cqi$learning$lunch$ understanding variation predicting ... · cqi$academy$of$quality$fundamentals$...

CQI Learning Lunch Understanding Variation

Predicting Your System’s Performance

July 10, 2013 CQI Preview -‐ 9:00 AM to 10:00 AM – Dial-‐In

Capital Quality & Innovation Audio Bridge - Conference Access 1-567-314-9082

Conference Passcode 734 254 9433

Learning Lunch -‐ 10:30 AM to 1:00 PM – In Person University Club of Michigan State

3435 Forest Road, Lansing, MI 48909 517-‐353-‐5111

2013 -‐ SPONSORS

Dennis Sergent 517-‐285-‐5500 [email protected] 4/15/13 -‐ Higher Quality -‐ Lower Costs -‐ BeJer Workplaces -‐

2013 CQI Programs

3

Excellent

•  Jan 7 -‐ Learning Lunch @ 10:30 AM * –  Idealized Design – StarQng Over With A Clean Sheet of Paper

•  JANUARY 23 -‐ CQI BREAKFAST PROGRAM @7:30 AM –  Jim Link – Ideas and Links

•  Feb 12 -‐ Learning Lunch @ 10:30 AM * –  Cultural Influences on Change

•  Mar 11 -‐ Learning Lunch @ 10:30 AM * –  Understanding a Theory of Knowledge – How We Know What We Know

•  MARCH 28 -‐ CQI BREAKFAST PROGRAM @7:30 AM –  BernadeJe Johnson -‐ Title To Be Announced

•  Apr 9 -‐ Learning Lunch @ 10:30 AM * –  New Neuroscience and Impacts on Thinking

•  May 13 -‐ Learning Lunch @ 10:30 AM * –  Systems -‐ How We Define Them, Is Everything

•  MAY 29, CQI BREAKFAST PROGRAM @7:30 AM –  SOAR TO NEW HEIGHTS WITH APPRECIATIVE INQUIRY -‐ John Victory -‐

•  Jun 11 -‐ Learning Lunch @ 10:30 AM * –  Customers and Understanding Their Voice

SPRING 2013 -‐ CQI ACADEMY •  March 13 -‐ IntroducYon to Quality •  March 27 -‐ Voice of the Customer •  April 10 -‐ Systems Thinking •  April 24 -‐ Understanding VariaYon •  May 8 -‐ Psychology •  May 22 -‐ Capstone Project PresentaYons

•  CQI PREVIEWS ARE SCHEDULED @ 9:00 AM – Every Learning Lunch Morning These are audio conferences on the topic of each month’s Learning Lunch!

•  Jul 10 -‐ Learning Lunch @ 10:30 AM * –  Understanding VariaQon

•  JULY -‐ CQI BREAKFAST PROGRAM @7:30 AM –  QUALITY IN GOVERNMENT -‐To Be Rescheduled to October

•  Aug 14-‐ Learning Lunch @ 10:30 AM * –  Analyzing Performance in Systems

•  SEPTEMBER -‐ CQI BREAKFAST PROGRAM @7:30 AM –  QUALITY IN EDUCATION

•  Sep 9 -‐ Learning Lunch @ 10:30 AM * –  New Learning Systems

•  Oct 10 -‐ Learning Lunch @ 10:30 AM * –  Asking Smart QuesQons

•  NOVEMBER -‐ CQI BREAKFAST PROGRAM – Date TBD –  THE NEW ECONOMICS of QUALITY in INDUSTRY

•  Nov 12 -‐ Learning Lunch @ 10:30 AM * –  Understanding Psychology in OrganizaQons

•  Dec 9-‐ Learning Lunch @ 10:30 AM * –  PredicQon -‐ Problems or SoluQons?

