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Week05 slides
1. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 1
MGT610
Lecture 5
Relations between Project Variation and
Project Value
Dr. Thomas Lechler Phone: (201) 216-8174
Morton Room 636 FAX: (201) 216-5385
email: tlechler@stevens.edu
2. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 2
Lecture 5: Evidence
• Analyzing project variation.
• Interpreting project variation.
• What to improve?
• How to improve?
3. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 3
Lecture 5: Topics and Objectives
• Managing Effort Value with SPC (Statistical
Process Control)
• Applying SPC on the Project Level
4. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 4
Lecture 5: Agenda
• 1. Maximizing Effort Value
• 2. Managing Variation
• 3. The Problem
• 4. The Solution
• 5. Implementation
• 6. Case Study
• 7. Interpretation
• 8. Improvement
5. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 5
1. Maximizing Effort Value: CC Limits
• Managing Effort Value:
Effort value means to implement the project by maximizing
the performance of the resources.
• CC helps to minimize the project duration
• but
• CC does NOT explicitly support process improvement
6. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 6
1. Maximizing Effort Value: Reducing Variation
• Definition of World-Class Quality:
• “On-Target with Minimum Variance.”
• Operating “On-Target” requires a different way of thinking
about our processes.
• Operating with “Minimum Variance” is achieved only when a
process displays a reasonable degree of statistical control.
• —Walter A. Shewhart
• Wheeler, Chambers 1992, p. xix
7. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 7
1. Maximizing Effort Value: Reducing Variation
• “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”
• —W. Edwards Deming
• “The central problem of management in all its aspects...is to
understand better the meaning of variation, and to extract the
information contained in variation.”
• —Lloyd S. Nelson
8. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 8
2. Managing Variation: Advantages
• Project Processes with less variation :
– Have less variability.
– Are more predictable.
– Have lower costs.
– Achieve faster throughput.
• Variation could mean both: improvement or debasement.
• What are the sources of variation?
• What are the steps for process management?
9. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 9
2. Managing Variation: The Learning Cycle
•How shall we learn?
– learn
– do
– check
– act
•Improvement requires learning
– Improvement is limited by the
rate of learning
– We can improve at learning
10. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 10
2. Managing Variation: 7 Quality Control Tools
Pareto chart
histogram
cause
and
effect
diagram
control chart
check sheet
graphs
scatter plot
11. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 11
3. The Problem: Analyzing Project Variation
• Metrics on Projects:
– Shareholder—Results to achieve on the business level
• The product was defined by a business strategy
– Stakeholder—Results to achieve high customer satisfaction
• The product has to be of value to the customer
– Output—attributes of the product
• You fix a defective product (this is rework)
• The product was produced by a process
– Effort—attributes of the process
• Process improvements to get better project results
• Process improvements to get better products in the future
• There is a problem with all process data
12. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 12
3. The Problem: Process Measurement
• Measuring the Process:
– Reliability Problem:
All metrics come from a measurement process—and it has
variation too. Is our measurement really stable?
If the measurement error is larger than the variation of the
process you are trying to measure, your results are not
meaningful!
– Validity Problem:
Using the right metrics or measures to describe the process.
Do we really measure what we want to measure?
13. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 13
3. The Problem: Analyzing Process Variation
The Process:
All real-world processes vary—
• they have natural “common cause” variation that is
random (“noise”)
• they also vary by a “special cause”
So how do we know if the data is showing us a real change
(from a “special cause” outside the process—a “signal”)
or just noise?
14. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 14
3. The Problem: Consequences
• Summary:
If we can’t differentiate between signals from noise, we can’t tell what
is happening to our process…
=> We can’t tell if it improved, or not…
=> We can’t manage it
15. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 15
4. The Solution: The Inventor of the Control Chart
• Telling signals from noise: control charts
– Dr. Walter Shewhart, the “father of Quality,” developed the control chart
in the 1920’s
– This was the first quality tool developed
16. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 16
5. Implementation: Interpreting the Data
• Process could be:
– stable, predictable, in control
– unstable, unpredictable, out of control
• Process could be changing (improving?):
– Location
– Dispersion (Variation)
• How can we tell? A control chart
17. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 17
4. The Solution: Effort Value with Control Chart
• Aren’t control charts for manufacturing?
In projects we don’t produce the same result over and over…
– Within projects we find similar activities, like the communication
processes, change processes …
– If you use a defined process for the project implementation like the
software development (a methodology), then you produce your
products with a process, and control charts will work
– (If you don’t, you have nothing to improve)
• Control charts don’t depend on the “product” being “the same”
but on the process being “the same”
– … and they will tell you if your process isn’t “the same”
18. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 18
5. Implementation: Choosing the Process Metrics
person week 1 week 2 week 3 week 4 total
Able
Baker
Charlie
Delta
Echo
total
7
5
3
4
3
22
8
2
3
4
3
20
6
3
2
7
2
20
4
7
4
2
3
20
25
17
12
17
11
82
data flow diagram defects
19. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 19
5. Implementation: A Controlled Process
x x
x
x
x
x x
x
x x
x x
Location: OK
Planned average met
Dispersion: OK
Variation tolerable
20. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 20
5. Implementation: An Uncontrolled Process
Location: NOT OK
Planned average not met
Dispersion: NOT OK
Variation not tolerable
21. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 21
5. Implementation: Analyzing the Process Data
22. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 22
5. Individual and Moving Range Charts
• The simplest control charts:
– Moving range (mR) charts
• plot the successive differences between actual data points
– Individual (X) charts
• plot the actual data points
• The strength of control charts:
– NO assumptions about the data!
23. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 23
5. Implementation: X Control Chart
X Control Chart: CHECK LOCATION
24. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 24
5. Implementation: Individual (X) Charts
•Center Line
– the average
•Upper Natural Process Limit
– three sigma limit
•Lower Natural Process Limit
– may be below zero
RXXLNPL
RXXUNPL
N
X
XCL
X
X
N
i
X
660.23
660.23
1
25. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 25
5. Implementation: mR control chart
mR control chart: CHECK DISPERSION
26. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 26
5. Implementation: Moving Range (mR) Charts
• Center Line
– the mean
• Upper Control Limit
– three sigma limit
• Lower Control Limit
– none noneRDLCL
RRDUCL
N
Rj
RCL
R
R
N
j
R
3
4
1
1
27.3
1
28. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 28
6. Case 1: Individual (X) Chart
• c
Improvements
implemented
Days
35
30
25
20
15
10
5
0
Modules
3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
Work assignment lost
UNPL = 23.27
Mean = 6.96
UNPL = 6.03
Mean = 2.83
New
method
•Development time in days
29. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 29
6. Case1: Moving Range (MR) Chart
Development time in days
Improvements
implemented
Days
30
25
20
15
10
5
0
Modules
3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
Work assignment lost
UCL = 20.03
Mean = 6.13
30. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 30
6. Case 2: Data
Module coding Time in Hours
no. 1 2 3 4 5 6 7 8 9 10
X 4.4 2.9 4.2 5.4 6.6 3.6 1.0 1.3 1.2 1.2
mR 1.5 1.3 1.2 1.2 3.0 2.6 0.3 0.1 0.0
no. 11 12 13 14 15 16 17 18 19 20
X 1.0 2.8 2.0 3.0 1.8 2.3 1.3 5.2 4.1 4.3
mR 0.2 1.8 0.8 1.0 1.2 0.5 1.0 3.9 1.1 0.2
31. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 31
6. Case 2: mR Control Chart
Coding Time in Hours—moving Range (mR) chart
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Modules
Hours
Mean= 1.21
UCL=3.95
32. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 32
6. Case 2: X Control Chart
Coding Time in Hours—individual (X ) chart
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Modules
Hours
Mean=
2.98
UCL=6.20
33. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 33
7. Interpretation: What’s a signal?
• Western Electric zone rules:
– 1 point more than three sigma
– 2 out of 3 consecutive points more than two sigma
on the same side of the center line
– 4 out of 5 consecutive points more than one sigma
on the same side of the center line
– 8 consecutive points on the same side of the center line
• These tell us the x chart has changed
34. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 34
7. Interpretation: Zone Rule 1
• 1 point more than three sigma
CL
3
2
1
1
2
3
Note: for both individual and moving range charts
35. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 35
7. Interpretation: Zone Rule 2
• 2 out of 3 points more than two sigma on the same side
of the center line
CL
3
2
1
1
2
3
Note: for individual charts ONLY
36. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 36
7. Interpretation: Zone Rule 3
• 4 out of 5 points more than one sigma
on the same side of the center line
CL
3
2
1
1
2
3
Note: for individual charts ONLY
37. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 37
7. Interpretation: Zone Rule 4
CL
3
2
1
1
2
3
Note: for individual charts ONLY
• 8 on the same side of the center line
38. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 38
7. Interpretation: The Empirical Rule
• For distributions commonly encountered:
– 60-75% of the values will be within
1 sigma of the center line
– 90-98% of the values will be within
2 sigma of the center line
– 99-100% of the values will be within
3 sigma of the center line
• So x, mR charts work regardless of the distribution—which we
don’t know…
39. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 39
8. Improvement: Statistical Process Control
• A process in statistical control:
– is stable ("in control")
– you may predict its performance,
or plan based on its past performance
– you may improve it
(and can tell that you have)
– may or may not be satisfactory!
• (it may not be "capable")
• So how do we improve a process?
40. Mgt 610 Strategic Perspectives on Project Management
(c) 2013, Thomas Lechler. All rights reserved.For academic use only. 40
8. Improvement: Process Improvement…
•A revolutionary idea
– By what method?
• What tools?
Techniques?
– How many last year?
– How many this year?
– Is there a plan?
– Are you improving at
improving?
– Is management doing it?
Why not?