Quality in the past was more related conforming to requirements, in lot of cases as it relates to engineering requirements and not necessarily enthusiastic customer experience. It was a very narrow definition of quality and focused more on Things Gone Wrong. Goal was to reach a level of customer accepted.
Quality definition today is much broader and winning in quality in this highly competitive environment requires deployment game changing quality strategies.
We will discuss how to infuse the voice of the customer into the way we design our products and services so that they exceed customer expectations. Organizations that engage all functions within enterprise and are customer centric will differentiate themselves from the rest of the competition. This presentation will provide an integrated roadmap on how to integrate proactive quality strategies such as Design for Six Sigma (DFSS), Advanced Product Quality Planning (APQP), Design Failure Modes and Effects Analysis (DFMEA), Process Failure Modes and Effects Analysis (PFMEA) along with reactive strategies such as Six Sigma and control plans to achieve organizational excellence.
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Game Changing Quality Strategies that Drive Organizational Excellence
1. Game Changing Quality Strategies
that Drive Organizational Excellence
Kush K. Shah
ASQ Fellow, GM Technical Fellow
Six Sigma MBB, Shainin Red X Master
ASQ – CMQ/OE, CSSBB, CQE, CQA, CBA
September 15, 2016
2. What Did Quality Mean in the Past?
• Focus on parts:
– Conformance to requirements
– Defects / deficiencies
– Within specifications
• The Goal was customer acceptance
3. What Does Quality Mean Today?
• Today, the Customer assumes all parts will work as a given
• Less than 50% of issues reported by the customer are hard
failures
• The Goal is to surpass customer expectations without
unpleasant surprises
4. What is Organizational Excellence?
What does Organizational Excellence mean to you?
ASQ Definition: Organizational excellence refers to ongoing efforts to
establish an internal framework of standards and processes intended
to engage and motivate employees to deliver products and services
that fulfill customer requirements within business expectations.
5. Game Changing Strategies
1. Customer-Centered Approach to Quality
2. Enterprisewide Engagement
3. Disciplined Problem Solving
4. Risk Management
5. Integrated Approach to Data Analytics
6. Closed Loop Learning
7. Innovation
6. 1. Customer-Centric Approach to Quality
Customer’s Perception of Quality
• Things Gone Wrong (QRD)
– Covered under warranty period - responsiveness and degree of
resolution
– Not covered under warranty period – out of pocket cost
• Features:
– Inconvenience and discomfort - inappropriate design
– Likes and dislikes - information to the customer after purchase
“There is only one boss. The customer.
And he can fire everybody in the
company from the chairman on down,
simply by spending his money
somewhere else.”
– Sam Walton
7. 1. Customer-Centric Approach to Quality
Styling
Ease of Use
Driving &
Handling
Features
Reliability
Safety
Customer
Service
Customer
8. 1. Customer-Centric Approach to Quality
Types of Customers:
• Fully Engaged – Strongly attached and loyal. Your most valuable
customers
• Engaged – Beginnings of emotional attachment but not strong
• Not Engaged – Emotionally and attitudinally neutral
• Actively Disengaged – Active emotional detachment and antagonist
Source:
Gallup
9. “House
of Quality”
RELATIONSHIP
MATRIX – Between
What and How
WHAT
HOW
target valuesHOW MUCH
CORRELATION
BENCHMARK
1. Customer-Centric Approach to Quality –
Quality Tools
(Attractive
Quality)
(One-Dimensional
Quality)
(Must-Be Quality)
Kano Model
11. 2. Enterprisewide Engagement
Mission
Vision
Strategic Objectives
Tactical Objectives
Measures
Why we exist
What we want to be
Indicators and
Monitors of success
Desired level of
performance and timelines
Planned Actions to
Achieve Objectives
O1 O2
AI1 AI2 AI3
M1 M2 M3
T1 T1 T1
Specific outcomes expressed in
measurable terms (NOT activities)
Strategic Plan
Action Plans
Evaluate Progress
Targets
Initiatives
What we must achieve to be successful
13. 3. Disciplined Problem Solving
• Definition of Problem: Anything that deviates from what is expected
or desired.
• Problem Solving Options?
– Try Something and Wait
– Do What Has Been Done in the Past
– Find an Expert and do what we’re told
– Brainstorm
– Have a Meeting and Vote
– Change the Design
– Attribute It to Normal Variation
– Assign a Task Force
– Do a Deep Dive
– Don’t Tell Anyone
– Blame a Supplier
– Do Nothing
15. Improve
Robustness
Common
Cause
Variation
Special
Cause
Variation
Transactional
Six Sigma
Reduce Variation /
Defects
Purpose
Improve Flow
Reduce Waste
Improve Product /
Process Design
Business
Processes
Manufacturing
/ Engineering
Six Sigma
Lean
Reduce
Risk
Disclaimer: Tools from different techniques can be used (integrated) on a
single project so the purpose of this chart is not to silo different techniques
but to help on identifying more prominent approach for the type of project.
