Improving Business Performance Through the Use of Statistical Thinking

1
Improving Business Performance Through the Use
of Statistical Thinking
By
Charles M. Parks, PhD, PE Industrial and
Manufacturing Systems Engineering parksc_at_ohio.edu
2
Today's Realities

• Global competition is forcing changes in all
  aspects of our society
• Business
• Government
• Education
• Customers demand more
• We have to change how we manage
• All aspects of our organizations
• All processes we use to do our work

3
Evolution of Statistics in Industry

• Driving Force Focus
• 1940 WWII Statistical Quality Control
• 1950 Post WWII Increase Production
• 1960 Sputnik Research, Development
• Food Drug Act Manufacturing
• Computer
• 1970 Environmental Biopharmaceutical
• Protection Agency Statistical Computing
• Environmetrics
• 1980 Global Competition Total Quality

4
Forces Affecting the Use of Statistical Thinking
U.S. Business
Global Competition
Computer Technology
5
Effects of Driving Forces

• Computer Technology
• More statistical studies done by
  non-statisticians
• Less need for statisticians to do routine
  statistical work
• Global Competition
• Management has to change how the organization
  operates
• Greater emphasis on managerial and strategic
  processes

Statisticians have opportunity to do more
strategic and managerial work
6
Strategic Questions Being Asked

• How do I identify improvement projects that will
  return 300k to the bottom line?
• What quality system should I use ISO 9000,
  Baldrige or Six Sigma?
• How do I get employees to implement improvements?
• Should we use data mining and if so, how?
• What statistical software packages should we
  adopt?
• What statistical and quality consultants should
  we hire?

7
Paradigm Shift for Use of Statistics

• FROM
• Problem solving focus
• Problem Solver
• Identify problems and solutions
• Use SPC, DOE and other tools

• TO
• Focus on improving processes, products the
  organization
• Process Improver, Leader, Problem Solver
• Identify problems solutions and implement
  improvements
• Use structured improvement methods

8
Expanding World Of Statistics
Organizational Impact
The Way We Think
Organizational Improvement
Product Process Improvement
Problem Solving
Time
9
Paradigm Shift for Use of Statistics

• FROM
• Manufacturing and R D focus
• Working with Scientists and engineers one-on-one
  as the expert
• Shared computing systems
• Limited statistical software

• TO
• Working with the whole organization
• Working with employee teams including management
  as a team member
• Personal Computers
• Statistical software broadly available

10
Skills Needed for the New Environment

• Business acumen
• Leadership and team building
• Ability to communicate with management
• Marketing and sales
• Platform and teaching skills
• Project planning and management
• Use of structured improvement methods
• Design and conduct meetings
• Modern computing and technology

11
Conjecture

• Broad use of statistical thinking will help
  organizations better manage and improve the
  processes they use to run their business and
  serve their customers.

12
Contribution of Statistics

• "The long-range contribution of statistics
  depends not so much on getting a lot of highly
  trained statisticians into industry as it does in
  creating a statistically minded generation of
  physicists, chemists, engineers and others who
  will in any way have a hand in developing and
  directing the productive processes of tomorrow."

Walter A. Shewhart Bell Telephone
Laboratories 1939
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What is Statistical Thinking?
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What is Statistical Thinking?

• 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, and

• Understanding and reducing variation are
• keys to success

Source Glossary of Statistical Terms, ASQ
Quality Press
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Using Statistical Thinking To Improve Business
Performance
Goal is to Delight Customers
Processes Serve Customers
Use Statistical Tools to - Analyze Process
Data - Understand Process Variation - Manage
Improve Processes - Better Serve Customers
Process Performance Varies
Measure Process Performance
16
Steps in Implementing Statistical Thinking
Satisfied

• Employees
• Customers
• Shareholders
• Community

17
Statistical Thinking
Key Concepts
Role of Data
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Relation Between Statistical Thinking and Methods
Process
Variation
Data
Statistical Tools
Statistical Thinking
Statistical Methods
19
Relation Between Statistical Thinking and
Statistical Methods
Statistical Thinking
Statistical Methods
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When People Have a Process View

• People understand the problem and their role
  in its solution
• It is easier to define the scope of the problem.
• It is easier to get to root causes.
• Opportunities for improvement are missed
• The process, not the people get blamed for the
  problem (85/15 Rule).
• Process management is effective
• Improvement is accelerated

