improving performance using statistical...
TRANSCRIPT
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Improving Performance Using Statistical Thinking
MN ASQ Section 1203post-Dinner MeetingSeptember 14, 1999
presented by Robert MitchellChair, ASQ Statistics Division
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MISSIONPromote Statistical Thinking for quality and productivity improvement.
Serve ASQ, business, industry, academia, and government as a resource for effective use of Statistical Thinking for quality and productivity improvement.
Our primary customers are Statistics Division members.
Other key customers are:
Management
Users and potential users of Statistical Thinking
Educators of the above customersProvide a focal point within ASQ for application-driven development and effective use of new statistical methods.
Support the growth and development of ASQ Statistics Divisionmembers.
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VISION
Process Variation Data Improvement
Statistical Thinking
Philosophy ActionAnalysis
Statistical Methods
Statistical Thinking Everywhere
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DESIRED END STATE
Our members will be proud to be part of the Statistics Division
Our Division’s operations will be a model for other organizations.
We will be a widely influential authority on scientific approaches to quality and productivity improvement.
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PRINCIPLESOur customers’ needs will be continuously anticipated and met (i.e. Customer focused rather than customer driven).
Our market focus for products and services is weighted as follows:
Greatest weight on intermediate level
Nearly as much weight on basic level
Much less weight on advanced level.
Focus on a few key things.
Balance short-term and long-term efforts.
Value diversity (including geographical and occupational) of our membership.
Be proactive.
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Recognize that we exist for our customers.
View statistics from the broad perspective of quality management.
Apply Statistical Thinking ourselves; that is, practice what we preach.
Uphold professional ethics.
Continuously improve.
PRINCIPLES
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STRATEGY
Design and deliver selected useable products.
Have a strong and vibrant Division infrastructure.
Demonstrate the broad effectiveness of Statistical Thinking.
Integrate Statistical Thinking into educational curricula.
Develop a vibrant information communication system.
Influence key decision makers.
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Improving Performance Through Statistical Thinking
• Why ST is important?• What is ST?• How do you apply ST?• How to begin implementing ST
capability in an organization• Summary• Appendix - tools, case studies
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Definition
Statistical Thinking is a philosophy of learning and action based on the following fundamental principles:
All work occurs in a system of interconnected processes
Variation exists in all processes
Understanding and reducing variation are keys to success.
Glossary and Tables for Statistical Quality Control - Quality Press, 1996
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Evaluation Based on Past Experiences or Perceptions
We’ve always done it this way!
We work with what we get!
We do the best we can!
I never thought about it!
I’m so busy with the day to day troubles, I don’t have time to try that!
That has no effect on the finished product (or service)!
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Evaluation Based on Data
THE KEY IS TO ASK WHY!!!
Why is the material from the fabrication department machine so inconsistent?
Why do so we constantly firefight?
Why does our daily output vary so much?
Why does every job result in a monumental task that takes forever to complete?
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Definition
Statistical Thinking is a philosophy of learning and action based on the following fundamental principles:
All work occurs in a system of interconnected processes,
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FinishedGoods
or Services
Inputs Transformation Outputs
SuppliersInformation
Historical Data
Accounts PayableCar RepairBlending
Approvals
External Factors
- Materials - People
- Methods - Machines
- Environment - Measures
ProcessTransforms Inputs into Outputs
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Processes and Sub-Processes
CustomerCustomer Customer Customer
Sub-Process A
Sub-Process B
Sub-Process C
External Supplier
External Customer
Supplier Supplier Supplier Supplier
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Definition
Statistical Thinking is a philosophy of learning and action based on the following fundamental principles:
All work occurs in a system of interconnected processes
Variation exists in all processes
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Like it or not, variation is everywhere!
Know it, accept it, learn to deal with it!
Our drive time to work each day.
The quantity of production each shift.
Departure time of our plane.
Measurement system
………
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DefinitionDefinition
Statistical Thinking is a philosophy of learning and action based on the following fundamental principles:
All work occurs in a system of interconnected processes
Variation exists in all processes
Understanding and reducing variation are keys to success.
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Deming once said:“If I had to reduce my message for management to just a few words, I’d say it all had to do with reducing variation.”