FALL 2013 -‐ CQI ACADEMY •  September 11 -‐ IntroducYon to Quality •  September 25 -‐ Voice of the Customer •  October 9 -‐ Systems Thinking •  October 23 -‐ Understanding VariaYon •  November 6 -‐ Psychology •  November 20 -‐ Capstone Project PresentaYons


CQI Academy of Quality Fundamentals

4

Excellent

CQI QUALITY, INNOVATION & LEADERSHIP FUNDAMENTALS -‐ AIM •  Teach the fundamentals of quality systems, including quality

management, conFnuous improvement, innovaFon and leadership exemplified in the System of Profound Knowledge.

•  Learn how these principles, pracFces and tools make a significant, posiFve difference in your professional lives and the organizaFons you work in.

•  Provide a foundaFon for any person or organizaFon that desires to be a leader in quality and innovaFon.

COST •  The cost is $2400 for the public and is $1800 for CQI members. MulFple

seat pricing is available if you send more than one person. The cost includes all required workshop materials with refreshments, conFnental breakfast, lunch and snacks each aWernoon throughout each of the six days. Also included in the price are pre-‐course assessments and assignments accessible via the web, plus a flash drive with all course content. Parking is free and lodging is available nearby, at an added cost with no markup.

•  Individual, one-‐day sessions of the academy are available by special request and are $900 per person for the public and $600 for CQI members with a class of 24 parFcipants minimum.

APPROACH •  We engage the learner in their own learning, coordinated with your

organizaFon’s leadership. We use accelerated learning/adult learning principles and pracFces in pre-‐course readings, in workshop dialogue, individual and team exercises, plus homework in interim weeks.

•  We also make our instructors available to learners and your leadership through coached team calls and provide on call advice to parFcipants for their projects.

•  Once we have a minimum of twelve (12) and up to forty-‐eight (48) parFcipants, we send out pre-‐course assessments of learning needs with the pre-‐course assignments.

•  When your individual assessments are returned, we set a joint conference call with the learners and their leaders to develop a capstone project for each parFcipant.

•  On the last day of the academy, the learners will make a presentaFon to your management, customers or both about what you will do with your learning.

•  AWer the academy, we follow-‐up with the cohort members and their leaders or customers, to see how well they use what they have learned.

•  At the conclusion of the Academy, the parFcipants and their leaders will also be asked to confirm their post-‐academy assessment and receive a monthly Fme window to call into a regularly scheduled conference bridge to stay connected to their class.

+ We have scheduled 6 dates in Spring 2013, 6 more in Fall 2013 and six in Spring 2014 + Contact Dennis or Adrian if you want more informaYon

Day 1 -‐ IntroducYon to Quality Day 2 -‐ Voice of the Customer Day 3 -‐ Systems Thinking Day 4 -‐ Understanding VariaYon Day 5 -‐ Psychology Day 6 -‐ Capstone Projects

6 Tuesdays, Wednesdays, or Thursdays, 2 weeks apart

-‐ 8:30 AM to 5:00 PM Located in the Lansing area, can be brought to your locaYon


An IntroducYon to Learning Lunch

•  Learning, not training –  This is about you, not the facilitator

•  Dialogue, not a lecture –  We will facilitate the dialogue about the subject

•  We will not read the slides to you –  We will use the handouts as a point of reference

•  You do not need to read the slides –  But it might help you learn more if the subject macers to you

•  Part of an Emerging TransformaYon of Quality –  Management Development – Philosophy, Principles & PracFces –  Professional, Quality Management Fundamentals –  Excellent OperaFons & Methods –  Profound Knowledge

•  Theory of Knowledge

•  Systems

•  VariaFon •  Psychology


Today’s Dialogue

•  Our Thesis –  the VariaYon in your system will help you predict performance

•  IF we listen, the process talks to us –  through variaYon mapped on control charts

•  Today we discuss how knowledge about variaYon reveals great wisdom –  Control Charts and Process Capability studies are a founda5on –  AT&T – Western Electric work with Sta5s5cal Quality Control –  Don Wheeler’s work –  Deming’s System Model & PDSA

•  We will discuss OUR OWN evidence of the voice of the process! –  We build on the trail blazed by giants of knowledge –  An opportunity to act with knowledge

