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Using SPC to Make Better
 Management Decisions
          Mark Graban
      Author, Lean Hospitals
   Co-Author, Healthcare Kaizen
     www.MarkGraban.com
         @MarkGraban
Key Management Questions
• How are we performing?
   – Are we getting better or worse?
• What action should we take?



“Failure to understand variation is a
central problem of management.”
   – Dr. Lloyd S. Nelson                Some rights reserved by Marco Bellucci
My Most Favorite Book Ever




                 Donald J. Wheeler, PhD
               http://www.spcpress.com/
“No data have meaning
apart from their context”
Comparisons in the News


                     Fatalities per 100 Million Vehicle
                        Miles Traveled (U.S. & CT)
                2
                                     U.S.
               1.5

                1
                                CT
               0.5

                0
                 1992    1995    1998   2001   2004   2007   2010
Need to Look for Trends
“You don't want to
make a big conclusion
based on just one
year.”
  – Jonathan Adkins of the
    Governors Highway Safety
    Association
                               “Office Space”
Two-Point Comparisons in Politics
Did We Improve?
Run Charts Show More Context
Need to Avoid Bad Conclusions
    “The average patient satisfaction
      increased from 87.2 to 89%”
A Better Dashboard




Limited information you need to make decisions
Not This…
Overwhelming Data

                                Sept „06


                                  ?

               Can we predict
               September?


      Can We See Trends?
The Good News…


There is a better way
SD = Standard Deviation, a measure of variation
                                               “X” Control Chart
                                          (Chart for Individual Values)




                                                                          Goal = 25 minutes
             “Every system is perfectly designed to
               get the results it gets.” (Deming)
X and MR Chart Combo
Small Business Example
           Revenue as a Stable Process?

X chart




MR chart
Deming‟s 7 Concepts of Variation
1. All variation is caused – specific reasons.
2. There are 4 types of causes:
  1.   Common causes
  2.   Special causes
  3.   Tampering
  4.   Structural
3. Managers must distinguish amongst these
  – Each one requires different managerial actions.
Deming‟s 7 Concepts of Variation
4. For special causes, get timely data
5. For common causes, all data are relevant.
  – In-depth knowledge of the process being improved is
    needed – statistics, flow charts, Pareto, stratification
    analysis, DOE
6. When all variation is common cause, the system
   is said to be “stable” and “predictable.”
7. SPC limits let a manager predict future
   performance with some confidence.
The Funnel Experiment
• Lloyd Nelson, 1987
  – Suspend a funnel on a stand a
    few inches off the ground
  – Drop 50 marbles
                                    x
A “Stable” System
• Does NOT mean:
  – Zero variability
  – System meets customer
    requirements

• Means only:
  – Causes of variation are basically constant over time
We Have to Try Harder!!!
• 4 different rules for adjusting the funnel
                                  Adjust relative             Adjust relative
       No adjustment              to last position              to center




   Learn more – online simulator at http://www.symphonytech.com/dfunnel.htm
So we should do
    nothing?
“Don’t just do something,
  stand there.” -- Deming
Responding to Daily Changes
60                         Daily Production Average
50         Praise                         PT                                            PT
40
           Team                                                                                                        GOAL
30
                        Kick                                                  KB
20                      Butt                                                                                KB
10

 0
               Are we helping? Is this process stable?
      3/1/07


               3/2/07


                        3/3/07


                                 3/4/07


                                          3/5/07


                                                   3/6/07


                                                            3/7/07


                                                                     3/8/07


                                                                               3/9/07


                                                                                        3/10/07


                                                                                                  3/11/07


                                                                                                             3/12/07
0
                10
                           20
                                           30
                                                40
                                                     50
 3/1/2007                                                           60




 3/3/2007


 3/5/2007


 3/7/2007
                     Lower Control Limit
                                                          Upper Control Limit




 3/9/2007


3/11/2007


3/13/2007


3/15/2007


3/17/2007
                                                                                Creating a Control Chart




3/19/2007
Step 1: Initial Data
• Generally need 20 data
  points to calculate
  control limits
Step 2: Mean & MRs
• Calculate mean of the
  first 20 points
• Calculate the moving
  range of the first 20
  points
   – Ex: =ABS(E5-E4)
Step 3: Draw Initial Chart
                       (with Mean line)
                                LeanBlog.org Daily Page Loads
2500



2000



1500



1000



 500



   0
       1   2   3    4   5   6    7   8   9   10   11   12   13   14   15   16   17   18   19   20   21   22
Step 4: Add Control Limits
• Calculate “MR-bar”
   – Average of the 1st 19
     MRs
• Calculate Control Limits
   – LCL = Mean – 3*(MR bar)/1.126
   – UCL = Mean + 3*(MR bar)/1.126
Step 5: Review Chart
                               LeanBlog.org Daily Page Loads
2500



2000



1500



1000



 500
                                                                     Special Cause?
   0
       1   2   3   4   5   6    7   8   9   10   11   12   13   14   15   16   17   18   19   20   21   22
Step 6: Revise Limits
Step 7: Evaluate Over Time
                                 LeanBlog.org Daily Page Loads
3000


