Transcript Project Risk Symposium - PMI Rome Italy Chapter

November 5-6, 2009
Copyright © 2009 PMI RiskSIG
A collaboration of the
PMI, Rome Italy Chapter
and the RiskSIG
“Project Risk Management –
An International Perspective”
RiskSIG - Advancing the State of the Art
A framework for
measuring operational
risks
Sabrina Grimaldi
Carlo Rafele
Politecnico di Torino
Department of System Production and Business
Economics
November 5-6, 2009
Copyright © 2009 PMI RiskSIG
Slide 2
Operational Risk
“The risk in loss resulting from
inadequate of failed internal processes,
people and systems or from external
events”
[Basel Commitee on Banking
Supervision]
November 5-6, 2009
Copyright © 2009 PMI RiskSIG
Slide 3
Framework aim
The proposed methodology is
consequently aimed at supporting
analysts in estimating a project's
exposure to operational risk, in all
those situations characterized by a lack
of data, by incomplete data or by lowquality data.
November 5-6, 2009
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Slide 4
Uncertainty and Risk
Uncertainty is unmeasurable risk
Uncertainty is described as epistemic
Uncertainty relates to a lack of knowledge about possible
outcomes of an event, including both their nature and
associated probabilities.
Risk is measurable uncertainty
Risk is described as aleatoric
Risk is an event where the set of possible outcomes is
known, and the probability of obtaining each outcome
can be measured or estimated, but the precise outcome in
any particular instance is not known in advance.
[D. Hillson]
November 5-6, 2009
Copyright © 2009 PMI RiskSIG
Slide 5
Uncertainty and Risk
Uncertainty is:
Ignorance “I don’t know what I don’t know”
Amnesia “I don’t know what I know”
Risk is:
Caution “I know what I don’t know”
[D. Hillson]
November 5-6, 2009
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Slide 6
Project Risk Management Process
1) Risk Analysis
1A) Identification
1B) Assessment (qualitative and/or quantitative)
2) Risk Response
2A) Response Development
2B) Response Control
November 5-6, 2009
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Slide 7
Risk Assessment
Qualitative Risk
Prioritizing risks for subsequent further analysis or
action by assessing and combining their probability of
occurence and impact.
Quantitative Risk
Numerically analyzing the effect on overall project
objectives of identified risks.
[PMBOK 3° ed.]
November 5-6, 2009
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Slide 8
Project Risk Management Process
Identification
phase
Complete
ignorance
November 5-6, 2009
Uncertainty
Assessment
phase
Risk
Copyright © 2009 PMI RiskSIG
Planning
phase
Complete
Information
Slide 9
Risk Analysis
Diverse Information need different
methodologies to be processed in order to
obtain reliable probability and impact
values
The risky event assessment phase may take
place in different contexts each characterized
by a specific informational domain, which
needs to be menaged by specific
methodologies.
November 5-6, 2009
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Slide 10
Risk Analysis
One of the most effective methodology
for risk identification is represented by
the so called Risk Breakdown Matrix
(RBM): bi-dimensional matrix, one
made of risk sources and the other of
corporate processes.
RBM perfectly re-enact risky event
manifestation process.
November 5-6, 2009
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Slide 11
General model
of risky event manifestation
Cause/Sources
Origin
Manifestation
Effect analysis
Transition
Consequence
Risk Factor
INT.
EXT.
Risk effects
Project Risk
Probability X%
November 5-6, 2009
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Impact
Slide 12
Risk Identification: WBS
Operational risk origin
coincides with all the activities
taking place in the assessed company
Risk identification starts with corporate
process analysis.
Work Breakdown Structure
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Slide 13
Work Breakdown Structure
ALPHA
MARKETING
TARGET
CUSTOMER
IDENTIFICATION
GATHERING
CUSTOMER
NEEDS
ADVERTISING
CAMPAIGN
MANAGEMENT
PRODUCT
DEVELOPMENT
TRANSFORM OF
CUSTOMER NEEDS
INTO PROJECT
REQUIREMENTS
PLANNING
PRODUCT
DEVELOPMENT
PROCESS
CUSTOMER
SATISFACTION
ANALYSIS
MANAGING
CODESIGN WITH
SUPPLIERS
PEGGING
SELLING PRICES
PROCUREMENT
PROCUREMENT
MARKETING AND
SUPPLIER
SELECTION
CONTRACTUAL /
LEGAL
RELATIONSHIPS
WITH SUPPLIER
PRICE AND
SUPPLIES
FEATURES
NEGOTIATION
PRODUCTION
MONITORING
SUPPLIES QUALITY
PLANT LOGISTICS
MANAGEMENT
SALES
AGENT SELECTION
AGENT
RELATIONSHIPS
MANAGEMENT
ASSEMBLY
AFTER-SALES
MANAGEMENT
PRODUCTION
SCHEDULING
RECALL PLAN
MANAGEMENT
SIZING PRODUCTION
PLANTS
GATHERING
ORDERS
MANAGING AND
MONITORING
PRODUCT COSTS
FREIGHT
MANAGEMENT TO
AGENTS
DESIGN CAR
COMPONENTS
November 5-6, 2009
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Slide 14
Risk Identification: RBS
Corporate processes to some extent provide a
favorable environment for risky events, but they are
not their primary source.