You cant improve a process that you dont
understand
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Process
Series of activities that transforms inputs into
outputs
Process
Inputs
Outputs
Suppliers
Customers
S I P O
C
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Process Transforms Inputs into Outputs
Finished Goods or Services
Suppliers Information Historical Data
External Factors - Materials - People - Methods -
Machines - Environment - Measures
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Processes and Sub-Processes
24
Leaky Pipe
Customer Orders In
Negotiation
Assignment
Manufacture
Installation
Completion
67 Go Through Without Leaking Out
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New Credit Card Account Process
Fill Out and Send in Application
Key in Application
Process Application
Produce and Deliver Card

• Key Metrics
• - Cycle time
• - Application completeness
• - Application accuracy
• - Backlog

Resolve Problem Applications
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When People Understand Variation

• Decisions are based on all the data
• - Not just the last data point
• Proper action is taken
• - Less fire fighting is done
• Tampering and micromanaging are reduced
• Goals and methods to attain them are successful
• Understanding the process in enabled
• Learning grows continuously
• Process management is effective
• Improvement is accelerated

27
Deming once said If I had to reduce my message
for management to just a few words, Id say it
all had to do with reducing variation.
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When People Use Data

• Decisions are guided by data
• Learning is enhanced - Progress is accelerated
• Those with data have greater influence
• Discussions produce more light and less heat
• Historical memory is more precise and accurate
• It is easier to get agreement on what
• The problem is and what success looks like
• Progress has been made
• Process management is effective
• Improvement is accelerated

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Pitfall Valuing only quantitative data
Qualitative data are just as important.
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Are you just pissing and moaning, or can you
verify what youre saying with data?
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Without Statistical Thinking

• Your ability to manage and improve processes to
  better serve customers is handicapped
• Its like
• Football without a passing attack
• Growing a lawn without fertilizer
• Doing research without measurements
• Playing golf without your irons

Early on, we failed to focus adequately on core
work processes and statistics. David Kearns
and David Nelder, Xerox Corporation
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Use of Statistical Thinking
Statistical Thinking Element
Process
Variation
Data
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Using Statistical Thinking Without Data

• Reduce the number of suppliers
• Use a variety of communication media
• Reduce tampering, micromanagement, and
  overcontrol
• Provide flexible benefits and work hours
• Use meeting management techniques
• Create project management systems
• Create, monitor, and update plans

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Value of Using Statistical Thinking

• Process focus provides the context and relevancy
  for using statistical methods
• How we do our work for our customers
• Results in broader and more effective use of
  statistical methods
• All parts of the organization
• Manage and improve processes
• Guide strategic and managerial action
• Provides traction for statistical methods

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Beef Industry Hits Hard TimesExperts Say
Answer Rests in Satisfying Customers

• The 37 billion beef industry is losing
  market share to chicken and pork 34 share in
  1996 down from 52 share in 1976. Annual beef
  consumption has decreased from 85lbs./person in
  1970 to 67lbs./person in 1996, while annual
  poultry consumption has increased from 41 to
  72lbs./person during the same time period.
• The problem is inconsistent product. I can
  go to a store now and look through 20 steaks to
  find one that is acceptable. But a chicken breast
  is a chicken breast, says one consumer. The
  poultry industry has changed how its products are
  raised, prepared, packaged and marketed.
  According to a 1991 study, consumers are not
  satisfied one in 5 times they cook or order beef.
  Complaints ranged from confusion over various
  grades of beef to difficulty cooking, to
  toughness or unpleasant beef.
• And in an era of increasing emphasis on
  healthy diets, consumers say they now avoid red
  meat because its fat and cholesterol content
  makes a less healthy choice. Source March 5,
  1996, USA Today

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Workshop - Wheres the Beef?

• Problem - Beef Industry Hits Hard Times
• USATODAY 3-5-96
• 1. Can statistical thinking be used to solve
  this
• problem? Why or why not?
• 2. If so, how should the beef industry apply
• statistical thinking to deal with this
  situation?
• Report Back - Your responses to questions 1 2

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Beef Industry Crisis

• Customers unhappy
• Inconsistent product
• Difficult to cook
• Not tender
• High fat content
• Market share down from 52 to 37
• Consumption of chicken and pork increasing
• Can statistical thinking help solve this problem?