•  Managing, Leading and Transforming Our Workplaces

•  Share Your Thinking with others in dialogue


CriYcal Resources

•  Circling Back – Clearing Up the Myths about The Deming Cycle and How It Keeps Evolving –  Ronald D. Moen and Clifford L. Norman (PDF ArFcle)

•  Design & Control of Quality –  Ian Bradbury (PDF PresentaFon)

•  The New Economics, 2nd EdiQon and Out of the Crisis –  W. Edwards Deming

•  Some Theory of Sampling –  W. Edwards Deming

•  StaQsQcal Method from the Viewpoint of Quality Control –  Walter A. Shewhart

•  StaQsQcal Quality Control Handbook –  Western Electric, AT&T Bell Telephone Laboratories -‐1956, and ediFons 1958, 1964, 1967, 1970,

1977, 1982, 1983(2), 1984(2), 1985

•  What is Total Quality Control? The Japanese Way –  Kaoru Ishikawa


AT&T – Western Electric Work with Quality Control

StaQsQcal Quality Control Handbook •  Wricen in non-‐technical language •  A descripFon of procedures to preserve essenFal features of

quality control •  Compendium of techniques and methods •  Used in all types of industry since the 1920’s

–  Developed on the work by Dr. Walter Shewhart •  W. Edwards Deming was his intern at Hawthorne Works

•  Most disFncFve features –  Emphasis on operaFons and engineering rather than inspecFon –  Emphasis on the control chart as the foundaFon


IntroducYon to StaYsYcal Quality Control

•  OperaFonal DefiniFons – StaFsFcal

• With the help of numbers

– Quality • We study the characterisQcs of our process

– Control •  In order to make it behave the way we want it to

– Process •  A set or system of condiFons or causes which work together to produce a given results


EssenYal Techniques & Methods

•  Process Capability Study –  Used by managers, engineers to obtain informaFon about how a

process behaves

•  Process Control Charts –  Used in process, on the shop floor to increase yields, cut down waste

and repair and “help the people to do beJer work”

•  StaFsFcal Sampling InspecFon –  Used by inspectors as scienFfic basis for accepFng product or service

•  Design of Experiments –  Used in R&D to study the effect of many variables at once


IntroducYon to VariaYon

•  FluctuaFng pacerns in data always exhibit variaFon •  In any series of events or manufacturing or service or government or educaFon, even entertainments and sciences –  With natural events too, such as acendance, health, populaFon, temperature, barometric pressure, precipitaFon, anything physical as well as anything mental such as the psychological reacFons of people

•  Instead of always being the same from point to point in Fme, the numbers vary


Exercise in VariaYon

•  Write this lecer “A” alongside the examples below: !A!A!A!A!A!A!!•  Are they each the same?

•  Try wriFng your own first name the same next to each “A”!–  Are all six of them idenQcal?


What Causes VariaYon?

•  FluctuaFng pacerns in data are caused by a large number of minute variaFons gathered –  Most differences are very small and fluctuate in a normal or natural

pajern

•  Occasionally there are larger differences more important than all other differences combined –  These larger causes make the pacern fluctuate in an unnatural or

abnormal manner

•  Experience shows the definite detectable differences between natural and unnatural pacerns –  Discoverable differences allow us to study these differences and

discover the causes


Unnatural Pajerns

•  Detectable differences between natural and unnatural pacerns allow us to study the signals and discover the causes –  The data make it possible to study the differences by well-‐known,

staFsFcal laws

•  DistribuFons of Data within the process studied fluctuate, yet they are grouped around a central value with scaJer on either side of it

•  These fluctuaQons become more definite as the number of measurements or observaFons increase.