2500


2000


1500


1000


500


   0
       1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930313233343536373839404142434445464748495051
Step 7: Evaluate Over Time
                                 LeanBlog.org Daily Page Loads
3000


2500


2000


1500


1000


500


   0
       1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930313233343536373839404142434445464748495051
Step 7: Shift the Limits
                                 LeanBlog.org Daily Page Loads
3000


2500


2000


1500


1000


500


   0
       1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930313233343536373839404142434445464748495051
“Western Electric” Rules (1956)
• 8 consecutive points on same side of mean

• 6 consecutive points moving same direction

• 14 alternating up/down points in a row

• Any single point above or below 3-sigma LCL or UCL

   – Full rules  http://bit.ly/WErules
Process Shifts
           35
           35
                                                       Daily TAT
           30
           30                                                                                                                                       Process Shift
           25
           25
           20
           20
           15
           15
           10
           10
            5
            5
            0
                1

                    4

                        7

                            10 10

                                    13 13

                                            16 16

                                                    19 19

                                                            22 22

                                                                    25 25

                                                                            28 28

                                                                                    31 31

                                                                                            34 34

                                                                                                    37 37

                                                                                                            40 40

                                                                                                                    43 43

                                                                                                                            46 46

                                                                                                                                    49 49

                                                                                                                                            52 52
            0
                1

                    4

                        7




• If you made a change that you expected to improve the
  system, use a control chart to test the hypothesis
Long-Term Process Shifts
NOT Understanding Variation Leads To…
• Pressuring people to get better results by
  working harder within the same system
• Wasting time looking for explanations of a
  perceived trend when nothing has
  changed
• Taking other actions when it would have
  been better to do nothing
• Not focusing on systemic improvements
Isn’t it always the system?


It’s (almost) always the system.
Q&A / Contact Info
• Email:
   – mark@constancy.us
• Blog:
   – www.leanblog.org
• Twitter:
   – @MarkGraban
• Books:
   – www.LeanHospitalsBook.com
   – www.HCkaizen.com

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Using SPC to Make Better Management Decisions

