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Importance of Project Management
• Projects represent change and allow organizations toeffectively introduce new products, new
process, new programs
• Project management offers a means for dealing withdramatically reduced product cycle times
• Projects are becoming globalized making them moredifficult to manage without a formal methodology
• Project management helps cross-functional teams to be more effective
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Management of IT Projects
• More than $250 billion is spent in the US each year onapproximately 175,000 information technology projects.
• Only 26 percent of these projects are completed on time andwithin budget.
• The average cost for a development project for a large companyis more than $2 million.
• Project management is an $850 million industry and is expectedto grow by as much as 20 percent per year.
Bounds, Gene. “The Last Word on Project
Management” IIE Solutions, November, 1998.
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What Defines a Project?
•
•
• •
•
•
•
How does a project
differ from a
program?
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Project Management versus Process Management
“Ultimately, the parallels between process and projectmanagement give way to a fundamental difference: process management seeks to eliminate variabilitywhereas project management must accept variability
because each project is unique.”
Elton, J. & J. Roe. “Bringing Discipline to Project
Management” Harvard Business Review, March-April,
1998.
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Measures of Project Success
•
•
• •
•
•
•
Was the movie
“Titanic”
a success?
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Delayed Openings are a Fact of Life in the Foodservice,
Hospitality Industry
Disney's shipbuilder was six months late in delivering its new cruise ships,and thousands of customers who had purchased tickets were stranded.
Even with that experience, their second ship was also delivered well after the
published schedules. Universal Studios in Orlando, Fla. had been building a
new restaurant and entertainment complex for more than two years. They
advertised a December opening, only to announce in late November that it
would be two or three months late.
Even when facilities do open close to schedule, they are rarely finished
completely and are often missing key components. Why do those things
happen? With all of the sophisticated computers and project management
software, why aren't projects completed on schedule?
Frable, F. Nation's Restaurant News (April 12, 1999)
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IT Project Outcomes
More than 200%
late
Cancelled
On-Time
Less than 20%
late
21-50% late
51-100% late
101-200% late
26%
29%
6%
16%
9%
8%
6%
Source: Standish Group Survey, 1999 (from a
survey of 800 business systems projects)
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Why do Projects Fail?
Studies have shown that the following factorscontribute significantly to project failure:
• Improper focus of the project management system
• Fixation on first estimates
• Wrong level of detail
• Lack of understanding about project management tools; too much
reliance on project management software
• Too many people
• Poor communication
• Rewarding the wrong actions
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Why do IT Projects Fail?
• Ill-defined or changing requirements
• Poor project planning/management
• Uncontrolled quality problems
• Unrealistic expectations/inaccurate estimates
• Naive adoption of new technology
Source: S. McConnell, Construx Software Builders, Inc.
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QuickTime™ and aPhoto - JPEG decompressor
are needed to see this picture.
Have You Ever Lost Sight of theProject Goals?
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Not all Projects Are Alike…
“[in IT projects], if you ask people what‟s done and what remains to be
done there is nothing to see. In an IT project, you go from zero to 100
percent in the last second--unlike building a brick wall where you can see
when you‟re halfway done. We‟ve moved from physical to non-physical
deliverables….”
J. Vowler (March, 2001)
Engineering projects = task-centric
IT projects = resource-centric
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Shenhar’s Taxonomy of Project Types
De g ree o f U n cert ain t y/ R isk
Sys tem C o m pl e xi t y/S c op e
H ig h
Low -
T e c h
A s s em b l y P ro ject s
A rr ay P ro ject s
Sy st e m P ro ject s
M e d i um- T e c h
H ig h- T e c h
S u p e r Hi gh - T e c h
Co n s tr u ct io n
N e w c e ll pho n e
N e w s h r i n k - w r ap p e d so ftw ar e
ER P im p l e me n t a ti on i n m u lti- na ti ona l
fi r m
A ut o r e pa ir
A d van c e d r ada r sy st e m
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Project Life Cycle
Time Phase 1 Phase 2 Phase 3 Phase 4Formation & Planning Scheduling & Evaluation &Selection Control Termination
R e q u i r e d R e s o u r
c e s
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Life Cycle Models: Pure Waterfall
ConceptDesign
Requirements
Analysis
Architecture
Design
Detailed
Design
Coding &
Debugging
System
Testing
Source: S. McConnell
Rapid Development (Microsoft Press, 1996)
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Life Cycle Models: Code & Fix
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Design, Cost, Time Trade-offs
Target
COST
D E S I G N
Due Date
Budget
Constraint
Optimal Time-Cost
Trade-off
Required
Performance
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Optional Scope Contracts
Fixed Scope Contract specifies SCHEDULE, COST, SCOPE
Optional Scope Contract specifies SCHEDULE, COST, QUALITY
(general design guidelines may be indicated)
Since it is widely accepted that you can select
three of the four dimensions (or perhaps only
two), what to do?
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Importance of Project Selection
“There are two ways for a business to succeed
at new products: doing projects right, and
doing the right projects.”
Cooper, R.G., S. Edgett, & E. Kleinschmidt.
Research • Technology Management , March-April, 2000.
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Project Initiation & Selection
• Critical factors 1) Competitive necessity
2) Market expansion
3) Operating requirement
• Numerical Methods 1) Payback period
2) Net present value (NPV) or Discounted Cash Flow (DCF)
3) Internal rate of return (IRR)
4) Expected commercial value (ECV)
• Project Portfolio 1) Diversify portfolio to minimize risk
2) Cash flow considerations
3) Resource constraints
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Payback Period
Number of years needed for project to
repay its initial fixed investment
Example: Project costs $100,000 and is expected
to save company $20,000 per year
Payback Period = $100,000 / $20,000 = 5 years
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Net Present Value (NPV)
Discounted Cash Flow (DCF)
Let Ft = net cash flow in period t (t = 0, 1,..., T)
F 0 = ini tial cash investment in time t = 0
r = discount rate of return (hurdle rate)
NPV =
Ft
1 + r t•t = 0
T
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Internal Rate of Return (IRR)
Find value of r such that NPV is equal to 0
F0 + F1
1 + r + F2
1 + r 2= 0
Example (with T = 2):
Find r such that
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DCF Project Example*
*Hodder, J. and H.E. Riggs. “Pitfalls in Evaluating Risky Projects”, Harvard
Business Review, Jan-Feb, 1985, pp. 128-136.
Product
Demand Product Life
Annual Net
Cash Inflow Probability
High 20 years $24 million 0.3
Medium 10 years $12 million 0.5
Low Abandon Project None 0.2
Phase I Research and Product De velopment
$18 million annual research cost for 2 years60% probability of succ ess
Phase II Market Development
Undertaken only if product development is succes sful
$10 million annual expenditure for 2 years to develop marketing and
distribution c hannels (net of any revenues earned in tes t marketi
Phase III SalesProceeds only if Phase I and I I verify opportunity.
Production is subcontracted and all cash flows are after-tax and occu
at year's end.
The results of Phase II (available at the end of year 4) identify the
product's mar ket po tential as indic ated below:
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DCF Project Example (cont’d)
Year Expe cte d Cash Flow (in $ million)
1 -18
2 -18
3 0.6 (-10) = -
4 0.6 (-10) = -5 - 14 .6 (0.3 x 24 + 0.5 x 12) = 7.92
15 - 24 .6 (0.3 x 24) = 4.32
What is the internal rate of return for this project?
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DCF Example Continued
What if you can sell the product (assuming that both Research and
Product Development AND Market Development are successful) to a
third party? What are the risks AT THAT POINT IN TIME?
Assume that discount rate r 2 is 5%
Probability
What is 20 years of cash inflow at $24M/year? $299.09 0.3
What is 10 years of cash inflow at $12M/year? $92.66 0.5
Expected value of product at Year 4: $136.06
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DCF Example Continued
Expected cash flows (with sale of product at end of year 4) are now:
Outflow Inflow Net Probability
Expe cted
Cash Flow
Year 1 18.00$ (18.00)$ 1 (18.00)$
Year 2 18.00$ (18.00)$ 1 (18.00)$Year 3 10.00$ (10.00)$ 0.6 (6.00)$
Year 4 10.00$ 136.06$ 126.06$ 0.6 75.63$
What is the internal rate of return for this project?
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Criticisms of NPV/DCF
1) Assumes that cash flow forecasts are accurate; ignoresthe “human bias” effect
2) Fails to include effects of inflation in long term
projects
3) Ignores interaction with other proposed and ongoing
projects (minimize risk through diversification)
4) Use of a single discount rate for the entire project (risk
is typically reduced as the project evolves)
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Expected Commercial Value (ECV)
Develop New
Product
Technical Failure
Technical Success
Probability = pt
Probability = 1 - pt
Launch New
Product
Commercial
Failure (with net
benefit = 0)
Commercial Success
(with net benefit =
NPV)
Probability = pc
Probability = 1 - pc
Risk class 1 Risk class 2
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DCF Example Revisited
Discount rate r 1 Discount rate r 2
Research &
Product
Development
Development
Succeeds
Probability = pt
Development Fails
Probability = 1 - pt
Market
Development
Product Demand
High 0.3
Product Demand
Medium
Product Demand
Low
0.5
0.2
Drop project
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Ranking/Scoring ModelsProfitability/value
1) Increase in profitability?2) Increase in market share?3) Will add knowledge to organization that can be leveraged by other projects?4) Estimated NPV, ECV, etc.
Organization's Strategy1) Consistent with organization's mission statement?2) Impact on customers?