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Variation and Targets
Variation can be thought of as:
1. Deviations around the overallaverage or
2. A deviation of the overall averagefrom a desired target.
Ave
TargetAve
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Reduced deviation around the Average and on Target
Voice ofProcess
Voice ofCustomer
Target
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Improvementusing
Statistical Thinking
Process Variation Data Improvement
Statistical Thinking Statistical Methods
Philosophy Analysis Action
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Pitfall
Valuing only quantitative data
Qualitative data are just as important.
Example: Idea data!!
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Benefits of Statistical Thinking
Provides a theory and methodology for improvement:
Helps identify where improvement is needed.
Provides a general approach to take.
Suggests tools to use.
A complete improvement approach includes all elements of Statistical Thinking:
Process - Variation - Data
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Check Act
Do Plan
CheckAssess major problems and root causesDefine the scope of the projectIdentify the people who will be affected by the project
DoImplement the plan.Assure continued process performance.
ActFix the obvious.Decide how to approach the issue or problem.
PlanSet project goals and expectations.Develop the project plan.
CAPDo DiagnosticTips for Statistical Thinking
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Use of Statistical ThinkingDepends on levels of activity and job responsibility.
Where we're headed
Systems & processesto guide us
Where the work gets done
Strategic
Managerial
Operational
Executives
Managers
Workers
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Process
SuppliersInputs
ProcessOutputs
Customers
S I P O C
A series of activities that converts inputs into outputs
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Understand Customer Needs
Customer Requirements
Process / Product Flow
EndUserReq..
Substitute Tech. Char.
Mfg. Tests
Product Planning Matrix
Converting
Coating
Extruding
DataPackage
Matrix
Qualification Matrix
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Examples of Operational Processes
ManufacturingOrder EntryDeliveryDistributionBillingCollectionService
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Examples of Statistical Thinking at the Operational Level
Work processes are flowcharted and documentedKey measurements are identified.
Time series plots displayed
Process management and improvement utilize:Knowledge of variation, andData
Improvement activities focus on the process, not blaming employees.
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Examples of Managerial Processes
1. Employee Selection2. Training and
Development3. Performance
Management (including coaching)
4. Recognition and Reward
5. Budgeting
6. Setting Objectives and Goals
7. Project Management
8. Communications9. Management
Reporting10. Planning
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Examples of Managerial Processes
Objectives & Goals
Planning
Budgeting
ManagementReporting
Core Business Processes
Customers
EmployeeSelection
Training &Development
Recognition& RewardsPerformance
Management
Communication
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Examples of Statistical Thinking at the Managerial Level
.
Managers use meeting management techniquesStandardized project management systems are in place.Both project process and results are reviewed.Process variation is considered when setting goals.Measurement is viewed as a process.The number of suppliers is reducedA variety of communication media are used.
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Examples of Strategic Processes
Strategic Plan DevelopmentStrategic Plan DeploymentAcquisitionsCorporate Budget DevelopmentCommunications - Internal and ExternalSuccession Planning and DeploymentOrganizational Improvement
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Examples of Statistical Thinkingat the Strategic Level
Executives use systems approach.Core processes have been flow chartedStrategic direction defined and deployed.Measurement systems in place (i.e. BSC).Employee, customer, and benchmarking studies are used to drive improvement.Experimentation is encouraged.Learning is valued.
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Robustness - An Underused Concept
Key aspect of Statistical ThinkingReduce the effects of uncontrollable variation in:
Product designProcess designManagement practices
Anticipate variation and reduce its effects
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Robustness of Product and Process Design
A third way to reduce variationAnticipate variation
Design the process or product to be insensitive to variation
A robust process or product is more likely to perform as expected
Improved reliability
100% inspection cannot provide robustness
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Robust Products are Designed in Anticipation of Customer Use
Unintended UseWashing machine topsCraftsman tools
User-friendly computers and softwareLow-maintenance automobiles5 mph bumpersMedical instruments for home use
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Product and Process Robustness
Product Performance is insensitive to variations in conditions of manufacture, distribution, use and disposal.
Process Performance is insensitive to uncontrollable variation in process
InputsTransformations - activities - stepsExternal factors
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Robustness in Management
Develop strategies that are insensitive to economic trends and cycles
Scenario Planning
Design a project system that is insensitive to Personnel changesChanges in project scopeVariations in business conditions
Respond to differing employee needsAdopt flexible work hoursProvide “cafeteria” benefits package
More ...