  • 1. Using SPC to Make Better Management Decisions Mark Graban Author, Lean Hospitals Co-Author, Healthcare Kaizen www.MarkGraban.com @MarkGraban
  • 2. Key Management Questions • How are we performing? – Are we getting better or worse? • What action should we take? “Failure to understand variation is a central problem of management.” – Dr. Lloyd S. Nelson Some rights reserved by Marco Bellucci
  • 3. My Most Favorite Book Ever Donald J. Wheeler, PhD http://www.spcpress.com/
  • 4. “No data have meaning apart from their context”
  • 5. Comparisons in the News Fatalities per 100 Million Vehicle Miles Traveled (U.S. & CT) 2 U.S. 1.5 1 CT 0.5 0 1992 1995 1998 2001 2004 2007 2010
  • 6. Need to Look for Trends “You don't want to make a big conclusion based on just one year.” – Jonathan Adkins of the Governors Highway Safety Association “Office Space”
  • 8.
  • 10. Run Charts Show More Context
  • 11. Need to Avoid Bad Conclusions “The average patient satisfaction increased from 87.2 to 89%”
  • 12.
  • 13. A Better Dashboard Limited information you need to make decisions
  • 15. Overwhelming Data Sept „06 ? Can we predict September? Can We See Trends?
  • 16. The Good News… There is a better way
  • 17. SD = Standard Deviation, a measure of variation “X” Control Chart (Chart for Individual Values) Goal = 25 minutes “Every system is perfectly designed to get the results it gets.” (Deming)
  • 18. X and MR Chart Combo
  • 19. Small Business Example Revenue as a Stable Process? X chart MR chart
  • 20. Deming‟s 7 Concepts of Variation 1. All variation is caused – specific reasons. 2. There are 4 types of causes: 1. Common causes 2. Special causes 3. Tampering 4. Structural 3. Managers must distinguish amongst these – Each one requires different managerial actions.
  • 21. Deming‟s 7 Concepts of Variation 4. For special causes, get timely data 5. For common causes, all data are relevant. – In-depth knowledge of the process being improved is needed – statistics, flow charts, Pareto, stratification analysis, DOE 6. When all variation is common cause, the system is said to be “stable” and “predictable.” 7. SPC limits let a manager predict future performance with some confidence.
  • 22. The Funnel Experiment • Lloyd Nelson, 1987 – Suspend a funnel on a stand a few inches off the ground – Drop 50 marbles x
  • 23. A “Stable” System • Does NOT mean: – Zero variability – System meets customer requirements • Means only: – Causes of variation are basically constant over time
  • 24. We Have to Try Harder!!! • 4 different rules for adjusting the funnel Adjust relative Adjust relative No adjustment to last position to center Learn more – online simulator at http://www.symphonytech.com/dfunnel.htm
  • 25. So we should do nothing? “Don’t just do something, stand there.” -- Deming
  • 26. Responding to Daily Changes 60 Daily Production Average 50 Praise PT PT 40 Team GOAL 30 Kick KB 20 Butt KB 10 0 Are we helping? Is this process stable? 3/1/07 3/2/07 3/3/07 3/4/07 3/5/07 3/6/07 3/7/07 3/8/07 3/9/07 3/10/07 3/11/07 3/12/07
  • 27. 0 10 20 30 40 50 3/1/2007 60 3/3/2007 3/5/2007 3/7/2007 Lower Control Limit Upper Control Limit 3/9/2007 3/11/2007 3/13/2007 3/15/2007 3/17/2007 Creating a Control Chart 3/19/2007
  • 28. Step 1: Initial Data • Generally need 20 data points to calculate control limits
  • 29. Step 2: Mean & MRs • Calculate mean of the first 20 points • Calculate the moving range of the first 20 points – Ex: =ABS(E5-E4)
  • 30. Step 3: Draw Initial Chart (with Mean line) LeanBlog.org Daily Page Loads 2500 2000 1500 1000 500 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
  • 31. Step 4: Add Control Limits • Calculate “MR-bar” – Average of the 1st 19 MRs • Calculate Control Limits – LCL = Mean – 3*(MR bar)/1.126 – UCL = Mean + 3*(MR bar)/1.126
  • 32. Step 5: Review Chart LeanBlog.org Daily Page Loads 2500 2000 1500 1000 500 Special Cause? 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
  • 33. Step 6: Revise Limits
  • 34. Step 7: Evaluate Over Time LeanBlog.org Daily Page Loads 3000 2500 2000 1500 1000 500 0 1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930313233343536373839404142434445464748495051
  • 35. Step 7: Evaluate Over Time LeanBlog.org Daily Page Loads 3000 2500 2000 1500 1000 500 0 1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930313233343536373839404142434445464748495051
  • 36. Step 7: Shift the Limits LeanBlog.org Daily Page Loads 3000 2500 2000 1500 1000 500 0 1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930313233343536373839404142434445464748495051
  • 37. “Western Electric” Rules (1956) • 8 consecutive points on same side of mean • 6 consecutive points moving same direction • 14 alternating up/down points in a row • Any single point above or below 3-sigma LCL or UCL – Full rules  http://bit.ly/WErules
  • 38. Process Shifts 35 35 Daily TAT 30 30 Process Shift 25 25 20 20 15 15 10 10 5 5 0 1 4 7 10 10 13 13 16 16 19 19 22 22 25 25 28 28 31 31 34 34 37 37 40 40 43 43 46 46 49 49 52 52 0 1 4 7 • If you made a change that you expected to improve the system, use a control chart to test the hypothesis
  • 40. NOT Understanding Variation Leads To… • Pressuring people to get better results by working harder within the same system • Wasting time looking for explanations of a perceived trend when nothing has changed • Taking other actions when it would have been better to do nothing • Not focusing on systemic improvements
  • 41. Isn’t it always the system? It’s (almost) always the system.
  • 42. Q&A / Contact Info • Email: – mark@constancy.us • Blog: – www.leanblog.org • Twitter: – @MarkGraban • Books: – www.LeanHospitalsBook.com – www.HCkaizen.com

Editor's Notes

  1. Nelson worked with Deming -- ASQ's 20th Honorary Member
  2. What is a “quality panel”? Keep in mind this is supposed to be a public metric in the LOBBY for visitors to see. What is the scale? What is a good score? What’s a good score compared to others? Why is the target what it is? The target is SUSPICIOUSLY close to the actual. Comparing a number to a target provides very little context… so does comparing a number to last year or last quarter… as we often see in the news.
  3. Test scores are down, teen smoking rates are up… Big changes aren't necessarily signal -- Small changes aren't just noise. 2.9% decline might be somewhat trivial (but good), while a 42% increase in CT *might* be statistically significant. Each state’s “JUMP” could be statistical noise. Look at the chart (made from NHTSA data) – are our roads safer (chart) or more dangerous (headline). A 42% increase in CT – what’s going on there?
  4. Weird that the time scale goes right to left. What looks like an increase from 43 to 47% disapproval, could statistically be a drop from 46% to 44%.
  5. Executive time series -- Take into account noise in the system and common cause variation the picture is much less clear
  6. Consulting firm case study from a hospital… the early and late data point comparison…. Or you can try the linear trend. But by SPC standards, this is a stable process… not statistically valid improvement
  7. Another reason charts are preferable is that they are VISUAL and much more easily interpreted by people
  8. I wish I could say I just won about a bet about incorporating Knight Rider into the webinar… but I just like the picture. Sorry.
  9. So we could CHART the data and make it more visual. But how do we manage?
  10. Driving to work….
  11. Management is prediction
  12. Topic that people didn’t like? Website down?  Stop SOPA Day
  13. Special cause of Jan 2 – holiday weekend, so that was eliminated. Not the most stable process, but can generally predict daily page loads would be between 1200 and 2200 without there being any special cause
  14. Expect one “false positive” signal every 371 data points with just this rule (“Shewhart Rule”)
  15. This is how I would test if a client is not only sustaining gains, but also improving
  16. You’re different story