Risk 1) Probability of research being successful?2) Probability of development being successful?3) Probability of process success?4) Probability of commercial success?5) Overall r isk of project6) Adequ ate market demand?7) Competitors in market
Organizat ion Costs
1)
Is new facilit y needed?2) Can use current personnel?3) External consultants needed?4) New hires needed?
Miscellaneous Factors1) Impact on environmental standards?2) Impact on workforce safety?3) Impact on quality?4) Social/political implications
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Scoring Attributes
vi xi =1 - exp L - xi
1 - exp L - U.
To convert various measurement scales to a (0, 1) range….
LINEAR SCALE: value of attribute i is
EXPONENTIAL SCALE: value of attribute i is
vi xi =xi - L
U - L
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
1 2 3 4 5 6 7
Res ponse
Linear Scale
Exponential Scale
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Ranking/Scoring Example
Attribute Measurement ScaleAttribute
Weight (wi)
1) Does project increase market share? unlikely likely 30%
2) Is new facilit y needed? yes no 15%
3) Are there safety concerns? likely unsure no 10%
4) Likeli hood o f successful t echnical development? unlikely likely 20%
5) Likelihood of successful commercial development? unlikely likely 25%
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
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Attribute #1 #2 #3 #4 #5
Project
Score (V j)
Project A 4 yes likely 4 1
Project B 2 no unsure 3 4
Linear ScaleProject A 0.75 0.25 0 0.75 0 0.413
Project B 0.25 0.75 0.5 0.5 0.75 0.525
Exponential ScaleProject A 0.97 0.64 0.00 0.97 0.00 0.581
Project B 0.64 0.97 0.88 0.88 0.97 0.845
Ranking/Scoring Example (cont’d)
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Analyzing Project Portfolios: Bubble Diagram
Expected NPV
Prob of Commercial Success
High Zero
Low
High
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Analyzing Project Portfolios: Product vs Process
Extent of Process Change
Source: Clark and Wheelwright, 1992
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Key Elements of Project Portfolio Selection Problem
1. Multi-period investment problem
2. Top management typically allocates funds to different
product lines (e.g., compact cars, high-end sedans)
3. Product lines sell in separate (but not necessarilyindependent) market segments
4. Product line allocations are changed frequently
5. Conditions in each market segment are uncertain from
period to period due to competition and changing
customer preferences
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“Stage-Gate” Approach
Installation Plan
Facility Prep
Training Plan
Implementation
Detail Design
Schedule & Budget
Contingency Plan
Product &
Performance Reviews
Initiation Define Design ControlImprove
Work Statement
Risk Assessment
Purchasing Plan
Change Mgt
Initiation
Project Review
Charter
Source: PACCAR Information Technology Division
Renton, WA
Production close-out
Lessons learned
Post-project audit
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Project Selection Example
Y e a r (t)
1 2 3 4
Project A ($40) $10 $20 $20
Project B ($65) ($25) $50 $50Budget
Limit (B t ) $120 $20 $40 $55
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Phases of Project Management
n Project formulation and selection
n Project planningu Summary statement
u Work breakdown structure
u Organization plan
u risk management
u
Subcontracting and bidding processn Project scheduling
u Time and schedule
u Project budget
u Resource allocation
u Equipment and material purchases
n Monitoring and controlu Cost control metrics
u Change orders
u Milestone reports
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Project Planning
n
Summary Statementu Executive summary: mission and goals, constraints
u Description and specifications of deliverables
u Quality standards used (e.g., ISO)
u Role of main contractor and subcontractors
u Composition and responsibilities of project team
n Organization Planu Managerial responsibilities assigned; signature authority
u Cross impact matrix (who works on what)
u Relationship with functional departments
u Project administration
u Role of consultants
u Communication procedures with organization, client, etc.
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Importance of Project Planning
The 6P Rule of Project Management:
Prior Planning Prevents Poor Project
Performance
“If you fail to plan, you will plan to fail”
Anonymous
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Work Breakdown Structure (WBS)
1) Specify the end-item “deliverables”
2) Subdivide the work, reducing the dollars and
complexity with each additional subdivision
3) Stop dividing when the tasks are manageable “work packages” based on the following:
• Skill group(s) involved
• Managerial responsibility
• Length of time
• Value of task
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Work Packages/Task Definition
The work packages (tasks or activities) that are defined
by the WBS must be:
• Manageable
• Independent
• Integratable
• Measurable
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Design of a WBS
“The usual mistake PMs make is to lay out too many tasks;subdividing the major achievements into smaller and
smaller subtasks until the work breakdown structure
(WBS) is a „to do‟ list of one-hour chores. It‟s easy to get
caught up in the idea that a project plan should detaileverything everybody is going to do on the project. This
springs from the screwy logic that a project manager‟s job
is to walk around with a checklist of 17,432 items and tick
each item off as people complete them….”
The Hampton Group (1996)
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Two-Level WBS
1. Charity Auction
1.1 Event
Planning
1.2 Item
Procurement
1.3 Marketing 1.4. Corporate
Sponsorships
WBS level 1
WBS level 2
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Three-Level WBS
1.1 Event
Planning
1.2 Item
Procurement
1.3 Marketing
1. Charity Auction
1.4 Corporate
Sponsorships
1.1.1 Hire Auctioneer
1.1.2. Rent space
1.1.3 Arrange for decorations
1.2.1 Silent
auction items
1.2.2 Live auction
items
1.2.3 Raffle items
1.3.1 Individual
ticket sales
1.3.2 Advertising
1.1.4 Print catalog
WBS level 1
WBS level 2
WBS level 3
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Estimating Task Durations (cont’d)
• Benchmarking
• Modular approach
• Parametric techniques
• Learning effects
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Beta Distribution
Completion time of task j
Optimistic Timet jo
Pessimistic Time t j p
Time
Probability density
function
Expected duration =Most Likely Time = tm
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Beta Distribution
For each task j, we must make three estimates:
most optimistic time
most pessimistic time
most likely time
t jo
t j p
t jm
Expected duration j =t jo + t j
p + 4t jm
6
Variance of task j = j2 = t j
p
- t jo 2
36
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Estimating Task Durations: Painting a Room
Task : Paint 4 rooms, each is approximately 10‟ x 20‟. Use flat paint on walls,
semi-gloss paint on trim and woodwork. Each room has two doors and four
windows. You must apply masking tape before painting woodwork around thedoors and windows. Preparation consists of washing all walls and woodwork
(some sanding and other prep work will be needed). Only one coat of paint is
necessary to cover existing paint. All supplies will be provided at the start of the
task. Previous times on similar painting jobs are indicated in the table below.
hours min hours min
27 25 31 52
38 25 19 1533 12 26 27
17 44 30 27
26 7 25 21
22 1 24 28
14 2 32 58
30 27 32 1
28 30 13 43
21 13 42 45
23 59 22 57
27 44 32 1523 15 32 31
37 6 27 15
17 54 26 11
17 13 21 52
What is your estimate of the average time you will
need? What is your estimate of the variance?
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Estimating Task Durations with Incentives
Task: Consider the painting job that you have just estimated. Now, however, there are
explicit incentives for meeting your estimated
times. If you finish painting the room before
your specified time, you will receive a $10
bonus payment. HOWEVER, if you finish
the painting job after your specified time, you
will be fined $1000. Revised estimated time =
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Estimating Task Durations with Incentives
Task: Consider the painting job that you have just estimated. Now, however, there are
explicit incentives for meeting your estimated
times. If you finish painting the room before
your specified time, you will receive a $10
bonus payment. If you finish the painting job
after your specified time, there is no penalty.
Revised estimated time =
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Role of Project Manager/Team
Project Manager
Client
Subcontractors
Regulating
Organizations
Project Team
Functional
Managers
Top
Management
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Responsibilities of a Project Manager
To the organization and top management
• Meet budget and resource constraints
• Engage functional managers
To the project team • Provide timely and accurate feedback
• Keep focus on project goals • Manage personnel changes
To the client• Communicate in timely and accurate manner
• Provide information and control on changes/modifications
• Maintain quality standards
To the subcontractors • Provide information on overall project status
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Project Team
What is a project team?
A group of people committed to achieve a
common set of goals for which they hold
themselves mutually accountable
Characteristics of a project team
• Diverse backgrounds/skills
• Able to work together effectively/develop synergy
• Usually small number of people • Have sense of accountability as a unit
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“I design user interfaces to please an audience of one.
I write them for me. If I’m happy, I know some cool
people will like it. Designing user interfaces by
committee does not work very well; they need to becoherent. As for schedule, I’m not interested in
schedules; did anyone care when War and Peace came
out?”
Developer, Microsoft Corporation As reported by MacCormack and Herman, HBR Case 9-600-097:
Microsoft Office 2000
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Intra-team Communication
M = Number of project team membersL = Number of links between pairs of team members
If M =2, then L = 1
If M =3, then L = 3
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Number of Intra-team Links
L = Number of Intra-team Links = N
2=
N(N-1)
2
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Importance of Communication
On the occasion of a migration from the east, men discovered aplain in the land of Shinar, and … said to one another, “Come, let
us build ourselves a city with a tower whose top shall reach the
heavens….” The Lord said, …“Come, let us go down, and there
make such a babble of their language that they will not
understand one another’s speech.” Thus, the Lord dispersedthem from there all over the earth, so that they had to stop
building the city.
