Fully Supporting the Entire
Project Lifecycle with
Information Technology
Dr. James R. Burns, Professor
Target/Output Layer
Process Nodes
College of Project Administration
Texas Tech University
Lubbock, Texas 79409-2101
Intermediate
Layers
Dr. Onur Ulgen, Professor
Department of Industrial and Systems Engineering
University of Michigan, Dearborn
Dearborn, Michigan 48128
Source/Input Layer
Process Nodes
Background
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Existing products for project management
do not support the entire lifecycle. As a
result many projects fail because of
1) poor definition of the ultimate product,
2) a lack of specification of the Project
case, or
3) failure to determine a measurable value
system by which benefit can be assessed
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
2
Existing PM Software

. The existing PM software product space
is populated with offerings that support
only two of the four stages of the project
lifecycle—a) planning and budgeting and
b) execution and control. Existing tools
do not support the beginning stage—
definition and conceptualization--nor do
they support the last stage—termination
and closure.
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
3
This paper proposes an
architecture for a project
management tool that…
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subsumes existing PM tools and provides
for integrated project definition, planning,
development, and closure.
suggests “prototypes” of specific features
one would expect a total project
management support tool to provide.
uses the Internet for multi-user
collaboration.
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
4
Focus
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Reduction of time to project and
product completion
Reduction of project and product cost
Increases in the contribution to
customer-perceived value
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
5
Architecture -- Components
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Reusable requirements repository
Expert system
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Knowledge base
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Knowledge nets, Rules, Boolean Matrices
Inference engine
Wizards
Simulation tools
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
6
Outline of Presentation
Project process Basics
Project Facilitation
Project Knowledge Representation and
Inferencing
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
7
Project Process Basics
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Project processes have definable
beginning and end points
Project processes have inputs consisting
of information, material, energy, etc.,
which they transform into outputs also
consisting of information, material,
energy, etc.
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
8
More Project Process Basics
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Project processes are created by higherlevel Project processes that monitor and
control their operation
Project processes report their status to
their higher-level controlling Project
processes
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
9
Implications for Project
Process Models

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They should incorporate a hierarchical
structure and include process
components and the relationship
between the processes as a minimum
Events, resources, actors, owners can
be included as the modeler requires
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
10
Process Dependency and
Project Rules
Process
2
Process
1
Process
4
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Process
3
Process
5
Dependencies can be one-to-one,
many-into-one, one-into-many, many
into many
Process dependencies are determined
by the Project RULES of the enterprise
Processes depend on other processes
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
11
Reuse..one key to faster,
cheaper project completions
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Reusable
Reusable
Reusable
Reusable
Reusable
Reusable
Reusable
requirements
project plans and budgets
functional specifications
design docs
code
test modules
knowledge
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
12
Estimation…of time and cost


The weakest link in any project, IT or
otherwise
Needed: reusable estimates of time and
cost broken down by task and adjusted
for the actual person doing the work

This is more than just a book of tables and
formulas for determining time and cost
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
13
Knowledge reuse

About techniques for faster, cheaper
completions of projects
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Crashing
Fast-tracking
Increasing parallelism
Minimizing changes to requirements
Doing it right the first time
Eliminate non-value-adding work
CODIFIED EXPERTISE is needed for all of
these
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
14
Knowledge related to
chunking
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To reduce testing time
To enhance maintainability
To reduce maintenance costs: the 1 to
3 rule
To reduce complexity

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Bug fixing time goes up exponentially with
increases in complexity
To create a plug and play landscape
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
15
Computer-codified knowledge
assistance with…

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Requirements scrubbing
Removal of safety
Management of multitasking
Management of procrastination
Increasing focus
Deciding what to measure and reward
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
16
Computer-codified knowledge
assistance with…

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Fire-fighting and expediting
Negotiations with stakeholders
Minimizing management interference
Change management
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
17
Codified knowledge of best
practices
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
18
Agenda of Best Practices

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Change Board
Daily Build and
Smoke test
Designing for
Change
Evolutionary
prototyping
Goal setting
Inspections
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Joint Applications
Development (JAD)
Lifecycle Model
Selection
Measurement
Miniature Milestones
Outsourcing
Principled
Negotiation
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
19
More best Practices
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Productivity
Environments
Rapid Development
Languages
Requirements
Scrubbing
Reuse
Signing Up
Spiral Lifecycle Model
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Staged Delivery
Theory-W Management
Throwaway Prototyping
Timebox Development
Tools Group
Top-10 Risks List
User-Interface Prototyping
Voluntary Overtime
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
20
Codified knowledge and bestpractice concepts are needed
for every knowledge area in
project management
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Scope Management
Time Management
Cost Management
Quality Management
Integration
Management
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Risk Management
Communications
Management
Procurement
management
Human Resources
Management
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
21
Measurements are a major
problem with projects
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Measurements should induce the parts to do
what is good for the system as a whole
Measurements should direct managers to the
point that needs their attention
So often it occurs that we measure the wrong
thing.
The wrong measure leads to wrong behavior