•  IF the cause system is constant, the distribuFon approaches a staFsFcal limit -‐ a sort of “natural law” – and for the process this becomes a way to predict behavior in the system


StaYsYcal Phenomena

•  DistribuFons and fluctuaFons are not separate and unrelated

–  DistribuQons are a composite of the fluctuaFons

–  FluctuaQons are confined within the distribuFon

–  StaQsQcal limits from distribuQons can be used to predict behavior of a fluctuaFng pacern

•  When there are no abnormal causes


Everyday Language

•  Everything varies •  Individual things are unpredictable •  Groups of things from a constant system of causes tend to be predictable •  Examples from Shewhart’s work in Bell Labs and US Dept. of Agriculture Example 1

a.  People live to different ages b.  No one knows how long they will live c.  Insurance companies can tell with great accuracy what percentage of people live to

age 60, 65, 70, etc. Example 2

a.  You cannot write the lecer “A” twice the same way b.  You have no way of knowing how your next “A” will differ from the last c.  There is sFll something about your lecers that is the same as the others and

something about them that is different than mine Example 3

a.  All pacerns fluctuate b.  The individual points are unpredictable c.  A group or series of points from a constant process will tend to follow

a pacern that obeys a fixed law


Process Control Charts

•  Used in process, on the shop floor to increase yields, cut down waste and repair and “help people to do becer work” –  One of the most sensiFve devices known for analyzing data and obtaining

informaFon

•  To find the limits, we start with the process measurements and data over Fme to create an average –  Depicted as a solid line above the numbers

•  The central line or base line is determined over Fme –  This defines a fluctuaFng pacern

•  We add staFsFcal limits or “control limits” at 3 sigma –  Depicted as doced lines added to the fluctuaFng pacern average –  This results in a control chart –  Which we use to track actual performance and predict future performance

•  To interpret data correctly, put it in a control chart


Experience is the Basis of Confidence

•  No one has to accept the evidence of control charts on faith •  Look at the data

•  It is always possible to invesFgate whether the chart is correct •  When large numbers of people act in accordance with control charts, addressing

the un-‐natural variaFon, certain remarkable results occur •  Costs are reduced •  Quality and yields improve rapidly •  There are major reducFons in waste, scrap, rework, and inspecFon •  Engineers understand their process knowledge increasing •  Workers stress and frustraFon is reduced •  Experiments are faster and more successful •  Difficult problems with specificaFons and requirements are solved easily and

economically –  All of this is evidence of the reliability of control charts


Example #1 – PredicYons v. Actual

•  Bags of M&M in CQI Academy Exercise – PredicFons versus Actual –  This is some evidence of the reliability of control charts

•  ASK YOURSELF IF THIS PROCESS IS IN CONTROL? WHAT DO YOU THINK?


Example #2 – X and R Chart

•  Bags of M&M in CQI Academy Exercise – Actuals compared to three values •  A Central line of the averaged values or X-‐Bar •  An Upper Control Limit or UCL •  A Lower Control Limit or LCL –  This is evidence of the power of control charts

•  THERE IS NOTHING YOU SHOULD DO – THIS PROCESS IS IN CONTROL, With Only Natural VariaQon


Principal Kinds of Control Charts

•  Most common kinds of data in order of sensiFvity 1.  Ranges 2.  Averages 3.  Percentages or counts 4.  Individual Numbers

•  Types of Control Charts 1.   R or Range -‐ of samples

–  Difference between highest and lowest in small groups of measurements

2.   X or X-‐Bar -‐ Average of samples –  Samples of small groups

3.   X and R Charts -‐ Average and Range Charts –  Most sensiYve chart to trace and idenFfy causes

4.   P-‐Charts or Percentage -‐ Percentages or acributes –  OWen represents the percent defecFve, second most sensiYve

5.   Moving Range –  Less sensiYve than X and R Charts, less sensiYve than P-‐Charts


Process Capability Studies

•  Used by managers, engineers to obtain informaFon about how a process behaves

•  TheoreFcal basis depicted at right

•  EssenFal points for management: •  IniFal variaFon is expected and normal •  Results from normal variaFon in people,

materials, methods, tools, machines and other process elements

•  Unnatural variaFon can be changed or corrected

•  If capability studies have not been made before, unnatural variaFon is likely to be the greatest part of the total

Total VariaYon in the Process

Natural VariaYon This, we must live with

Unnatural VariaYon This, we do not have to

live with

The Capability Study shows what causes unnatural variaYon and what must be

done to get it out of the process

When unnatural variaYon is eliminated, we have the true process

capability.