Genesis 11: 1-8
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Project Performance and Group Harmony
Two schools of thought:
1) “Humanistic school” -- groups that have positivecharacteristics will perform well
2) “Task oriented” school -- positive group
characteristics detract from group performance
What is the relationship between the design of multidisciplinary project teams and project success?
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Project Performance and Group Harmony (cont’d)
Experiment conducted using MBA students at UW and
Seattle U using computer based simulation of pre-operationaltesting phase of nuclear power plant*
Total of 14 project teams (2 - 4 person project teams) with atotal of 44 team members; compared high performance (low
cost) teams vs low performance (high cost) teams
Measured: Group Harmony
Group Decision Making Effectiveness
Extent of Individual‟s Contributions to Group
Individual Attributes
*Brown, K., T.D. Klastorin, & J. Valluzzi. “Project Management
Performance: A Comparison of Team Characteristics”, IEEE Transactions on
Engineering Management , Vol 37, No. 2 (May, 1990), pp. 117-125.
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Group Harmony: High vs Low Performing Groups
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Extent of Individual Contribution: High vs LowPerforming Groups
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Decision Making Effectiveness: High vs LowPerforming Groups
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Project Organization Types
• Functional: Project is divided and assigned to appropriate functional
entities with the coordination of the project being carried out by
functional and high-level managers
• Functional matrix: Person is designated to oversee the project
across different functional areas
• Balanced matrix: Person is assigned to oversee the project and
interacts on equal basis with functional managers
• Project matrix: A manager is assigned to oversee the project and is
responsible for the completion of the project
• Project team: A manager is put in charge of a core group of
personnel from several functional areas who are assigned to the
project on a full-time basis
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Project Organization Continuum
Project Team
Organization
Project Matrix
Project fully managed
by functional managers Project fully managed by
project team manager
FunctionalOrganization
Functional Matrix
Balanced Matrix
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A Business School as a Matrix Organization
Dean
Associate Dean for
Undergraduate
Program
Associate Dean for
MBA Programs
Director of
Doctoral Program
Accounting
Department Chair
Marketing
Department Chair
Finance Department
Chair
Gloria
Diane
Bob
Zelda Larry
Curly
Moe
Barby
Leslie
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Matrix Organizations & Project Success
• Matrix organizations emerged in 1960‟s as analternative to traditional means of project
teams
• Became popular in 1970‟s and early 1980‟s
• Still in use but have evolved into many different
forms
• Basic question: Does organizational structure
impact probability of project success?
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Organizational Structure & Project Success• Studies by Larson and Gobeli (1988, 1989)
• Sent questionnaires to 855 randomly selected PMI members
• Asked about organizational structure (which one best describes the primary
structure used to complete the project)
• Perceptual measures of project success: successful, marginal, unsuccessful
with respect to :
1) Meeting schedule2) Controlling cost
3) Technical performance
4) Overall performance
• Respondents were asked to indicate the extent to which they agreed with
each of the following statements:1) Project objectives were clearly defined
2) Project was complex
3) Project required no new technologies
4) Project had high priority within organization
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• Classification of 547 respondents (64% response rate)
30% project managers or directors of project mgt programs16% top management (president, vice president, etc.)
26% managers in functional areas (e.g., marketing)
18% specialists working on projects
• Industries included in studies
14% pharmaceutical products10% aerospace
10% computer and data processing products
others: telecommunications, medical instruments, glass products,software development, petrochemical products, houseware goods
• Organizational structures:
13% (71): Functional organizations
26% (142): Functional matrix
16.5% (90): Balanced matrix
28.5% (156): Project matrix
16% (87): Project team
Study Data
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ANOVA Results by Organizational Structure
Controlling
Cost
Meeting
Schedule
Technical
Performance
Overall
Results
Organizational Structure N Ave (SD) Ave (SD) Ave (SD) Ave (SD)
A
Functional
Organization 71 1.76 (.83) 1.77 (.83) 2.30 (.77) 1.96 (.84)
B Functional Matrix 142 1.91 (.77) 2.00 (.85) 2.37 (.73) 2.21 (.75)
C Balanced Matrix 90 2.39 (.73) 2.15 (.82) 2.64 (.61) 2.52 (.61)
D Project Matrix 156 2.64 (.76) 2.30 (.79) 2.67 (.57) 2.54 (.66)
E Project Team 87 2.22 (.82) 2.32 (.80) 2.64 (.61) 2.52 (.70)
Total Sample 546 2.12 (.79) 2.14 (.83) 2.53 (.66) 2.38 (.70)
F-statistic 10.38* 6.94* 7.42* 11.45*
Scheffe Results
A,B < C,D,E
E < D A, B < C < D,E A, B < C,D, E A, B < C,D, E
*Statisticall y signif icant at a p<0.01 level
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Summary of Results
• Project structure significantly related to project success
• New development projects that used traditional functional organization
had lowest level of success in controlling cost, meeting schedule,
achieving technical performance, and overall results
• Projects using either a functional organization or a functional matrix had
a significantly lower success rate than the other three structures
• Projects using either a project matrix or a project team were more
successful in meeting their schedules than the balanced matrix
• Project matrix was better able to control costs than project team
• Overall, the most successful projects used a balanced matrix, project
team, or--especially--project matrix
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Subcontracting = Business Alliance
n When you subcontract part (or all) of a
project, you are forming a business
alliance....
Intelligent Business Alliances: “A business relationship for
mutual benefit between two or more parties with compatible
or complementary business interests and/or goals”
Larraine Segil, Lared Presentations
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Communication and Subcontractors
How is knowledge
transferred?
What types of communication mechanism(s) will be
used between company and subcontractor(s)?
WHAT a companycommunicates.....
HOW a companycommunicates.....
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Personality Compatibility
Corporate
Personality
Subcontractor
Personality
Individual
Personality
Project
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Subcontracting Issues
n• What part of project will be subcontracted? n• What type of bidding process will be used? What type of
contract?
n• Should you use a separate RFB (Request for Bids) for
each task or use one RFB for all tasks?n• What is the impact on expected duration of project?
n• Use a pre-qualification list?
n• Incentives? Bonus for finishing early? Penalties for
finishing after stated due date?
• What is impact of risk on expected project cost?
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Basic Contract Types
n Fixed Price Contract u Client pays a fixed price to the contractor irrespective of actual audited
cost of project
n Cost Plus Contract
u Client reimburses contractor for all audited costs of project (labor, plant,& materials) plus additional fee (that may be fixed sum or percent of costs
incurred)
n Units Contract
u Client commits to a fixed price for a pre-specified unit of work; final
payment is based on number of units produced
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Incentive (Risk Sharing) Contracts
General Form:Payment to Subcontractor = Fixed Fee + (1 - B) (Project Cost)
where B = cost sharing rate
Cost Plus Contract
B = 0 B = 1
Fixed Price Contract
Linear & Signalling
Contracts
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Why Use Incentive Contracts?
Expected Cost of Project = $100MTwo firms bid on subcontract
Firm 1 Firm 2
Fixed Fee (bid) $5 M $7 M
Project Cost $105 M $95 M
(inefficient producer)
What is result if Cost Plus Contract (B = 0) used?
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Washington State Bid Code (WAC 236-48-093)
n WAC 236-48-093: A contract shall be awarded to the lowest responsible and responsive
bidder based upon, but not limited to, the following criteria where applicable and onlythat which can be reasonably determined:
n 1) The price and effect of term discounts...price may be determined by life cycle costing
if so indicated in the invitation to bid
n 2) The conformity of the goods and/or services bid with invitation for bid or request for
quotation specifications depicting the quality and the purposes for which they are
required.n 3) The ability, capacity, and skill of the bidder to perform the contract or provide the
services required.
n 4) The character, integrity, reputation, judgement, experience, and efficiency of the
bidder.
n 5) Whether the bidder can perform the contract with the time specified.
n 6) The quality of performance on previous contracts for purchased goods or services.n 7) The previous and existing compliance by the bidder with the laws relating to the
contract for goods and services.
n 8) Servicing resources, capability, and capacity.
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Competitive Bidding: Low-Bid System
n “In the low-bid system, the owner wants the most building for the least money, while the contractor wants the least building for the most money. Thetwo sides are in basic conflict.”