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Beef Industry Crisis

• Key sources of variation
• Genetics -- breed bloodlines
• Feed content
• Animal environment and treatment

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Beef Industry Crisis

• Solution
• Recognize that excessive variation is the problem
• Recognize the process involved
• Identify key measurements
• Frame size
• Lean-to-fat ratio
• Muscling levels
• Find a solution that
• Reduces variation throughout the process
• Produces products that satisfy customer needs

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Beef Production Process
Genetics Defined
Purebred Breeders
Retailers Restaurants
Processors Packers
Commercial Herds
Back-Grounders
Feedlots
Calves Produced 6 months 400 lbs.
10 months 800 lbs.
15 months 1200 lbs.
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Market Alliance Goals

• Low-fat genetics
• Constant commercial herd genetics
• A few high-performance bulls
• Calves raised and fed in a constant way
• Product marketed in a constant way

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Robustness - An Underused Concept

• Key aspect of Statistical Thinking
• Reduce the effects of uncontrollable variation
  in
• Product design
• Process design
• Management practices
• Anticipate variation and reduce its effects

43
Robustness of Product and Process Design

• A third way to reduce variation
• Anticipate variation
• Design the process or product to be insensitive
  to variation
• A robust process or product is more likely to
  perform as expected
• 100 inspection cannot provide robustness

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Robust Products are Designed in Anticipation of
Customer Use

• Washing machine tops
• User-friendly computers and software
• Low-maintenance automobiles
• 5 mph bumpers
• Medical instruments for home use

45
Product and Process Robustness

• Product Performance is insensitive to variations
  in conditions of manufacture, distribution, use
  and disposal.
• Process Performance is insensitive to
  uncontrollable variations in process
• Inputs
• Transformations - activities - steps
• External factors

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Robustness in Management

• Develop strategies that are insensitive to
  economic trends and cycles
• Design a project system that is insensitive to
• Personnel changes
• Changes in project scope
• Variations in business conditions
• Respond to differing employee needs
• Adopt flexible work hours
• Provide cafeteria benefits package

More ...
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Robustness in Management (Continued)

• Enable personnel to adapt to changing business
  needs
• 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 ways
• People vary --- they are different
• - Day to day
• - Person to person
• - Group to group
• - Organization to organization

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Three Ways to Reduce Variation and Improve
Quality
Control the Process Eliminate Special Cause
Variation
Improve the System Reduce Common Cause Variation
Quality Improvement
Anticipate Variation Design Robust Processes
Products
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Process Robustness Analysis

• Identify Those Uncontrollable Factors that Affect
  Process Performance
• Weather
• Customer Use of Products
• Employee Knowledge, Skills, Experience, Work
  Habits
• Age of Equipment
• Design the Process to be Insensitive to the
  Uncontrollable Variations in the Factors

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Using Statistical Thinking in the Organization
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Use of Statistical Thinking
Depends on levels of activity and job
responsibility.
Where we're headed
Strategic
Executives
Managerial processes to guide us
Managerial
Managers
Where the work gets done
Operational
Workers
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Process
A series of activities that converts inputs into
outputs
Process Steps
Inputs
Outputs
Suppliers
Customers
S I P O
C
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IBM Core Processes
Product Processes
Enterprise Processes
Requirements Collections and Definition
Translation

Planning Financial Personnel Mgmt. Info.
Sys. Legal Communications Public Relations
Market Segment
INTERFACES
Market Place
Business Processes
55
Examples of Operational Processes

• Manufacturing
• Order Entry
• Delivery
• Distribution
• Billing
• Collection
• Service

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Examples of Statistical Thinking at the
Operational Level

• Work processes are mapped and documented
• Key measurements are identified
• Time plots displayed
• Process management and improvement utilize
• Knowledge of variation, and
• Regular reviews of process data
• Improvement activities focus on the process, not
  blaming employees.

.


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Examples of Strategic Processes

• Strategic Plan Development
• Strategic Plan Deployment
• Acquisitions
• Corporate Budget Development
• Communications - Internal and External
• Succession Planning and Deployment
• Organizational Improvement

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Examples of Statistical Thinking at the Strategic
Level

• Executives use systems approach.
• Core processes have been flow charted
• Strategic direction defined and deployed.
• Measurement systems in place.
• Employee, customer, and benchmarking studies are
  used to drive improvement.
• Experimentation is encouraged.