EvoluYon of ScienYfic Method & PDSA Cycle

•  PDCA = plan-‐do-‐study-‐act •  PDSA = plan-‐do-‐study-‐act •  QC = quality control •  TQC = total quality control

PragmaYsm Charles Pierce & William James

Modern Science Galileo

IntegraYon of PragmaYsm & Empiricism C. I. Lewis

Shewhart Cycle Walter

Shewhart

Deming Wheel W. Edwards Deming

Shewhart Cycle Deming

PDSA Deming

How We Think John Dewey

InducYve Learning

Francis Bacon

PDCA Japanese QCs

PDCA Kaoru Ishikawa

TQC

Ron Moen’s article* in the Quality Progress” magazine in November 2010 with Cliff Norman on the Deming Cycle has expanded our understanding of the PDSA learning and improvement cycle as well as the relationships to fundamentals of the tool and variants. It is also clear to see the connection into Deming’s description of the System of Profound Knowledge. *Circling Back – Clearing up myths about the Deming Cycle and seeing how it keeps evolving by Ronald D. Moen and Clifford L, Norman

1610

1620

1872

1933

1929

1939

1950

1951 1985

1986 1993

StaQsQcal Quality Control Handbook – 1956 – based on Bell Labs work in 1920’s, 30’s, 40’s


Benefits of Managing VariaYon

•  Proper standards •  RealisFc specificaFons •  Good predicFons, forecasts and esFmates •  Reliable measures of process, operator,

machines, tools, materials, methods, designs, costs

•  Improved processes •  Lower costs of service and manufacture •  Less inspecFon •  More informaFon about process variables •  SoluFons to perplexing engineering

problems •  Making order out of chaos

FOUR STEPS IN A PROCESS CAPABILITY STUDY 1.  Collect data from the

process

2.  Plot sta5s5cal paQerns

3.  Interpret the paQerns 4.  Do what the paQerns

tell you un5l you reach process capability


Unpredictable Processes?

“When a process displays unpredictable behavior, you can most easily improve the process and process outcomes by idenFfying the assignable causes of unpredictable variaFon and remove their effects from your process.”

–  Donald J. Wheeler

•  To remove these effects, you must remove the causes.

•  To remove the causes, you must understand the system and interdependencies.

•  You must talk to the people in the process

•  Listen to what the process has been telling you through the variaFon.


Deming’s 14 Points Key to understanding the 14 Points is variation. The more variation - the more waste, Deming’s 14 points are paraphrased here: 1.  Create constancy of purpose towards improvement.

•  Replace short-term reaction with long-term planning. 2.  Adopt the new philosophy.

•  Management should walk the talk. 3.  Cease dependence on inspection.

•  Reduced variation eliminates need to inspect for defects. 4.  Move towards a single supplier for any one item.

•  Multiple suppliers mean variation between feedstocks. 5.  Improve constantly and forever.

•  Constantly strive to reduce variation. 6.  Institute training on the job.

•  Adequately trained staff will all work the same way, and reduce variation. 7.  Institute leadership.

•  Mere supervision is quota- and target-based 8.  Drive out fear.

•  Long term, it prevents workers from acting in the organization's best interests. 9.  Break down barriers between departments.

•  Use the 'internal customer', that each department serves other departments that use its output. 10.  Eliminate slogans.

•  It's not people who make most mistakes - it's the process they are working within. 11.  Eliminate “management by objectives”.

•  Deming saw production targets as encouraging the delivery of poor-quality goods. 12.  Remove barriers to pride of workmanship.

•  Many of the other problems outlined reduce worker satisfaction. 13.  Institute education and self-improvement.

•  Harassing the workforce without improving the processes they use is counter-productive. 14.  The transformation is everyone's job.

•  “You do not have to do this. Survival is not compulsory.”