Steven Goldblatt
Department of Building Construction
University of Washington
The Seattle Times, Nov 1, 1987
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Precedence Networks
Networks represent immediate precedence relationshipsamong tasks (also known as work packages or activities)
and milestones identified by the WBS
Milestones (tasks that take no time and cost $0 but indicate
significant events in the life of the project) Two types of networks: Activity-on-Node (AON)
Activity-on-Arc (AOA)
All networks: must have only one (1) starting and one (1)ending point
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Precedence Networks: Activity-on-Node (AON)
A
B
C
D
Start End
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Precedence Diagramming
Standard precedence network (either AOA or AON) assumes that a successor
task cannot start until the predecessor(s) task(s) have been completed.Alternative relationships can be specified in many software packages:
Finish-to-start (FS = a): Job B cannot start until a days after Job A is
finished
Start-to-start (SS = a): Job B cannot start until a days after Job A hasstarted
Finish-to-finish (FF = a): Job B cannot finish until a days after Job A
is finished
Start-to-finish (SF = a): Job B cannot finish until a days after Job A
has started
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Critical Path Method (CPM): Basic Concepts
Task A
7 months
Task B
3 months
End
Task C
11 months
Start
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Critical Path Method (CPM): Basic Concepts
Start
Task A
7 months
Task B
3 months
Task C
11 months
End
ESStart = 0
LFStart = 0
ESA = 0
LFA = 8
ESB = 7
LFB = 11
ESC = 0
LFC = 11
ESEnd = 11
LFEnd = 11
ES j = Earliest starting time for task (milestone) j
LF j = Latest finish time for task (milestone) j
AON P d N t k Mi ft P j t
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AON Precedence Network: Microsoft Project
Start
1 0d
Wed 12/20/00 Wed 12/20/00
Ta sk A
2 7d
Wed 12/20/00 Thu 12/28/00
Task C
4 11d
Wed 12/20/00 Wed 1/3/01
End
5 0d
Wed 1/3 /0 1 Wed 1/3 /0 1
Ta sk B
3 3d
Fri 12/29 /00 Tue 1 /2 /01
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Critical Path Method (CPM): Example 2
Ta sk A 14 w k s
Ta sk D
12 w k s
Ta sk E 6 w k s
Ta sk B 9 w k s
Ta sk C 20 w k s
Ta sk F 9 w k s
START END
ES F = LF F =
ES D = LF D =
ES ST ART = 0LFST ART = 0
ES A = LF A =
ES B = LF B =
ES END = LF END =
ES C = LF C =
ES E = LF E =
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Example 2: Network Paths
Path Tasks
Expected
Duration (wks)
1 START-A-D-F-END 35
2 START-A-D-E-END 323 START-B-D-F-END 30
4 START-B-D-E-END 27
5 START-C-E-END 26
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Example 2: CPM Calculations
E A R L I E S T L A T E S T
Task or
Milestone
Duration
( )
Start Time
(ESi) Finish Time Start Time
Finish Time
(LFi)
ST ART 0 0 0 0 0
A 14 0 14 0 14
B 9 0 9 5 14C 20 0 20 9 29
D 12 14 26 14 26
E 6 26 32 29 35
F 9 26 35 26 35
END 0 35 35 35 35
ti
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Example 2: Calculating Total Slack (TSi)
Task or
Milestone
Duration
( )
Earliest
Start Time
(ESi)
Lastest
Finish Time
(LFi)
Total Slack
(TSi)
Critical
Task?
ST ART 0 0 0 0 YesA 14 0 14 0 Yes
B 9 0 14 5 No
C 20 0 29 9 No
D 12 14 26 0 Yes
E 6 26 35 3 No
F 9 26 35 0 Yes
END 0 35 35 0 Yes
ti
Total Slack for task i = TSi = LFi - ESi - ti
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Slack (Float) Definitions (for task i)
Total Slack (TSi) = LF
i
- ESi
- ti
Free Slack (FSi) = ESi,min - ESi - ti
where ESi,min = minimum early start time of all tasks that
immediately follow task i
= min (ES j for all task j Si)
Safety Slack (SSi) = LFi - LFi,max - ti
where LFi,max = maximum late finish time of all tasks that
immediately precede task i
= min (LF j for all task j Pi)
Independent Slack (ISi) = max (0, ESi,min - LFi,max - ti)
E l #2 LP M d l
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Example #2: LP Model
Decision variables: START j = start time for task j
END = ending time of project (END milestone)
Minimize END
subject to
STARTj ≥ FINISHi for all tasks i that immediately precede task j
STARTj ≥ 0 for all tasks j in project
where FINISHi = STARTi + ti = STARTi + duration of task i
E l #2 E l S l M d l
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Example #2: Excel Solver Model
Gantt Chart
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Gantt Chart
Microsoft Project 4.0
P j t B d ti
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Project Budgeting• The budget is the link between the functional units and the project
• Should be presented in terms of measurable outputs
• Budgeted tasks should relate to work packages in WBS and
organizational units responsible for their execution
• Should clearly indicate project milestones
• Establishes goals, schedules, and assigns resources (workers,
organizational units, etc.)
• Should be viewed as a communication device
• Serves as a baseline for progress monitoring & control
• Update on rolling horizon basis
• May be prepared for different levels of aggregation (strategic,
tactical, short-range)
P j t B d ti ( t’d)
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Project Budgeting (cont’d)
• Top-down Budgeting: Aggregate measures (cost,
time) given by top management based on
strategic goals and constraints
• Bottom-up Budgeting: Specific measures aggregated
up from WBS tasks/costs and subcontractors
I i P j t B d t
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Issues in Project Budgets
• How to include risk and uncertainty factors?
• How to measure the quality of a project budget?
• How often to update budget?
• Other issues?
C iti l P th M th d (CPM) E l 2
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Critical Path Method (CPM): Example 2
Ta sk A 14 w k s
Ta sk D
12 w k s
Ta sk E 6 w k s
Ta sk B 9 w k s
Ta sk C 20 w k s
Ta sk F 9 w k s
START END
ES F = 26 LF F = 35
ES D = 14 LF D = 26
ES ST ART = 0LFST ART = 0
ES A = 0
LF A = 14
ES B = 0 LF B = 14
ES END = 35 LF END = 35
ES C = 0 LF C = 29
ES E = 26 LF E = 35
P j t B d t E l
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Project Budget Example
Task or
Milestone
Duration
(tj)
Early Start
Time (ESj)
Latest Start
Time (LSj)
No. of
Resource A
workers
No. of
Resource B
workers
Material
Costs
Direct Labor
Cost/wk
Labor +
Materials
ST ART 0 0 0 - - - - -
A 14 0 0 2 0 340$ 800$ 1,140$
B 9 0 5 4 12 125$ 8,800$ 8,925$
C 20 0 9 3 14 -$ 9,600$ 9,600$
D 1214 14 0 8 200$ 4,800$ 5,000$
E 6 26 29 1 0 560$ 400$ 960$
F 9 26 26 4 10 90$ 7,600$ 7,690$
END 0 35 35 - - - - -
Cost for Resource A worker = $400/week
Cost for Resource B worker = $600/week
P j t B d t E l ( t’d)
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Project Budget Example (cont’d) Early Start Times
Task 1 2 3 4 5 6 7 8 9 10 11 12
A 1140 800 800 800 800 800 800 800 800 800 800 800
B 8925 8800 8800 8800 8800 8800 8800 8800 8800
C 9600 9600 9600 9600 9600 9600 9600 9600 9600 9600 9600 9600
D
E
F
Weekly Subtotals 19665 19200 19200 19200 19200 19200 19200 19200 19200 10400 10400 10400
Cumulative 19665 38865 58065 77265 96465 115665 134865 154065 173265 183665 194065 204465
Late Start Times
Task 1 2 3 4 5 6 7 8 9 10 11 12
A 1140 800 800 800 800 800 800 800 800 800 800 800
B 8925 8800 8800 8800 8800 8800 8800 8800
C 9600 9600 9600 9600
D
E
F
Weekly Subtotals 1140 800 800 800 9725 9600 9600 9600 19200 19200 19200 19200
Cumulative 1140 1940 2740 3540 13265 22865 32465 42065 61265 80465 99665 118865
W e e k
W e e k
C l ti C t
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Cumulative Costs
Range of
feasible budgets
Weekly Costs (Cash Flows)
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Weekly Costs (Cash Flows)
M i C h Fl
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Managing Cash Flows
• Want to manage payments and receipts
• Must deal with budget constraints on
project and organization requirements (e.g.,
payback period)• Organization profitability
C h Fl E l
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Cash Flow Example
M1
END
START
Task B
8 mos
Receive payment
of $3000
Receive payment
of $3000
Make paymentof $5000
Task C
4 mos
Task A
2 mos
M2
Task D8 mos
Task E
3 mos
C h Fl E l S l M d l
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Cash Flow Example: Solver Model
Material Management Issues
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Material Management Issues
When to order materials? How much to order?
Example:
• Single material needed for Task B (2 units) and Task E (30 units)
• Fixed cost to place order = S
• Cost of holding raw materials proportional to number of unit-weeks in
stock
• Cost of holding finished product greater than the cost of holding raw
materials
• Project can be delayed (beyond 17 weeks) at cost of $P per week
Material Management Example
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Material Management Example
Task A
4 wks Task B
8 wks Task C
5 wks
Task D
6 wks Task E
2 wksTask F
3 wks
EndStart 2 units
30 units
LSA = 0 LSB = 4 LSC = 12
LSD = 6 LSE = 12 LSF = 14
Lot-Sizing Decisions in Projects
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Lot Sizing Decisions in Projects
• To minimize holding costs, only place orders at Late Starting Times
• Can never reduce holding costs by delaying project
Time
1 2 3 4 5 6 7 8 9 10 11 12
Demand: 2 30
Order option #1: 32
Order option #2: 2 30
Choose the option that minimizes inventory cost = order cost + holding
cost of raw materials
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Time-Cost Tradeoffs
Ti C t T d ff E l
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Time-Cost Tradeoff Example
Task
Normal
Duration Normal Cost
Marginal Cost
to Crash One
Week A 7 $60 $8
B 6 $85 $5
C 15 $55 $10
D 10 $120 $4
A
B
C
D
Start End
Ti C t T d ff E l ( t’d)
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Time-Cost Tradeoff Example (cont’d)
Project
Duration
(weeks) Critical Path(s) Task(s) Reduced
Total Direct
Cost
22 Start-A-C-End - $320
21 Start-A-C-End A $328
Start-A-B-End
20 Start-A-C-End C $338
Start-A-B-End
19 Start-A-C-End C $348
Start-A-B-End
18 Start-A-C-End A, B $361
Start-A-B-End
Linear Time-Cost Tradeoff
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Linear Time-Cost Tradeoff In theory, the normal or expected duration of a task can be reduced by
assigning additional resources to the task
Time
Cost
Crash
Point
Normal
Point
Slope (b j) = Increase in cost by
reducing task by one time unit
Normal time =Crash time =
Normal
cost =
Crash
cost =
t j Nt j
c
C j
c
C j N
Balancing Overhead & Direct Costs
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Balancing Overhead & Direct Costs
Project
Duration
Cost
Indirect
(overhead)
Costs
Direct
Costs
Total Cost
Crash
Time
Normal Time Minimum Cost
Solution
Time-Cost Tradeoff (Direct Costs Only)
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( y)
Given Normal point with cost and time
and Crash point with cost and time
Assume constant marginal cost of crashing task j =
Decision Variables: S j = Starting time of task j
END = End time of project
t j = Duration of task j
Minimize Total Direct Cost =
S j ≥ Si + ti for all tasks i P j
for all tasks in project
END = Tmax
t j, S j ≥ 0
C j N
C jc
t jc
t j N
b j =C j
c - C j N
t jc - t j
N
b j t j• j
t jc t j t j
N
General Time-Cost Tradeoffs
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where
I = indirect (overhead) cost/time period
P = penalty cost/time period if END is delayed beyond
deadline Tmax
L = number of time periods project is delayed beyond
deadline Tmax
Minimize Total Costs = + I (END) + P L b j t j• j
QUESTION: HOW TO DEFINE L?
