In this webinar (sponsored by Gemba Academy), Mark Graban, author of Lean Hospitals, will show how simple statistical process control (SPC) methods can be used by managers and leaders to make better decisions about their businesses.
Using examples from manufacturing, healthcare, and services industries, Mark will illustrate the basic SPC rules and will show you how to create and interpret a control chart, allowing you to spot statistically valid trends and avoid overreacting to common cause variation in your performance measures.
Please join us for a lively discussion and interactive Q&A!
http://www.MarkGraban.com
http://www.GembaAcademy.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/
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”
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)
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)
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
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.
Nelson worked with Deming -- ASQ's 20th Honorary Member
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.
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?
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%.
Executive time series -- Take into account noise in the system and common cause variation the picture is much less clear
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
Another reason charts are preferable is that they are VISUAL and much more easily interpreted by people
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.
So we could CHART the data and make it more visual. But how do we manage?
Driving to work….
Management is prediction
Topic that people didn’t like? Website down? Stop SOPA Day
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
Expect one “false positive” signal every 371 data points with just this rule (“Shewhart Rule”)
This is how I would test if a client is not only sustaining gains, but also improving