Transcript Decision and Risk Analysis in Project Management

Decision-Making In Project Management
Introduction to project decision analysis
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Example: San Francisco Bay Bridge
• Beginning 2005 – Decision to stop construction
• Later 2005 – Decision of continue construction based on
original project
• Result: $81M cost overrun. Will be paid by California
taxpayers and toll payers
Burden of Poor Decisions
• Cost of poor decisions in pharmaceutical industry is passed to
consumers
• Dry hole cost in oil and gas industry is passed to motorists
• Wrong policy decisions by government will be passed to
taxpayers
• You paint your deck without properly removing old paint. You
have to do it again next year.
Why is decision-making so complicated ?
• Most problems in project management involve multiple
objectives
• Project managers are always dealing with uncertainties
• Project management problems may be very complex
• Most projects include multiple stakeholders
How are decisions made?
No uncertainties – No
alternatives
No alternatives – No decisions
Two decision-making approaches:
Advocacy-based
approach
Decision Analysis
Process
Do We Have a Solution?
Decision Analysis Process
Decision Science
Theory of Probability
and
Statistics
Psychology of
Judgment and
Decision Making
Human Judgment Is Always to Blame
A study by Swiss Federal Institute of Technology in Zurich
analyzed 800 cases of structural failures where engineers were at
fault. In these incidents 504 people were killed, 592 injured and
millions of dollars of damage incurred.
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Insufficient Knowledge – 36%
Underestimation of influence – 16%
Ignorance, carelessness, neglect – 14%
Forgetfulness – 13%
Relying upon others without sufficient control – 9%
Objectively unknown situation – 7%
Other factors related to human error – 5%
Blink or Think?
Intuitive Thinking
Vulcans as Mr. Spock make
logical choices, but not
necessarily the best
When you think
automatically and
sometimes when you are
analyzing a situation, you
apply certain simplification
techniques. We use these
techniques due to limitations
in our thinking mechanisms.
In many cases, these
simplification techniques can
lead to wrong judgments.
Decision-Making Training
You may train yourself to overcome biases
the same way as you train yourself to walk
on the glass floor of Toronto’s CN Tower
Garbage In/Garbage Out:
Project managers know it
Uncertain input data
Advanced analytical
tools
Useless results of
analysis
Solutions:
1.
Perform analysis based on reliable
historical data
2.
Track project performance and
constantly refine data
Biases
• Cognitive – hard to detect, possible to mitigate by training
• Motivational – easy to detect, hard to mitigate negative effect
R e a lity
Bias is a discrepancy
between somebody’s
judgment and reality
30%
35%
40%
45%
50%
55%
60%
70%
Y o u r ju d g m e n t
W h a t ca u se d th is e rro r in ju d g m e n t?
Heuristics and Biases
The Bank of Sweden Prize in
Economic Sciences in Memory
of Alfred Nobel 2002
Daniel Kahneman
for having integrated insights
from psychological research
into economic science,
especially concerning human
judgment and decisionmaking under uncertainty
Decision makers use
“heuristics”, or
general rule of
thumb, to arrive to
their judgments.
In certain instances
they lead to systemic
biases.
Some Heuristics in Probabilistic Business Modeling
Representativeness – unwanted appeal to detailed scenarios
Availability – access the probability of an event by the ease with which
instances can be brought to mind.
Anchoring – human tendency is to remain close to the initial estimate
Solution: establish an uncertainty management
process in the organization
Availability
Welcome to Our Friendly Casino
This year 168,368 people lost $560M here.
5% of our guests divorced, 1% became alcoholics, and 0.4%
committed suicide.
Selective Perception
• “I see what I want to see”
• Overconfidence
• Confirmation bias
E xte rn a l W o rld
Edon
Brunswik ‘s
Lens Model
P sych o lo g ica l P ro ce sse s
In p u t
Ju d g m e n t
Lens of C ues
Selective Perception
• Are you motivated to see the project in a particular way?
• What do you expect from this particular decision?
• Would you be able to see project differently without these expectations
and motivational factors?
Behavioral Traps
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Sunk cost effect
Investment trap (Money Pit Movie)
Time delay (balance long-term and short-term goals)
Ignorance trap – usability to realize consequences of wrong
decisions for a long time
• Deterioration trap (maintenance of legacy products)
Framing
Scenario 1: You are involved in a construction project worth $300 million
and have discovered a new approach that would save $1 million. It will take
you a lot of time and effort to do the drawings, perform structural analysis,
and prepare a presentation that will persuade management to take this
course. Would you do it?