Software Project Schedules
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j
“Observe that for the programmer, as for the chef, the urgency of the patron may govern the scheduled completion of the task, but itcannot govern the actual completion. An omelet, promised in tenminutes, may appear to be progressing nicely. But when it has notset in ten minutes, the customer has two choices--wait or eat itraw. Software customers have the same choices.
The cook has another choice; he can turn up the heat. Theresult is often an omelet nothing can save--burned in one part, rawin another.”
F.P. Brooks, “The Mythical Man-Month”, Datamation, Vol 20, No 12 (Dec, 1974), pp.44-52.
Coordination Costs (Software Development Project)
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Coordination Costs (Software Development Project)
n Assume you want to develop program that will require (approximately) 50,000 lines of
PERL code
n A typical programmer can write approximately 1500 lines of code per week
n Coordination time is M (M-1)/2 weeks
No. of Programmers
No. of
WeeksCoding
No. of
CoordinationWeeks
Total
Number of Weeks
1 33.33 0 33.33
2 16.67 1 17.67
3 11.11 3 14.11
4 8.33 6 14.33
5 6.67 10 16.67
6 5.56 15 20.56
7 4.76 21 25.76
8 4.17 28 32.17
9 3.70 36 39.7010 3.33 45 48.33
11 3.03 55 58.03
Brook’s Law
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Brook s Law
“Adding manpower to a latesoftware project makes it later.”
n F.P. Brooks, “The Mythical Man-Month”, Datamation, Vol 20, No 12 (Dec, 1974), pp. 44-52.
Compressing New Product Development
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p g pProjects
Traditional Method
Design follows a sequential pattern where
information about the new product is slowly
accumulated in consecutive stages
Stage 0 Stage 1 Stage N
New Product Development Process
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New Product Development Process
Overlapped Product Design
Allows downstream design stages to start before
preceding upstream stages have finalized their specifications….
Stage 0
Stage 1
Stage N
Issues and Tradeoffs
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Issues and Tradeoffs
What are the tradeoffs when moving from a
traditional sequential product design process
to an overlapped product design process?
• Increased uncertainty (that leads to additional
work)
• Can add additional resources to tasks to reduce
duration--but costs are increased
Classic PERT Model Defined
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• Since task durations are now random variables, time of any
milestone (e.g., end of project) is now RV
• Assume all tasks are statistically independent
• Use values of j to identify expected critical path
• Since time of event (e.g., ESk ) is now sum of independent RV‟s,
central limit theorem specifies that ESk is approximatelynormally distributed with mean E[ESk ] and variance Var[ESk ]
where there exists s paths to task k
Expected early start time of task k = E ESk =max
s j•
tasks j on path s
Classic PERT Model (cont’d)
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Expect Project Duration = E[E SEND] = j•tasks j on CP
Variance of Project Duration = Var[E SEND] = j2•
tasks j on CP
Thus, expected project duration is defined as:
Using central limit theorem and standard normal distribution:
P ESENDŠ Tmax = P z ŠTmax - E ESEND
Var ESEND
PERT Example #1
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Duration Estimates Expected
Task Description Predecessors Optimistic Pessimistic Likely Duration Variance
A Requi rements Analysis none 2 14 6 6.67 4.00
B Programming A 4 12 7 7.33 1.78
C Hardware acquisi tion A 2 13 8 7.83 3.36D User training A 12 18 14 14.33 1.00
E Implementation B, C 3 7 5 5.00 0.44
F Testing E 3 7 4 4.33 0.44
END End of project D, F 0 0 0 0.00 0.00
StartTask A
RequirementsAnalysis
Task C Hardware
Acquisition
Task B Programming
Task F Testing
Task D User
Training
Task E Implementation
End
PERT Example #1 (cont’d)
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Expected
Task Path Early Start Variance Due Date Zi Pr(zi)
B,C,D Start-A 6.67 4.00 6 -0.33 0.37
E Start-A-C 14.50 7.36 15 0.18 0.57
F Start-A-C-E 19.50 7.81 20 0.18 0.57
End Start-A-C-E-F-End 23.83 8.25 25 0.41 0.66
PERT Expe cted Dur at i on = 23 .8 3 Ex pected CP = {Star t , A, C , E, F , En d}
PERT Var ia nce = 8.25 0
StartTask A
RequirementsAnalysis
Task C Hardware
Acquisition
Task B Programming
Task F Testing
Task D User
Training
Task E Implementation
End
PERT Example #2
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Task B
B = 12
B 2 = 4
Task D
D = 3
D 2 = 1
Task A
A = 4
A 2 = 2
Task C
C = 10
C 2 = 5
END START
Example #3: Discrete Probabilities
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Task A Task B Task C Task D
Value Prob Value Prob Value Prob Value Prob
7 0.333 2 0.2 5 0.2 3 0.3
8 0.333 12 0.8 15 0.2 12 0.7
9 0.333 25 0.6
START END
Task A
(8.0)
Task B
(10.0)
Task C
(19.0)
Task D
(9.3)
Example #3 (cont’d)
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Task A Task B Task C Task D Critical Pr ob of Len gth PATHS
Combination Value Prob Value Prob Value Prob Value Prob Path CP of CP A,D B, D C
1 7 0.333 2 0.2 5 0.2 3 0.3 A, D 0.004 10 0.004 0.000 0.000
2 7 0.333 2 0.2 5 0.2 12 0.7 A, D 0.009 19 0.009 0.000 0.000
3 7 0.333 2 0.2 15 0.2 3 0.3 C 0.004 15 0.000 0.000 0.004
4 7 0.333 2 0.2 15 0.2 12 0.7 A, D 0.009 19 0.009 0.000 0.000
5 7 0.333 2 0.2 25 0.6 3 0.3 C 0.012 25 0.000 0.000 0.012
6 7 0.333 2 0.2 25 0.6 12 0.7 C 0.028 25 0.000 0.000 0.028
7 7 0.333 12 0.8 5 0.2 3 0.3 B, D 0.016 15 0.000 0.016 0.000
8 7 0.333 12 0.8 5 0.2 12 0.7 B, D 0.037 24 0.000 0.037 0.000
9 7 0.333 12 0.8 15 0.2 3 0.3 B, D 0.016 15 0.000 0.016 0.000
10 7 0.333 12 0.8 15 0.2 12 0.7 B, D 0.037 24 0.000 0.037 0.000
11 7 0.333 12 0.8 25 0.6 3 0.3 C 0.048 25 0.000 0.000 0.048
12 7 0.333 12 0.8 25 0.6 12 0.7 C 0.112 25 0.000 0.000 0.112
13 8 0.333 2 0.2 5 0.2 3 0.3 A, D 0.004 11 0.004 0.000 0.000
14 8 0.333 2 0.2 5 0.2 12 0.7 A, D 0.009 20 0.009 0.000 0.00015 8 0.333 2 0.2 15 0.2 3 0.3 C 0.004 15 0.000 0.000 0.004
16 8 0.333 2 0.2 15 0.2 12 0.7 A, D 0.009 20 0.009 0.000 0.000
17 8 0.333 2 0.2 25 0.6 3 0.3 C 0.012 25 0.000 0.000 0.012
18 8 0.333 2 0.2 25 0.6 12 0.7 C 0.028 25 0.000 0.000 0.028
19 8 0.333 12 0.8 5 0.2 3 0.3 B, D 0.016 15 0.000 0.016 0.000
20 8 0.333 12 0.8 5 0.2 12 0.7 B, D 0.037 24 0.000 0.037 0.000
21 8 0.333 12 0.8 15 0.2 3 0.3 B, D 0.016 15 0.000 0.016 0.000
22 8 0.333 12 0.8 15 0.2 12 0.7 B, D 0.037 24 0.000 0.037 0.000
23 8 0.333 12 0.8 25 0.6 3 0.3 C 0.048 25 0.000 0.000 0.048
24 8 0.333 12 0.8 25 0.6 12 0.7 C 0.112 25 0.000 0.000 0.112
25 9 0.333 2 0.2 5 0.2 3 0.3 A, D 0.004 12 0.004 0.000 0.000
26 9 0.333 2 0.2 5 0.2 12 0.7 A, D 0.009 21 0.009 0.000 0.00027 9 0.333 2 0.2 15 0.2 3 0.3 C 0.004 15 0.000 0.000 0.004
28 9 0.333 2 0.2 15 0.2 12 0.7 A, D 0.009 21 0.009 0.000 0.000
29 9 0.333 2 0.2 25 0.6 3 0.3 C 0.012 25 0.000 0.000 0.012
30 9 0.333 2 0.2 25 0.6 12 0.7 C 0.028 25 0.000 0.000 0.028
31 9 0.333 12 0.8 5 0.2 3 0.3 B, D 0.016 15 0.000 0.016 0.000
32 9 0.333 12 0.8 5 0.2 12 0.7 B, D 0.037 24 0.000 0.037 0.000