Tell me how you measure me and I will show you
how I behave
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
22
More Measurements
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
23
Project Knowledge
Representation
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
24
Knowledge representation and
Inferencing using Boolean
Algebra/Binary Matrices
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
25
Test doc
Acceptance test
plan
Implementation
doc
Code
Design doc
Functional Spec
Project plan
Requirements doc
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
26
Definitions
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A = requirements document
B = project plan and proposal
C = functional specification
D = design document
E = code
F = test document
G = acceptance test plan
H = implementation
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
27
Notation

Let eij = 1 if there is an edge directed
from i to j and 0, otherwise
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
28
Information contained in the
above can be represented as
A
A
B
C
D
E
F
G
H
B
1
C
1
1
D
E
1
F
G
H
1
1
1
1
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
29
Matrix Product
A
A
B
C
D
E
F
G
H
B
C
1
D
1
1
E
F
1
1
G
1
1
H
1
1
1
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
30
Continuous Simulation
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A way to capture behavioral and
dynamic project knowledge
And do inferencing on it
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
31
initial project
definition
Project Tasks
project is done
WP norm
work
procurement
rate
productivity max
project work
remaining
work flow
project work
completed
<project staff
size>
productivity
norm
eff staff size on
productivity
productivity
Staff
staff adj time
desired staffing
level
project staff size
effect of staff size on
productivity lookup
interactions
interaction norm
interaction max
staff adj rate
interactions lookup
Productivity
training
<Time>
training effects
lookup
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
32
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
33
Work Flow vs. People
60 project task/Month
100 person
30 project task/Month
50 person
0 project task/Month
0 person
0
work flow : anissa5
project staff size : anissa5
1
2
Time (Month)
3
4
project task/Month
person
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
34
Work Flow vs. People
100
100
project task/Month
person
50 project task/Month
50 person
0 project task/Month
0 person
0
work flow : anissa10
project staff size : anissa10
4
8
12
16
Time (Month)
20
24
project task/Month
person
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
35
A Project Blueprint Model
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
36
Project Rules—another way to
codify project knowledge

Project rules are a shorthand language
for expressing the Project knowledge
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Are the declarative scripts of the project
No matter what happens, one or more
project rules would control what happens
after that
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
37
Project Rules

Project rules are a shorthand language
for expressing the Project knowledge
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Are the declarative script of the enterprise
No matter what happens, one or more
Project rules would control what happens
after that
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
38
The Project Rules
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Any enterprise can be analyzed from a
structural perspective, a functional
perspective, and a behavioral or
dynamical perspective (also called
“viewpoint”)
Project rules apply to any and all of the
enterprise perspectives
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
39
Examples of Structural Project
Rules
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The enterprise should have a marketing
department, personnel department, finance
department, accounting department, and
customer service department. (Organization
rule)
Annual Total Profit = Annual Total Revenue –
Annual Total Expense (Entity definition)
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
40
Examples of Functional Rules

Functional rules are the rules that specify the
goals and objectives of the enterprise.
Basically, they collectively define the “what
should be done (by whom)”. Examples of
these rules are:


The enterprise should maintain at least 35% of
the domestic market of product A.
The management of human resources is the
responsibility of the managers throughout the
company (as opposed to being established as a
separate organizational unit)
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
41
Behavioral Project Rules
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Used to control the preconditions and postconditions of the state changes of the
enterprise
The form is…
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When certain events occur and/or certain
conditions hold true, then other events are
triggered and the system undergoes state change
Clearly, there is a “chain of events” that gives
rise to certain observed behaviors
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
42
A Simplified Project Process
Model (SBPM)