Scenario 2: You are involved in an IT project worth $500,000 and discovered
a way to save $80,000. You need to spend at least a couple of days for
researching and putting together a presentation. Would you do it?
Scenario 3: You are involved in the same construction project as in Scenario 1
and found a way to save $80,000 (replace one beam) and need to spend a
couple of days on research and the presentation. Would you do it?
Decision Analysis Manifesto
What do we want from decision analysis process?
– We want the decision to be made rationally.
– We want decision-making process to be transparent
– We want to have a mechanism to correct mistakes
Decision Analysis Process
S te p s o f D e cisio n A n a lysis P ro ce ss
D e cisio n
F ra m in g
M o d e llin g
th e S itu a tio n
Q u a n tita tive
A n a lysis
Im p le m e ta tio n
M o n ito rin g
E va lu a tio n
P ro je ct R isk M a n a g e m e n t
P ro ce sse s (P M B O K )
Id e n tifica tio n P ro b le m s o r O p p o rtu n itie s
A sse ssin g B u sin e ss S itu a tio n
D e te rm in in g S u cce ss C rite ria
Id e n tifyin g U n ce rta in tie s
G e n e ra tio n A lte rn a tive s
R isk M a n a g e m e n t P la n n in g
R isk Id e n tifica tio n
C re a tin g M o d e ls fo r P ro je ct A lte rn a tive
Q u a n tifyin g U n ce rta in tie s
Q u a lita tive R isk A n a lysis
D e te rm in in g W h a t Is M o st Im p o rta n t
Q u a n tifyin g R isks A sso cia te d w ith P ro je ct
D e te rm in in g th e V a lu e o f N e w In fo rm a tio n
D e cid in g o n a C o u rse o f A ctio n s
Im p le m e n tin g th e B e st A lte rn a tive
M o n ito rin g th e P ro je ct Im p le m e n ta tio n
E va lia tio n o f th e D e cisio n E xp e rie n ce
Q u a n tita tive A n a lysis
R isk R e sp o n se P la n n in g
R isk M o n ito rin g a n d C o n tro l
3D Principle of Decision Analysis
Decision Analysis Process vs.
PMBOK© Guide Risk Management
Decision
Analysis Process
PMBOK Risk
Management
Process
Tools and
processes to
manage risks
What is the rational choice?
Decision policy is a set of principles or preferences used for
selection alternatives.
Is he rational decision maker?
Strong emphasis on profitability;
Low emphasis on the safety of adversaries and a strong
emphasis on the security of its own employees with a special
concern for management;
Low regard for following legal rules and regulations;
Strong emphasis on organizational structure including clear
definitions of roles, responsibilities, and reporting;
Strong emphasis on fostering good relationships with the local
community .
Rational behavior is behavior that maximizes the value of
consequences and based on decision policy
Expected Value
For example, a big pharmaceutical company has two choices:
1. Continue developing a drug. The chance that it will get
FDA approval is 80%. If the drug is approved, the company
will get $800 million, but if it fails, the company will have
lost the $200 million it in development costs (20%
chance).
2. Buy another company that has already developed an FDA
approved drug. The estimated profit will be $500 million
dollars.
Decision Trees
F D A A p p ro va l
80%
$800M
D e v e lo p o w n
N o F D A A p p ro va l
S tra te g y
D e c is io n
20%
Buy Com pany
-$ 2 0 0 M
$500M
Expected value is a probability-weighted average of all outcomes. It is calculated
by multiplying each possible outcome by its probability of occurring and then
adding the result.
U tility
Utility Function
O b je c tiv e M e a s u re
(M o n e y )
Utility reflects a preferences of decision-maker toward
different factors, including profit, loss, and risk.
U tility
Risk Avoider vs. Risk Taker
R isk N e u tra l D e cisio n M a ke r
R isk A vo id e r
R isk T a ke r
O b je ctive M e a su re
Future Reading
Lev Virine and Michael Trumper
Project Decisions:
The Art and Science
Management Concepts, Vienna, VA, 2007
Lev Virine and Michael Trumper
Project Think:
Why Good Managers Make Poor Project Choices
Gower, 2013
Questions?