33 9 0.333 12 0.8 15 0.2 3 0.3 B, D 0.016 15 0.000 0.016 0.000
34 9 0.333 12 0.8 15 0.2 12 0.7 B, D 0.037 24 0.000 0.037 0.000
35 9 0.333 12 0.8 25 0.6 3 0.3 C 0.048 25 0.000 0.000 0.048
36 9 0.333 12 0.8 25 0.6 12 0.7 C 0.112 25 0.000 0.000 0.112
6.8% 32.0% 61.1%
Example #3 (cont’d)
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Length of Cumulative
CP's Prob Prob
10 0.004 0.00
11 0.004 0.01
12 0.004 0.01
15 0.108 0.12
19 0.019 0.14
20 0.019 0.16
21 0.019 0.18
24 0.224 0.4025 0.599 1.00
Task A Task B Task C Task D
6.8% 32.0% 61.1% 38.8%
Criticality Indices
Expected Project Duration = 23.22
Monte-Carlo Simulation (PERT Example 1)
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Task Duration Early Latest Total Expected
Task (Uniform Dist) Start Finish Slack Duration Variance
A 4.99 0 4.99 0.00 6.67 4.00
B 4.75 4.99 9.74 0.00 7.33 1.78C 3.38 4.99 9.74 1.36 7.83 3.36
D 12.20 4.99 21.02 3.83 14.33 1.00
E 5.94 9.74 15.68 0.00 5.00 0.44
F 5.34 15.68 21.02 0.00 4.33 0.44
END 0.00 21.02 21.02 0.00 0.00 0.00
Run Proj ect Duration t(B) t(C) t(D) t(E) t(F)
1 31.07 1 0 0 1 1
2 27.41 0 1 0 1 1
3 23.97 1 0 0 1 1
4 28.93 0 1 0 1 1
5 26.85 1 0 0 1 1
6 28.82 0 0 1 0 0
7 28.77 0 1 0 1 1
197 30.37 0 1 0 1 1
198 29.78 1 0 0 1 1
199 25.33 1 0 0 1 1200 29.70 0 1 0 1 1
Ave 27.13 48.5% 42.0% 9.5% 90.5% 90.5%
Var 16.777
Project Makespan Lower Limit Upper Limit
95% Confidence interval 26.56 27.72
99% Confidence interval 26.37 27.90
Calculating Confidence Intervals
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For a confidence interval, we can use the sample meanand the estimated standard error of the mean
where s is the sample standard deviation and n is the
number of trials
Using a normal approximation, a (1- a) two-
sided confidence interval is given by
sX = snX
X -+ za/2 s
New Product Development Projects
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START
Lease
Mfg/Office
Space
Identify/hirestaff
Design of
physical unit
Electronics
design Software
Assemble prototype Beta test
prototype
END
Beta test fails (with
probability of 0.25)
and rework is needed
Beta test fails (withprobability of 0.25)
and rework is needed
New Product Development Projects (cont’d)
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START
Lease
Mfg/Office
Space
Identify/hire
staff
Design of
physical unit
Electronics
design Software
Assemble prototype Beta test
prototype
END
Beta test fails andrework is needed
Prob = .25
Prob = .75
Critical Chain and the Theory of Constraints (TOC)
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• Use deterministic CPM model with buffers to deal with any
uncertainties,
• Place project buffer after last task to protect the customer‟s
completion schedule,
• Exploit constraining resources (make certain that resources are
fully utilized),
• Avoid wasting time slack time by encouraging early task
completions,
• Carefully monitor the status of the buffer(s) and communicate
this status to other project team members on a regular
basis, and• Make certain that the project team is 100 percent focused on
critical chain tasks
Project “Goal” (according to Goldratt): Meet Project Due Date
Project Buffer Defined
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• Project Buffer is placed at the end of the project to protect the
customer‟s promised due date
PERT Example #1 Revisited with Project Buffer
Start
Task B
Programming
User Task D User
training
Task E
Implementation
End Project
Buffer
Task A requirements
analysis
Task C Hardware acquisition
Task F
Testing
Calculating Project Buffer Size
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For tasks k on critical chain, we can calculate project buffer
using following formula that project will be completed
within worst-case duration estimates around 90 percent of
the time:
For those “who want a scientific approach to sizingbuffers....”
Buffer = •tasks k on cr itic al chain
tk p - k
2
Implications of Project Uncertainty
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Assume that the duration of both tasks A and B are described by a
normal distribution with a mean of 30 days
START END
Task A
Task B
What is the probability that the project will be completed within 30
days?
Uncertainty and Worker Behavior
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Consider a project with two tasks that must be completed serially
The duration of each task is described by a RV with values Ti (i = 1, 2)
Values of T1 Prob Values of T2 Prob
7 0.3 14 0.5
8 0.4 18 0.5
9 0.38.0 16
Start Task 1 Task 2 End
Parkinson’s Law (Expanding Work)
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“Work expands so as to fill the time available for its
completion”
Professor C.N. Parkinson (1957)
Set a deadline D = 24 days
So T(D) = project makespan (function of D) where
E[T(D)] = E(T1) + E(T2) + E[max(0, D - T1 - T2)]
Values of T1 Prob Values of T2 Prob
Project
Makespan Prob
7 0.3 14 0.5 24 0.15
7 0.3 18 0.5 25 0.158 0.4 14 0.5 24 0.2
8 0.4 18 0.5 26 0.2
9 0.3 14 0.5 24 0.15
9 0.3 18 0.5 27 0.15
E[T(D)] = 25 days
Procrastinating Worker
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Set a deadline D = 24 daysE’[T(D)] = E(T1) + E(T2) + E{max[0, D - T1 - E(T2)]}
Can show that E[T(D)] ≥ E’[T(D)] ≥ D
What are the implications for project managers?
Values of T1 Prob
E[De lay] =
max[0, D - T1 - E(T2)] E[Makespan]
7 0.3 1 24
8 0.4 0 24
9 0.3 0 25
8 0.3 24.30
Schoenberger’s Hypothesis
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An increase in the variability of task durations willincrease the expected project duration….
Schoenberger’s Hypothesis Illustrated
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START END
Task A
Task B
Duration of
Task A Probability
Duration of
Task B Probability
12 0.1 10 0.5
14 0.8 15 0.5
16 0.1
14.0 12.5
Schoenberger’s Hypothesis Illustrated
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Realization
Task A
Duration
Task B
Duration Probability Max (A, B)
1 12 10 0.05 12
2 14 10 0.4 14
3 16 10 0.05 16
4 12 15 0.05 15
5 14 15 0.4 15
6 16 15 0.05 16
Duration of
Task A Probability
Duration of
Task B Probability
12 0.3 10 0.5
14 0.4 15 0.5
16 0.314.0 12.5
Increasing the variance of Task A:
Results in an increased expected duration = 14.65 days
Expected duration equals 14.55 days
Risk Management
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• All projects involve some degree of risk
• Need to identify all possible risks and outcomes
• Need to identify person(s) responsible for managing
project risks
• Identify actions to reduce likelihood that adverse
events will occur
Risk Analysis
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Risk Exposure (RE) or Risk Impact =
(Probability of unexpected loss) x (size of loss)
Example: Additional features required by client
Loss: 3 weeksProbability: 20 percent
Risk Exposure = (.20) (3 weeks) = .6 week
How to Manage Project Risks?
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Preventive Actions
• Actions taken in anticipation of adverse events
• May require action before project actually begins
• Examples?
Contingency Planning • What will you do if an adverse event does occur?