Process Prediction and Possibilities


Process Based Improvements


From Data to Wisdom •  Learning begins with questions we cannot answer and ends with

questions we can. . . •  Russ Ackoff

• A pound of informaYon is worth an ounce of knowledge

• A pound of knowledge is worth an ounce of understanding

• A pound of understanding is worth an ounce of wisdom

• A pound of wisdom is priceless

Data InformaYon Knowledge Understanding Wisdom

SYNTHESIS focuses on FUNCTIONS and WHY things work

ANALYSIS focuses on STRUCTURE and HOW things work

ANALYSIS yields KNOWLEDGE SYNTHESIS yields UNDERSTANDING

• A pound of data is worth an ounce of

informaYon


Deming’s Process Model •  Stage or Phase “0” InnovaFons feed the Process at Design & redesign •  Stage 0 Generates Ideas

Suppliers of information, material, equipment

Receipt and test of information & materials

Test of process, machines, methods, costs, user acceptance

Production, assembly, inspection, conformance

Design and redesign Consumer Research

Distribution

Consumers of products & services

A

C

B

D


Deming’s use of this chart in Japan demonstrated the process as a system, starFng in the 1950’s

P-‐D-‐S-‐A or Plan-‐Do-‐Study-‐Act

•  We PLAN what we want to accomplish over a period of time and what we will do to get there.

Action Plan

Do Study

> Plan the objective. > Ask questions, make predictions > Plan what, where, when and who to implement the cycle

Ron Moen’s article with Cliff Norman on the Deming Cycle has expanded our views of the PDSA learning and improvement cycle.

> Carry out the plan. > Document problems and unexpected observations > Begin data analysis

> Analyze the data completely.

> Compare data to

predictions

> Summarize learning

> Adopt the change.

> Adapt the change

> Begin the next

cycle

•  We DO something that furthers the strategies and goals developed in our plan.

We STUDY the results of our actions to make sure we achieve what we plan.

We ACT by developing procedures to ensure our plans continue to be successful and by changing what is needed to achieve the initial goals.


A System of Order From Chaos In YOUR System •  You have SUBJECT KNOWLEDGE

•  You DESIRE IMPROVEMENT

•  What is Your AIM?

•  What is Your THEORY?

•  What are we trying to accomplish?

•  How will we know a change is improvement?

•  What changes can result in an improvement?

•  Use the PDSA Cycle to learn if your THEORY is correct

–  If not, •  Change your theory if it is not correct

AIM

SUBJECT KNOWLEDGE

THEORY

DESIRE FOR IMPROVEMENT IN ANY SYSTEM

“What Is

In It For Me!”

Act Plan

Do Study

System of Profound Knowledge

A Theory of Knowledge

Understanding of Systems

Understanding of Variation

Psychology


System of Profound Knowledge

•  “The aim . . . is to provide an outside view -‐ a lens . . . provides a map of theory by which to understand the organizaYons that we work in”

•  Components of The Whole –  Theory of Knowledge

•  Knowledge is built on theory

–  AppreciaFon for a System •  A system is a network of interdependent components that work

together to accomplish the aim of the system

–  Knowledge About VariaFon •  There will always be variaFon…..

–  Psychology •  Individuals •  Groups •  Society •  Change

•  “One need not be eminent in any part of profound knowledge in order to understand and to apply it”

Psychology

Theory of Knowledge

Knowledge

About Variation

Appreciation For a System

AIM


Table Discussions

AT EACH TABLE DISCUSS: •  WHAT ARE OUR NEXT ACTION STEPS?

–  What did we learn here? –  What do we need to discuss next? –  Who else needs to hear about this? –  What will we do with our learning? –  What adds value to you and your organizaYon? –  What are the posiYve ajributes you can use? –  What are the differences which influence your thinking?


Understanding VariaYon -‐ CQI Learning Lunch

•  Success/Highlight

•  Key Learning

•  Improve

•  Next Steps


CQI Learning Lunch Understanding VariaYon

PredicYng Your System’s Performance

July 10, 2013 Learning Lunch -‐ 10:30 AM to 1:00 PM

cqi$learning$lunch$ understanding variation predicting ... · cqi$academy$of$quality$fundamentals$...

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