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Robustness in Management(Continued)
Enable personnel to adapt to changing business needs
High Performance Organization (HPO)Change Acceleration Process (CAP)
Technological AcceptanceCultural Acceptance
Ensure meeting effectiveness is not dependent on facilities, equipment, or participants
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Understanding Human Behavior
Different people have different methods and styles of working, learning and thinking Different people take in, process and communicate information in different waysPeople vary --- they are different:
Day to dayPerson to personGroup to groupSite to siteOrganization to organization
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Process Robustness Analysis
Identify Those Uncontrollable Factors that Affect Process Performance
WeatherCustomer Use of ProductsEmployee Knowledge, Skills, Experience, Work HabitAge of Equipment
Design the Process to be Insensitive to the Uncontrollable Variations in the Factors
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Three Ways to Reduce Variation and Improve Quality
Control the Process:Eliminate SpecialCause Variation
Improve the System:Reduce Common Cause Variation
Anticipate Variation:Design RobustProcesses and Products
Quality Improvement
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Tips for Statistical Thinking
Start with the customer.Identify customer requirements and expectations. Identify market trends.
Start small.Pick a process that is not very detailed and does not involve many functions or work groups. Small “wins” build confidence and teamwork. Share successes; celebrate failures.
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Tips for Statistical Thinking
• Flow Diagram• Pareto Charts• Cause & Effect • Histograms• Run Charts• Control Charts• Scatter Diagram
• Affinity Diagram• InterRelationship
Diagram• Tree Diagram• Prioritization Matrices• Matrix Charts• Arrow Diagram• Process Decision
Program Chart
7 Quality Tools 7 Management Tools
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3 Types of Variation
Special Cause Common Cause Structural
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Identify Process State
Process StatesIdeal State
Process in Control
100% Conforming Product
Maintain Control
Threshold StateProcess in Control
NonConformance
Change process or specs
Sort
State of Chaos
Out of Control
Out of Spec
Eliminate Special Causes
Brink of Chaos
Out of Control
100% Conforming
Investigate Special Causes
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Tips for Statistical Thinking
If a process or system is not stable -- showing signs of Special Cause …
Use the tools of problem-solving to identify the root cause. Try to identify exactly when, where, how, and why the process changed.
If a Special Cause hurts the process, develop procedures to eliminate the return of the problem. If a Special Cause is beneficial, develop procedures to make it a permanent part of the process.
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Tips for Statistical Thinking
If a process or system is stable -- showing only Common Causes of variation…
Use the tools of improvement to study all the data (not just the “good” or the “bad” points) and identify factors that cause variation. Determine what needs to be permanently changed to achieve a different level of quality.
Stratify the process - sort the data into groupsDisagregate the process - divide the process into its sub-
processes
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RequestedRequestedQualityQuality
ExpectedExpectedQualityQuality
Not FulfilledNot Fulfilled
FulfilledFulfilled
Not Not SatisfiedSatisfied
SatisfieSatisfiedd
Kano Model of QualityKano Model of Quality
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1. Demonstrate the Broad Application of Statistical Thinking D1Collect new case studies; Market Statistical ThinkingExpand the theory of Statistical Thinking
• Assist in the discovery process for new applications• Maintain the integrity of ST (license and trademark)• Publish new series, “Improving Processes…”
2. Integrate Statistical Thinking into Education & Training B2Pilot the “Pegasus” charter school project (Dallas, TX)
• PDCA the process; repeat with new school principals
3. Develop a Vibrant Information & Communication System A2Develop and implement a member nurturing processCreate and staff the Section Liaison position
• Develop a WebPages policy and e-commerce strategy
4. Design & Deliver Selected Useable Products B5Develop and disseminate Newsletter technical contentCreate a Clearinghouse of Statistical Stuff
• Beef-up our Short Course offerings; more variety; regional• Identify and start no more than 3 new publications
5. Have a Strong and Vibrant Division Infrastructure C3Division organization re-alignment; change By-Laws
• Develop a Division “Balanced Scorecard”
Statistical Thinking Everywhere1999 - 2000 STAT Tactics
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Statistical Thinking Everywhereread more about it...
“Statistical Thinking” Special Publication (Spring 1996)“Data Sanity” Special Publication (Summer 1998)
available through QIC 1-800-248-1946 or [email protected]
“How to Teach Others to Apply Statistical Thinking”Quality Progress, June 1997, pg. 67 - 79
“Improving Performance through Statistical Thinking”ASQ Quality Press available November 1999