• “Trigger point” invokes contingency plan
• Frequently requires additional costs
Risk and Contracts
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H igh Low Low H igh
Degree of Risk
Contractor Client
Fixed Price Contract Cost Plus Contract
Firm price
Elements
can be
renegotiated Incentives
T&M
with limits
Cost Plus
with
Incentives
Time &
materials
Tornado Diagram
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Wage Rate
Direct Labor Hours
Material Units Needed
Early Completion Bonus
Material Unit Cost
Interest rates
Energy costs
Overhead
Project Cost ($000's)
$1290
$1265
$1260
$1310
$1350
$1350
$1380
$1400
$1700
$1720
$1680
$1690
$1640
$1620
$1625
$1760
$1500 $1600 $1800$1700$1400$1300$1200
Sensitivity Chart
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Wage Rate 0.85
Direct Labor Hours 0.73
Material Units Needed 0.62
Early Completion Bonus -0.45
Material Un it Cos t 0.42
Inter es t rates 0.28
Energy cos ts 0.19
Overhead 0.10
0 0.5 1.0-0.5
Rank Order Correlation with Total Project Cost
Van Allen Company
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Strike Expected
(wks) Prob Duration
3 0.45 1.354 0.3 1.20
5 0.25 1.25
E[Strike Duration] 3.80
Resource Allocation & Leveling
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Resource Leveling: Reschedule the noncriticaltasks to smooth resource requirements
Resource Allocation: Minimize project
duration to meet resource availability constraints
Resource Allocation & Leveling
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Three types of resources: 1) Renewable resources: “renew” themselves
at the beginning of each time period (e.g.,
workers)
2) Non-Renewable resources: can be used at
any rate but constraint on total number
available
3) Doubly constrained resources: bothrenewable and non-renewable
Resource Leveling
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Task B
2 wks
Task E
3 wks
Task C
9 wks
Task D
5 wks
Task F
2 wks
Task A
3 wks
START Task G
5 wksEND
Task Workers Duration ( t j) Early Start Late Start
A 7 3 0 0
B 3 2 0 3C 2 9 3 4
D 10 5 3 3
E 4 3 2 5
F 5 2 2 11
G 6 5 8 8
Resource Leveling: Early Start Schedule
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Resource Leveling: Late Start Schedule
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Resource Leveling: Microsoft Project
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5
10
15
20
25
Workers Ov era ll ocat ed: Al loca te d:
T W T F S S M T W T F S S M T W T F S S M T W T F S
Dec 17, '00 Dec 24, '00 Dec 31, '00 Jan 7, '01
10 10 10 10 10 10 10 10 10 10 16 16 16 16 16 21 21 21
Renewable Resource Allocation Example(Single Resource Type)
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Ta sk B 3 w k s
Ta sk D 5 w ks
Ta sk A 4 w k s
Ta sk E
4 w k s
START
END
Ta sk C 1 w k
3 workers
5 workers
6 workers
8 workers
7 workers
Maximum number of workers available = R = 9 workers
Resource Allocation Example: Early Start Schedule
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Maximum number of workers available = R = 9 workers
Start
End
Week 1 2 3 4 5 6 7 8 9 10 11 12
No. of Worke rs/wk 8 8 8 11 14 8 8 8 7 7 7 7
Cumulative Workers 8 16 24 35 49 57 65 73 80 87 94 101
"Waste d" worker-wks 1 1 1 - - - - - - - - -
Task B:
5 workers
Task A:
3 workers
Task C:
6 workers
Task E:
7 workersTask D:
8 workers
Resource Allocation Example: Late Start Schedule
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Maximum number of workers available = R = 9 workers
Start
End
Week 1 2 3 4 5 6 7 8 9 10 11 12
No. of Workers/wk 5 5 5 11 11 11 11 14 7 7 7 7
Cumulative Workers 5 10 15 26 37 48 59 73 80 87 94 101
"Waste d" worker-wks - - - - - - - - 2 2 2 2
Task B:
5 workers
Task A:
3 workers
Task C:
6 workers
Task E:
7 workersTask D:
8 workers
Resource Allocation HeuristicsRk
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n Some heuristics for assigning priorities to available tasks j, where denotes the
number of units of resource k used by task j
n 1) FCFS: Choose first available task
n 2) GRU: (Greatest) resource utilization =
n 3) GRD: (Greatest) resource utilization x task duration =
n 4) ROT: (Greatest) resource utilization/task duration =
n 5) MTS: (Greatest) number of total successors
n 6) SPT: Shortest processing time = min {t j}
n 7) MINSLK: Minimum (total) slack
n 8) LFS: Minimum (total) slack per successor
n 9) ACTIM j: (Greatest) time from start of task j to end of project = CP - LS j
n 10) ACTRES j: (max) (ACTIM j)
n 11) GENRES j: w ACTIM j + (1-w) ACTRES j where 0 ≤ w ≤ 1
R jk
R jk
•
k
R jk / t j•
k
R jk
•
k
t j
Resource Allocation Problem #2
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Task A1
6 da sTask A2
4 da s
EndStart Task B1
3 da s
Task C1
2 da s
Task B2
5 da s
Task C2
5 da s
Purple CrewGold Crew
How to schedule tasks to minimize project makespan?
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Priority scheme: schedule tasks using total slack (i.e., tasks with
smaller total slack have higher priority)
Task A1 Task B1 Task C1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Task A2 Task B2 Task C2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Gold Crew
Purple
Resource Allocation Example (cont’d)
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But, can we do better? Is there a better priority scheme?
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Gold Crew
Purple
Microsoft Project Solution (Resource Leveling Option)
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Soluti on by: M icrosoft Project 2000
Critical Chain Project Management
Id if h i i l h i f k h d i h ll
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• Identify the critical chain: set of tasks that determine the overall
duration of the project
• Use deterministic CPM model with buffers to deal with uncertainty
• Remove padding from activity estimates (otherwise, slack will be
wasted). Estimate task durations at median.
• Place project buffer after last task to protect customer‟s completion
schedule
• Exploit constraining resource(s)
• Avoid wasting slack times by encouraging early task completions
• Have project team focus 100% effort on critical tasks • Work to your plan and avoid tampering
• Carefully monitor and communicate buffer status
Critical Chain Buffers
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Project Buffer : placed after last task in project to protect schedule
Feeding Buffers: placed between a noncritical task and a critical task
when the noncritical task is an immediate predecessor of the critical task
Resource Buffers: placed just before a critical task that uses a new
resource type
Critical Chain Illustrated
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Task A1
6 da s
Task A2
4 da s
EndStart
Task B1
3 da s
Task C1
2 da s
Task B2
5 da s
Task C2
5 da s
Resource Buffers
Feeding Buffers
Non-Renewable Resources
12 units
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Task B5 wks
Task D2 wks
Task C3 wks
Task A6 wksST ART END
6 units
10 units
8 units
Task Duration
No. of Nonrene wable
Resource s Units
Needed Early Start Late Start
A 6 6 0 0
B 5 12 6 6
C 3 10 6 8
D 2 8 11 11
Non-Renewable Resources: Graphical Solution
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
40
36
32
28
24
20
16
12
8
4
Cumulative ResourcesSupplied
C u m u l a t i v e R e s o u r c e s
Cumulative Resources
Required
Resource Allocation Problem #3
Issue: When is it better to “team” two or more
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Issue: When is it better to team two or more
workers versus letting them work separately?
• Have 2 workers, Bob and Barb, and 4 tasks: A, B, C, D
• Bob and Barb can work as a team, or they can work separately
• When should workers be assigned to tasks? Which configurationdo you prefer?
How to Assign Project Teams?
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Configuration #1
Bob and Barb work jointly on all four tasks; assume that they can complete each
task in one-half the time needed if either did the tasks individually
A C
B D
Start End
Configuration #2 Bob and Barb work independently. Bob is assigned to tasks A and C; Barb is
assigned to tasks B and D
Bob and Barb: Configuration #1
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TASK A TASK B TASK C TASK D
Duration Prob Duration Prob Duration Prob Duration Prob
6 0.33 9 0.667 12 0.6 10 0.255 0.33 6 0.333 7 0.4 6 0.75
4 0.33
Expected
duration 5.0 8.0 10.0 7.0
Configuration #1
Bob and Barb work jointly on all four tasks.
What is the expected project makespan?
Bob and Barb: Configuration #2
Bob and Barb work independently. Bob is assigned to tasks A and C; Barb is
assigned to tasks B and D
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assigned to tasks B and D
Realization # A B C D
Bob
A + C
Barb
B + D
max
(A+C,
B+D) Prob
1 6 9 12 10 18 19 19 0.03
2 6 9 12 6 18 15 18 0.10
3 6 9 7 10 13 19 19 0.02
4 6 9 7 6 13 15 15 0.07
5 6 6 12 10 18 16 18 0.02
6 6 6 12 6 18 12 18 0.05
7 6 6 7 10 13 16 16 0.01
8 6 6 7 6 13 12 13 0.039 5 9 12 10 17 19 19 0.03
10 5 9 12 6 17 15 17 0.10
11 5 9 7 10 12 19 19 0.02
12 5 9 7 6 12 15 15 0.07
13 5 6 12 10 17 16 17 0.02
14 5 6 12 6 17 12 17 0.05
15 5 6 7 10 12 16 16 0.01
16 5 6 7 6 12 12 12 0.03
17 4 9 12 10 16 19 19 0.03
18 4 9 12 6 16 15 16 0.10
19 4 9 7 10 11 19 19 0.02
20 4 9 7 6 11 15 15 0.07
21 4 6 12 10 16 16 16 0.02
22 4 6 12 6 16 12 16 0.05
23 4 6 7 10 11 16 16 0.01
24 4 6 7 6 11 12 12 0.03
Bob and Barb: Configuration #2
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Bob and Barb work independently. Bob is assigned to tasks A and C; Barb is
assigned to tasks B and D
max (A+C,
B+D) Prob
Cumulative
Prob
12 0.07 0.07
13 0.03 0.10
15 0.20 0.30
16 0.20 0.5017 0.17 0.67
18 0.17 0.83
19 0.17 1.00
Expected Project Makespan: 16.42
Parallel Tasks with Random Durations
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START END
Task B
Task A
• Assume that both Tasks A and B have possible durations:
8 days with probability = 0.5
10 days with probability = 0.5
• What is expected duration of project? (Is it 9 days?)
Project Monitoring and Control
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n “It is of the highest importance inthe art of detection to be able to
recognize, out of a number of acts,
which are incidental and which are
vital. Otherwise your energy and
attention must be dissipated instead
of being concentrated.”