Purpose is to capture relationships
between sub processes represented as
nodes
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Such relationships exist when there is a
triggering control sequence of events
between the sub process nodes
There is a temporal sequence that we
shall represent with a directed link
between the sub process nodes
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
43
The SBPM is a Form of
Knowledge Representation
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The domain knowledge K consists of
two components—the set V of Project
process nodes and sub process nodes
The set E of relationships among the
nodes; thus
K = <V,E>; i.e., K is a dyad of V and E
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
44
A Simplified Project Process
Model (Diagram)
Process
2
Process
1
Process
4
Process
3
Process
5
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
45
Process Node Architecture
Components
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A task function that provides the
services expected to be done at this
node
An actor who is in charge of or
responsible for the services of this node
Information storage for input/output
of locally stored information
Information throughput capability
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
46
Process Node Architecture Diagram
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
47
Connectionist Approach to Project
Knowledge Inferencing
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The network of process nodes will have
a mesh topology and might contain
loops or cycles
The topology is a hierarchical one as
exhibited in the following…
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
48
Design Principles for Project
Knowledge System (PKS)
Target/Output Layer
Process Nodes
Intermediate
Layers
Source/Input Layer
Process Nodes
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
49
Design Principles for PKS,
Continued
(1) Is a network representation of processing
knowledge
(2) Represents the relative importance of the
sub-process over the whole Project process
(3) Represents the influence of process nodes
by weight values
(4) One-node-one-process representation (nondistributed representation)
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
50
Design Principles for PKS,
Continued
(5) Layered network will be both acyclic
and cyclic, depending upon the specific
type of analysis being applied
(6) Knowledge reasoning is accomplished
by inferencing
(7) Knowledge updating is by learning
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
51
Initialization of PKS knowledge
network
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Requires data (a specific set of inputs
and outputs)
Utilizes a learning algorithm
Determines the weights attached to all
of the connections, links between the
nodes
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
52
Inference
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1. Forward-chaining computation:
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2. Backward-chaining computation

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Find the effect of input/source process nodes;
Calculating the Performance Factor of the target
process nodes;
Find the causes or causal paths for a (or set of)
target process node (probably which is a
problematic one); and
Produce justifications/explanations for
the conclusion
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
53
Other inferencing schemes

Use of large sparse matrices and
Boolean matrix algebra as reported in
IEEE Trans on Sys, Man & Cyber,
Vol. SMC-19, No. 1, pp. 58-68, January
1989. (Burns, et al.)
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
54
Successful Applications

A managerial knowledge network
(Decision Support Systems, North
Holland Press, 1993—Jung, Burns)
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
55
Learning

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Humans learn from experience
This entails building and updating their
knowledge structures
PKS learns in a similar manner
Initially, the Generalized Delta Rule or back
propagation method will be utilized
This is the most important and most widely
used algorithm for connectionist learning
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
56
Analysis of the Discovered
Knowledge Network

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Can use simulation and system
dynamics to assess and understand
performance
Value analysis will be performed on the
knowledge network

Process value analysis has its origins in
total quality management
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
57
More analysis of the
Knowledge Network


Can perform carbon/silicon replacement
analysis
Can compare the knowledge network
with the original enterprise model
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
58
Simulation and System
Dynamics


To understand why a particular behavior
is being exhibited
To conduct “What if” experiments to
see if there are better structures that
will produce more desirable behavior
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
59
A Dynamic Process Model
fraction facilities ready
Orders in
Process
orders
target process delay
Orders Requiring
Testing
processing
<TIME STEP>
testing
<TIME STEP>
target test delay
Testing
Capacity
start orders
test adj time
Processing
Capacity
fraction facilities good
Orders Requiring
Service
proc adj time
target service delay
<TIME STEP>
dispatching
target activation
delay
Dispatching
Capacity
dispatch adj time
Activating
Capacity
Awaiting
Activation
activating
New
Customers
activation adj time
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
60
Behavior of the Dynamic
Process Model
Orders in different States
250
125
0
0
10
20
30
40
50
60
Time (Day)
70
80
90
Orders in Proces s
Orders Requiring Testing
Orders Requiring Service
Orders Await ing Activation
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
100
Line
Line
Line
Line
61
Process Value Analysis

Might find that some nodes add no value
and that a simpler network might achieve
the same process outputs or results at
lower cost and shorter cycle times, indeed
even better quality
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
62
Summary


A project Knowledge base and inference
schemes are badly needed to codify
project knowledge
Several knowledge representation and
inferencing schemes were investigated



Boolean algebra/binary matrices
Rules
Knowledge network
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
63
Summary, Cont’d

Such a system would

Produce a basis for continuous learning and
improvement
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
64
Questions??!?

Thank you for coming!!
Burns & Ulgen, Fully Supporting the PM Lifecycle -- USP
Conference -- September 2003
65