3. Disciplined Problem Solving
Shainin Red X DFSS FMEA
17. 4. Risk Management
• Risk Identification
– Identification significant risks based on organization’s risk appetite
• Risk Analysis
– Measure risks consistently with respect to enterprise objectives
– Prioritization and quantification
– Assignment of specific responsibility for controls to mitigate risks
• Risk Response
– Scenario development
– Action Plan Implementation
• Risk Control
– Hold the gains through monitoring and controls
18. • Introduction - risk-based thinking is explained
• Clause 4 - organization is required to address the risks and
opportunities wrt QMS processes
• Clause 5 – top management is required to promote awareness of
risk-based thinking and determine and address risks and
opportunities that can affect product /service conformity
• Clause 6 - organization is required to identify risks and
opportunities related to QMS performance and take appropriate
actions to address them
• Clause 9 - organization is required to analyse and evaluate
effectiveness of actions taken to address risks and opportunities
• Clause 10 - organization is required to correct, prevent or reduce
undesired effects and improve the QMS and update risks and
opportunities
18
4. Risk Management – ISO 9001: 2015
19. 4. Risk Management – Quality Tools
System
FMEA
Design
FMEA
Process
FMEA
Subsystems
Main Systems
Components
Manpower
Machine
Method
Material
Measurement
Environment
Design’s impact
on Manufacturing
System’s impact
on Component
Manufacturing’s
impact on Design
Component’s
impact on System
DFSS
Control
Plan
20. PROACTIVE APPROACH
Problem Prevention:
High Leverage
Low Visibility
Low Cost
Customer Enthusiasm
Difficult to Measure Performance
REACTIVE APPROACH
Problem Solving:
Low Leverage
High Visibility
High Cost
Customer Dissatisfaction
Easy to Measure Performance
Where are your organization’s resources focused?
Organizations that are
always putting out fires
will eventually get
burned.
4. Risk Management – Proactive vs. Reactive
21. 5. Integrated Approach to Data Analytics
• 89% of US Businesses are investing in data and data analytics and
41% claim that their systems cannot make sense of large volumes of
data from different sources
• Expanding data:
– Data Volume
– Data Variety
– Data Velocity
• Types of business data – Sales, Marketing, Operational, Quality,
Service, HR
• Factors to be Considered in Big Data Analysis:
– Automation - Analysis and complex computations
– Reproducibility - Analysis results can be reproduced
– Flexibility - Data repository can organically expand & extend
– Robustness - Less error prone
22. 5. Integrated Approach to Data Analytics
• Neither Time or Miles analysis could highlight the underlying failure
mechanism
• Customers opt in to send OEMs hundreds Gb of engineering log data
per day from thousands of vehicles
• Advantages of Big Data Analytics:
– Enable data-driven decision making in field reliability
– Faster decisions made with higher confidence
– Higher impact on service decision
– Higher influence on design targets and testing specs for next
generation vehicles
Automotive Example - Sunroof
Source: 2014 ARS, North America, Indianapolis
- Better Field Reliability with Big Data Analytics -
Georgios Sarakakis, Jason Shiverick, Carlo
Torniai, Tesla Motors
24. Closed loop learning is not frequent improvement
When we re-invent for
each generation of
product
Time
Closed loop learning
means building on past
accomplishment and its
learning to achieve a new
height.
6. Closed Loop Learning
25. 6. Closed Loop Learning
Time
Less Variation
Shorter Spike
Duration
Better Starting Point
Steeper Slope Aggressive Remediation
Quality
Planning
Quality
Control
Quality
Improvement
ProblemsExperienced
Innovation
Disciplined Execution
Closed Loop Learning
Enterprise Engagement
Benchmark
Start of
Production
26. 7. Innovation
Top Innovation Factors in an Organization:
• Culture (employee attitudes & participation)
• Senior Leadership Support (risk/long-term results)
• Capabilities (workforce talent, training, & experience)
• Strategy (alignment to profitable growth & business goals)
• Process (effective methods & tools)
“Research is the transformation of money into knowledge.
Innovation is the transformation of knowledge into money.”
Dr. Geoffrey Nicholson, 3M
(inventor of the Post-It note)
Innovation is the successful conversion of new concepts and knowledge
into products and processes that deliver new customer value in the
marketplace
Innovation and Value Creation Technical Committee, 2009
28. • Genrich S. Altshuller - the Father of TRIZ
• Leading to 3 key discoveries:
1. Problems and solutions were repeated across industries and
sciences
2. Patterns of technical evolution were repeated across industries
and sciences
3. Innovations used scientific effects outside the field where they
were developed
>200,000 Patents
~1,250
typical
system
conflicts
~40
techniques
for overcoming
system conflicts
7. Innovation – TRIZ Overview
29. 7. Innovation – TRIZ Overview
Trade-off Contradiction Example:
• Number of features of a product increases, power use gets worse
• Number of features of a product increases, size gets worse
• Diversity of services provided to customers gets better, but amount of
training required gets worse
Ideality = S Benefits / (S Costs + S Harm)
30. 7. Innovation
• What functions do I deliver to my customer?
• How can I improve usefulness of my function?
• Do I need the current product / process for that?
• How efficient is my current product / process really?
Operational questions
31. Summary – Game Changing Strategies
1. Customer-Centered Approach to Quality
2. Enterprisewide Engagement
3. Disciplined Problem Solving
4. Risk Management
5. Integrated Approach to Data Analytics
6. Closed Loop Learning
7. Innovation