Sherlock Holmes
Status Reporting?
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One day my Boss asked me to submit a statusreport to him concerning a project I was working
on. I asked him if tomorrow would be soon enough.
He said, "If I wanted it tomorrow, I would have
waited until tomorrow to ask for it!"
New business manager, Hallmark Greeting Cards
Control System Issues
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n What are appropriate performance metrics?
n What data should be used to estimate the value of each
performance metric?
n
How should data be collected? From which sources? Atwhat frequency?
n How should data be analyzed to detect current and future
deviations?
n How should results of the analysis be reported? To whom?
How often?
Controlling Project Risks
K i t t l i k d i j t
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Key issues to control risk during projecct:
(1) what is optimal review frequency, and
(2) what are appropriate review acceptance levels
at each stage?
“Both over -managed and under-managed
development processes result in lengthy design
lead time and high development costs.”
Ahmadi & Wang. “Managing Development Risk in
Product Design Processes”, 1999
Project Control & System Variation
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Common cause variation: “in-control” or normal
variation
Special cause variation: variation caused by forces
that are outside of the system
According to Deming:
• Treating common cause variation as if it were special cause variation
is called “tampering”
• Tampering always degrades the performance of a system
Control System Example #1
Project plan: We estimate that a task
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n Project plan: We estimate that a task
will take 4 weeks and require
n 1600 worker-hours
At the end of Week 1, 420 worker-hours
have been used
Is the task “out of control”?
Control System Example (cont’d)
Week 2: Task expenses = 460 worker-hours
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Week 2: Task expenses 460 worker hours
Is the task “out of control”?
370380
390
400
410
420
430
440
450
460
470
1 2 3 4
Week
Week
Planned Cost
(BCWS) Actual Cost
CumulativeActual Cost
(ACWP)
1 400 420 420
2 400 460 880
Control System Example (cont’d)
Week 3: Task expenses = 500 worker-hrs
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Is the task “out of control”?
Week
Planned cost
(worker-hours)
Actual cost
(worker-hours)
Cumulative cost
(worker-hours)
1 400 420 420
2 400 460 880
3 400 500 1380
0
100
200
300
400
500
600
1 2 3 4
Week
Earned Value Analysis
I t t t h d l d k f d
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• Integrates cost, schedule, and work performed
• Based on three metrics that are used as the basic
building blocks:
BCWS: Budgeted cost of work scheduled
ACWP: Actual cost of work performed
BCWP: Budgeted cost of work performed
Schedule Variance (SV)
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Schedule Variance (SV) = difference between value of
work completed and value of scheduled work
Schedule Variance (SV) = Earned Value - Planned Value
= BCWP - BCWS
Cost Variance (CV)
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Cost Variance (CV) = difference between value of work completed and actual
expenditures
Cost Variance (CV) = Earned Value - Actual Cost
= BCWP - ACWP
Earned Values Metrics Illustrated
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W o r k e r - H o u r s
Week 1 Week 2 Week 3 Week 4 Week 5 Week 6
Present time BAC
Actual Cost(ACWP)
Earned Value
(BCWP)
Planned Value
(BCWS)
Schedule Variance
(SV)
Cost Variance
(CV)
Relative Measure: Schedule Index
C
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Schedule Index (SI) =
BCWP
BCWS
If SI = 1, then task is on schedule
If SI > 1, then task is ahead of schedule
If SI < 1, then task is behind schedule
Relative Measure: Cost Index
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Cost Index (CI) = BCWPACWP
If CI = 1, then work completed equals
payments (actual expenditures)
If CI > 1, then work completed is ahead
of payments
If CI < 1, then work completed is behindpayments (cost overrun)
Example #2
W E E K 1 2 3 4 5 6 7 8 9 10
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1 2 3 4 5 6 7 8 9 10
6 6 6 8 10
12 12 12
10 10 12 12 12
Scheduled
Worker-Hrs 6 6 6 20 22 22 10 12 12 12
Scheduled
Worker-Hrs
(BCWS) 6 12 18 38 60 82 92 104 116 128
Task A (36 worke r-hrs)
Task B (36 worker-hrs)
Task C (56 worker-hr
Example #2 (cont’d)
Progress report at the end of week #5:
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Week 1 2 3 4 5
Task A 15% 30% 40% 60% 80%
Task B 25% 65%
Task C Not started yet
Cumulative Percent of Work Completed:
Worker-Hours Charged to Project:
Week 1 2 3 4 5
Task A 5 6 8 10 10
Task B 15 10
Task C Not started yet
Example #2 (cont’d)
Progress report at the end of week #5:
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W E E K 1 2 3 4 5 6 7 8 9 10
Cumulative
Scheduled
Worker-Hrs
(BCWS) 6 12 18 38 60 82 92 104 116 128Actual Worker-
Hrs Used
(ACWP) 5 11 19 44 64
Earned Value
(BCWP) 5.4 10.8 14.4 30.6 52.2
Schedule
Variance (SV) -0.6 -1.2 -3.6 -7.4 -7.8
Cost Variance
(CV) 0.4 -0.2 -4.6 -13.4 -11.8
Example #2 (cont’d)
140
BAC
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0
20
40
60
80
100
120
1 2 3 4 5 6 7 8 9 10
Week
ACWP
BCWP
BCWS
Schedule
Variance
Cost
Variance
Using a Fixed 20/80 Rule
Cumulative Percent of Work Completed:
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W E E K 1 2 3 4 5 6 7 8 9 10
Cumulative
Scheduled
Worker-Hrs
(BCWS) 6 12 18 38 60 82 92 104 116 128Actual Worker-
Hrs Used
(ACWP) 5 11 19 44 64
Earned Value(BCWP) 7.2 7.2 7.2 14.4 14.4Schedule
Variance ( SV) 1.2 -4.8 -10.8 -23.6 -45.6Cost Variance
(CV) 2.2 -3.8 -11.8 -29.6 -49.6
Week 1 2 3 4 5Task A 20% 20% 20% 20% 20%
Task B 20% 20%
Task C Not s tar ted yet
Using a Fixed 20/80 Rule
140
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0
20
40
60
80
100
120
140
1 2 3 4 5 6 7 8 9 10
Week
BCWP
ACWP
BCWS
Updating Forecasts: Pessimistic Viewpoint
Assumes that rate of cost overrun will continue
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= (64/52.2) 128 = 1.23 x 128 = 156.94 worker-hrs
Estimate at Completion (EAC) = ACWP
BCWPBAC = 1
CIBAC .
Assumes that rate of cost overrun will continue
for life of project….
Updating Forecasts: Optimistic Viewpoint
Assumes that cost overrun experienced to date
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Estimate at Completion (EAC) = BAC - CV = 128 + 11.8 = 139.8 worker-hrs .
Assumes that cost overrun experienced to date
will cease and no further cost overruns will beexperienced for remainder of project life…
Multi-tasking with Multiple Projects
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Project A Project B
A-1 B-1 A-2 B-2 A-3 A-4B-3 B-4
Consider two projects with and without multi-tasking
How to prioritize your work when you have multipleprojects and goals?
Due-Date Assignment with Dynamic Multiple Projects
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• Projects arrive dynamically (common situation for bothmanufacturing and service organizations)
• How to set completion (promise) date for new projects?
• Firms may have complete control over due-dates or only partial
control (i.e., some due dates are set by external sources)
• How to allocate resources among competing projects and tasks (so
that due dates can be realized)?
• What are appropriate metrics for evaluating various rules?
What Does the Research Tell Us?
• Study by Dumond and Mabert* investigated four due date assignment
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rules and five scheduling heuristics• Simulated 250 projects that randomly arrive over 2000 days
• average interarrival time = 8 days
• 6 - 49 tasks per project (average = 24); 1 - 3 resource types
• average critical path = 31.4 days (range from 8 to 78 days)
• Performance criteria: 1) mean completion time
2) mean project lateness
3) standard deviation of lateness
4) total tardiness of all projects
• Partial and complete control on setting due dates
* Dumond, J. and V. Mabert. “Evaluating Project Scheduling and Due Date Assignment Procedures:
An Experimental Analysis” Management Science, Vol 34, No 1 (1988), pp 101-118.
Experimental Results
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• No one scheduling heuristic performs best across all due datesetting combinations
• Mean completion times for all scheduling and due date rules not
significantly different
• FCFS scheduling rules increase total tardiness • SPT-related rules do not work well in PM (SASP)
• Best to use more detailed information to establish due dates
Project Management Maturity Models
M h d l i i i ’ l l f
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• Methodologies to assess your organization’s current level of
PM capabilities
• Based on extensive empirical research that defines “best
practice” database as well as plan for improving PM process
• Process of improvement describes the PM process from
“ineffective” to “optimized”
• Also known as “Capability Maturity Models”
PM Maturity Model Example*
1) Ad-Hoc The project management process is described as disorganized, and occasionally even
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chaotic. Systems and processes are not defined. Project success depends on individual effort.
Chronic cost and schedule problems.
2) Abbreviated: Some project management processes are established to track cost, schedule,
and performance. Underlying disciplines, however, are not well understood or consistently
followed. Project success is largely unpredictable and cost and schedule problems are the norm.
3) Organized: Project management processes and systems are documented, standardized, and
integrated into an end-to-end process for the company. Project success is more predictable. Cost
and schedule performance is improved.
4) Managed: Detailed measures of the effectiveness of project management are collected and used
by management. The process is understood and controlled. Project success is more uniform.
Cost and schedule performance conforms to plan.