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Examples of Managerial Processes

• 1. Employee Selection
• 2. Training and Development
• 3. Performance Management (including coaching)
• 4. Recognition and Reward
• 5. Budgeting

• 6. Setting Objectives and Goals
• 7. Project Management
• 8. Communications
• 9. Management Reporting
• 10. Planning

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Examples of Managerial Processes
Management Reporting
Training Development
Planning
Core Business Processes
Objectives Goals
Budgeting
Customers
Recognition Rewards
Communication
Performance Management
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Examples of Statistical Thinking at the
Managerial Level

• Managers use meeting management techniques
• Standardized 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 reduced
• A variety of communication media are used.

.
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Personnel Requisition Process
Resume Received
Resume Returned by Hiring Manager
Resume Sent to Hiring Manager
Applicant Interviewed by Company
Applicant Interviewed by Consultant
New Employee Starts Work
63
Corporate RD Budgeting Process
Board of Directors Review
RD Senior VP Review
Budget 1 Initiatives
Budget 2 Personnel Funding ()
Budget 3 Final
Budget Deployment
Business Unit Budget Preparation
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Variables Affecting Managerial Processes
Employee Background Skills Bosss
Needs Other Managers Needs Actions Market
Place Demands
Product and Service Processes
Managing Processes
Customer
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Example - Effect of Managerial Processes on
Customers
Recruiting and Hiring
Motivated and Capable Employees
Good Products and Services
Training
Recognition and Reward
Happy Customer
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Examples of Managerial Processes

• 1. Employee Selection
• 2. Training and Development
• 3. Performance Management (including coaching)
• 4. Recognition and Reward
• 5. Budgeting

• 6. Setting Objectives and Goals
• 7. Project Management
• 8. Communications
• 9. Management Reporting
• 10. Planning

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How Do We Use Statistical Thinking to Improve
Business Performance?

• By individuals and teams?
• By the whole organization?
• How do we deploy statistical thinking throughout
  the organization?
• An effective approach

Six Sigma
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References on Statistical Thinking

• ASQ Statistics Division (1996) Statistical
  Thinking, Special publication available from
  American Society for Quality, Quality Information
  Center, Milwaukee, WI. (1-800-248-1946).
• Britz, G. C., Emerling, D.W., Hare, L. B., Hoerl,
  R.W., Janis, S. J. and Shade, J.E. (1999)
  Improving Performance Through Statistical
  Thinking, ASQ Quality Press, Milwaukee, WI.
• Hoerl, R. W. and Snee, R.D. (1995) "Redesigning
  the Introductory Statistics Course," University
  of Wisconsin Center for Quality and Productivity
  Improvement, Report No. 130, Madison, WI.
• Hoerl, R. W. and Snee, R. D. (2001) Statistical
  Thinking -Improving Business Performance, Duxbury
  Press, Pacific Grove, CA.
• Quality Press (1996) Glossary and Tables for
  Statistical Quality Control, Quality Press,
  Milwaukee, WI.

69
References on Statistical Thinking

• Shewhart, Walter A. (1939) "Statistical Methods
  from the Viewpoint of Quality Control", The
  Graduate School, U.S. Department of Agriculture,
  Washington, D.C.
• Snee, R.D. (1990) "Statistical Thinking and Its
  Contribution to Total Quality", The American
  Statistician, 44, pp. 116-121.
• Snee, R.D. (1991) "Can Statisticians meet The
  Challenge of Total Quality?", Quality Progress,
  24, No1, pp.60-64.
• Snee, R.D. (1993) "Creating Robust Work
  Processes", Quality Progress, February 1993, pp.
  37-41
• Snee, R.D. (1998) Getting Better Business
  Results Using Statistical Thinking and Methods
  to Shape the Bottom Line, Quality Progress, June
  1998, 103-106.

70
References on Statistical Thinking

• The Power of Statistical Thinking, M.G.Leitnaker,
  R.D.Sanders,C.Hild, Addison-Wesley, 1996
• Snee, R.D. (1998) "Nonstatistical Skills That Can
  Help Statisticians Be More Effective," Total
  Quality Management Journal, V 9, 711-722.
• Snee, R. D. (1999) Statisticians Must Develop
  Data-Based Management Systems as Well as Create
  Measurement Systems. International Statistical
  Review, 67, No.2, August 1999, 139-144.
• Snee, R.D. (1999) Why Should Statisticians Pay
  Attention to Six Sigma? Quality Progress,
  September 1999, 100-103.
• Snee, R. D.(1999) Development and Use of
  Statistical Thinking A New Era, International
  Statistical Review, 67.
• Snee, R. D. (2000) Six Sigma has Improved Both
  Statistical Training and Processes, Quality
  Progress, Oct. 2000.