SL
WHICH IS HIGHER QUALITY?
Quality Management Definitions
“Zero to 60 in under 6 seconds”
WHICH IS HIGHER QUALITY?
Quality Management Definitions
“Better than 25 MPG”
QUALITY ASSURANCE“The process of auditing the quality requirements and the
results from quality control measurements to ensure appropriate quality standards and operational
definitions are used”
QUALITY CONTROL“The process of monitoring and recording results of
executing the quality activities to assess performance and recommend necessary changes”
Quality Management Definitions
PMBOK® Guide 4ed p189
•Cause and Effect Diagrams (Fishbone)•Control Charts•Flowcharting•Histogram•Pareto Chart•Run Chart•Scatter Diagram•Statistical Sampling•Inspection
PMBOK® Quality Tools and Techniques
• Quality management ALWAYS involves assessment of risk
• Risks to consider– Risk related to poor quality (scrap, recalls, reputation, liability,
etc)– Risk related to sampling/inspection error
• Complete elimination of risk is impractical in terms of time and cost; risk-based mitigation strategies are at the heart of effective QM
• Understanding risks is the first step towards prevention of quality problems
Quality and Risk
• Define Quality and Cost– Define Acceptable Quality Level– Define Cost of Quality and Risk/Cost of Poor Quality
• Acceptable Quality Level1. What are the user requirements / specifications?2. What is needed to meet them?
• Cost of Quality and Risk/Cost of Poor Quality1. What is the cost of compliance (process, QA, QC)?2. What is the cost and risk of poor quality (scrap, returns, etc)?
Quality, Risk and Cost
The Economics of Quality
95% 100%
QUALITY LEVEL - ACCEPTABLE WIDGETS
CO
ST
OF
PR
OC
ES
S /
QA
/ Q
CP
er 1
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$ 0
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The Economics of Quality
95% 100%
CO
ST
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ES
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/ Q
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QUALITY LEVEL - ACCEPTABLE WIDGETS
The Economics of Quality
95% 100%
CO
ST
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ES
S /
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/ Q
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er 1
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QUALITY LEVEL - ACCEPTABLE WIDGETS
POINT OF LOWEST COST
The Economics of Quality
95% 100%
CO
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/ Q
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QUALITY LEVEL - ACCEPTABLE WIDGETS
POINT OF LOWEST COST
(Risk Averse Case)
RISK
• Investing in Quality– FIRST invest in capable processes– NEXT invest in Quality Assurance– LAST invest in Quality Control
• Consider in your Risk Assessment…– Cost of lost customers– Cost of lost reputation– Cost of liability
• Accepting less than Six Sigma Quality may not be sufficient to mitigate your risks!
The Economics of Quality
So… what the heck is Six Sigma?
• A measure of process capability• The simple definition
– A process capable of producing not more than 3.4 defects per 1,000,000 opportunities
– That’s 99.9997% “Good”• The slightly-more-complex definition
– Acceptance range of the process is 3 standard deviations (SD, Sigma or σ) of the process’ normal distribution on either side of the desired specification point
Six Sigma Quality
Six Sigma Quality
NU
MB
ER
OF
OB
SE
RV
AT
ION
S
DEVIATION BELOW SPECIFICATION
DEVIATION ABOVE SPECIFICATION
Six Sigma Quality
NU
MB
ER
OF
OB
SE
RV
AT
ION
S
DEVIATION BELOW SPECIFICATION
DEVIATION ABOVE SPECIFICATION
“NORMAL” Distribution
Curve
Specification
Six Sigma Quality
NU
MB
ER
OF
OB
SE
RV
AT
ION
S
DEVIATION BELOW SPECIFICATION
DEVIATION ABOVE SPECIFICATION
ACCEPTANCE CRITERIA
Six Sigma Quality
NU
MB
ER
OF
OB
SE
RV
AT
ION
S
DEVIATION BELOW SPECIFICATION
DEVIATION ABOVE SPECIFICATION
1σ
2σ
3σ
99.9997%
68%
95%
NOT A SIX SIGMA PROCESS!
Conforming to Six Sigma
NU
MB
ER
OF
OB
SE
RV
AT
ION
S
DEVIATION BELOW SPECIFICATION
DEVIATION ABOVE SPECIFICATION
1σ
2σ
3σ
99.9997%
68%
95%
IMPROVE PROCESS CAPABILITY
Conforming to Six Sigma
NU
MB
ER
OF
OB
SE
RV
AT
ION
S
DEVIATION BELOW SPECIFICATION
DEVIATION ABOVE SPECIFICATION
1σ
2σ
3σ
99.9997%
68%
95%
WIDEN THE ACCEPTANCE RANGE
Causes and Effects of Quality Problems
• Ishikawa (Fishbone) Diagram– Featured in the PMBOK® - a basic tool of investigating defects– Qualitative but not quantitative– Does not always help determine causality
• Other Tools– Causal Circle explores cause-effect relationships of undesirable effects
(UDEs) – suited to complex systems– Failure Mode and Effect Analysis (FMEA) systematically analyzes and
prioritizes potential failures, consequences and preventative/corrective actions.
Cause and Effect of Quality Problems
Causal CircleUDEs (Tablet Compression Project)1. Tablet chipping2. Tablet hardness variation3. Coating is not uniform4. Tablets under weight5. Press force drifting during process6. Granulation density low7. Press process too slow8. Speed control past limit
1. List and Number UDEs
Causal Circle1
8 2
7
5
3
6 4
UDEs1. Tablet chipping2. Tablet hardness variation3. Coating is not uniform4. Tablets under weight5. Press force drifting during process6. Granulation density low7. Press process too slow8. Speed control past limit
2. Arrange numbers in circle
Causal Circle1
8 2
7
5
3
6 4
UDEs1. Tablet chipping2. Tablet hardness variation3. Coating is not uniform4. Tablets under weight5. Press force drifting during process6. Granulation density low7. Press process too slow8. Speed control past limit
3. Establish Relationship between UDE 1 and others
Causal Circle1
8 2
7
5
3
6 4
UDEs1. Tablet chipping2. Tablet hardness variation3. Coating is not uniform4. Tablets under weight5. Press force drifting during process6. Granulation density low7. Press process too slow8. Speed control past limit
4. Repeat for all UDEs
Causal Circle1
8 2
7
5
3
6 4
UDEs1. Tablet chipping2. Tablet hardness variation3. Coating is not uniform4. Tablets under weight5. Press force drifting during process6. Granulation density low7. Press process too slow8. Speed control past limit
5. Tabulate incoming and outgoing arrows for each
UDE IN OUT
1 5 1
2 3 3
3 3 0
4 4 1
5 2 3
6 0 5
7 0 1
8 1 4
Causal Circle1
8 2
7
5
3
6 4
UDEs1. Tablet chipping2. Tablet hardness variation3. Coating is not uniform4. Tablets under weight5. Press force drifting during process6. Granulation density low7. Press process too slow8. Speed control past limit
6. Identify drivers, outcomes, contributors
UDE IN OUT
1 5 1
2 3 3
3 3 0
4 4 1
5 2 3
6 0 5
7 0 1
8 1 4
D
D
O
O
O
C
C
DRIVER
DRIVER
DRIVER
OUTCOME
OUTCOME
OUTCOME
CONTRIBUTOR
CONTRIBUTOR
D
1. Study the system, product or process2. Brainstorm possible range of failure modes for each process step3. List potential consequences of each failure mode4. Assign Severity (SEV) scores for each failure mode5. Identify cause(s) of each failure mode6. Assign Occurrence probability (OCC) scores for each cause7. Identify controls to detect the failure modes8. Assign a detection escape (DET) score for each control9. Calculate Risk Priority Number (RPN) for each FMEA line [RPN = SEV x OCC x DET]10. Prioritize failure modes and causes based on RPN11. Determine actions to be taken on failure and plans for prevention12. Recalculate RPN based upon actions/plans and re-prioritize
Failure Mode and Effect Analysis
Failure Mode and Effect Analysis
Category 5 (Very Bad) 4 3 2 1 (Good)
Severity (SEV) Severe consequence of failure
High consequence Moderate consequence
Minor consequence Negligible consequence of
failure
Occurrence (OCC) Very high probability cause will occur
High probability Moderate probability Low probability Very low probability cause will occur
Escaped Detection (DET)
Very high probability failure will escape detection before
reaching the customer
High probability Moderate probability Low probability Very low probability failure will escape detection before
reaching the customer
Proc Step Failure Mode
Failure Effect
SEV
Cause OCC
Control DET
RPN
Action Plan pSEV
pOCC
pDET
pRPN
Matrix
Scoring
• Fishbone: Beware that correlation ≠ causality (use Causal Circle for complex systems)• Control Charts: Look for off-center trends; plot a distribution if you have enough data• Pareto Charts: Beware that all items must be a direct cause of the defect or you can
draw invalid conclusions• Scatter Plots: Do these in Excel and you can easily plot trend lines, derive formulas and
R-squared values• Statistical Sampling: Subject to errors; know how to calc margin of error so you can
create a valid sampling plan
PMBOK® Statistical Tool Cautions & Tips
• Understand what quality is, and who defines it• Good quality management is dependent on good risk management• Understanding economics of quality is a competitive advantage• Process capability is the most important factor in quality and usually the most cost
effective in the long run • Knowing cause, effect & failure mode is the only way to anticipate and investigate
failure and continuously improve• Understand what tools and statistics are telling you• Quality is profitable unless it is just a buzzword – then it costs!
Summary
Questions? Comments?
Thank You!Chris Maddox
[email protected]+1 443 243 2220
This Presentation © 2011 Christopher E. Maddox. For use only by PMI members for non-profit educational purposes without express written consent of the copyright holder. Dilbert cartoons © United Features Syndicate and are used under Fair Use doctrine for educational purposes.