A source, that is the element originating the risky event for the
company, needs in fact to be associated to any “favorable
environment”. As far as operational risk is concerned, four main
sources are to be considered:
People, technology, processes, external sources
Risk Breakdown Structure
November 5-6, 2009
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Slide 15
Risk Breakdown Structure
The RBS is “A source-oriented grouping of project
risks that organises and defines the total risk
exposure of the project. Each descending level
represents an increasingly detailed definition of
sources of risk to the project” (Hillson,2002-1). The
RBS is therefore a hierarchical structure of
potential risk sources, which can be an invaluable
aid to understanding the risks faced by the project,
acting as a framework to structure and guide the
risk management process
November 5-6, 2009
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Slide 16
Risk Breakdown Structure
ALPHA
EXTERNAL
SOURCES
INTERNAL
SOURCES
PROCESSES
FITNESS
IMPLEMENTATION
PROPRIETY
HUMAN
RESOURCES
TECHNOLOGY
NOVELTY
RELIABILITY
BEHAVIOURAL
ASPECTS
SECURITY
AVAILABILITY
CONTINUITY
AVAILABILITY
CONFIDENTIALITY
PRODUCTIVITY
ILLNESS
TURNOVER
INDEX
AVAILABLE
QUANTITY
CARRIERS
FITNESS
ON DUTY
CONTIUNUITY
SUPPLIERS
RELIABILITY
ECONOMIC
STABILITY
DELIVERY TIME
SKILL
PUNCTUALITY
INSTRUCTION
CORRESPONDA
NCE
FLEET
MANAGEMENT
AGENTS
SOCIAL, POLITICAL,
NATURAL EVENTS
BEHAVIUR
FITNESS
CONGRUITY
ROADS
STRIKES
Neutral indications of risk source
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Slide 17
Risk Breakdown Structure
RBS content is absolutely neutral, in the sense that
economic stability of the supplier and not the
possibility of his failure is considered.
The source is a system state; the event acts as an
output of such a state, which is characterized by a
certain probability to happen.
Starting from the internal system characteristics a
series of events characterized by positive or negative
impacts on company output may take place. The
taking place possibility is measured by probability.
November 5-6, 2009
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Slide 18
Risk Breakdown Matrix
November 5-6, 2009
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Slide 19
Risk Breakdown Matrix
A RBM cell does not necessarily need to contain a
specific event. As a matter of fact, there could be
processes where a source does not cause any risky
event. The RBM is important since it helps
distinguish processes from sources.
Especially
when dealing with operational risks, the analyst could
be induced to consider processes as sources of risk,
thus making relevant mistakes.
November 5-6, 2009
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Slide 20
Event analysis
Risky events could be basically divided into
two main categories:
1. Repetitive events
Events related to manufacturing processes
2. Single events
Events related to the development of new products
or projects
November 5-6, 2009
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Slide 21
The events categories in the
Project Risk Management Process
Identification
phase
Single
events
Complete
ignorance
November 5-6, 2009
Uncertainty
Assessment
phase
Planning
phase
Repetitive
events
Risk
Copyright © 2009 PMI RiskSIG
Complete
Information
Slide 22
Repetitive event analysis
Repetitive Events
quantitative
approach
The outcomes of a company may be
described as functions of the performances
of its main processes as monitored over
time.
E.g. processes in a company manufacturing
mechanical components: machines, tools and
products will probably change in the long
term, but the company has a specific
production capacity, given processes and a
fixed set of products in the short term.
Classical models: Probability Analysis,
Monte Carlo Simulation
November 5-6, 2009
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Slide 23
Single event analysis
Single events
qualitative
approach
Order projects, such as the construction of a
bridge, a dam, or a manufacturing plant…
The main characteristic of these projects is
their uniqueness. As a matter of fact, even if
it is managed by standardized procedures, a
order project is unique because of the product
to be developed (and a project team has been
formed for this purpose), the people working
on it, third party stakeholders, execution
times, the assigned financial budget, the
strategic role of the final product, and its
market.
Conceptual models: Fuzzy Analysis
November 5-6, 2009
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Slide 24
Single event analysis
Risks related to the performances of a project for new product
development processes are quantified by means of expert
judgments. Experts are people in the company having a good
experience and knowledge.
Their evaluation could be
integrated with available data about past projects.
For instance, there is no doubt that the relationship between the
product development delay (a popular consequence of many
risks) and the company outcomes is very well known to
experts, even if it is not possible to express it in a mathematical
form. Usually, this knowledge comes from both past
experiences and the results of studies performed on the topic
by specialized organizations.
November 5-6, 2009
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Slide 25
Risk Assessment: qualitative approach
The qualitative approach should be used in all those
situations characterized by a complete lack of numerical
data, where the people we have called experts are the
only source of information available for the risk analyses
Qualitative Model
Supported by:
Elicitation Methodology
FMEA/FMECA
Fuzzy Function
November 5-6, 2009
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Slide 26
Qualitative approach
The qualitative approach may be divided into two phases:
1. Experts are interviewed one by one (elicitation
methodology);
2. Experts are brought together to discuss the results
expressed during their respective interviews
(individual judgment aggregation).
November 5-6, 2009
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Slide 27
Qualitative approach:
elicitation methodology (phase 1)
Expert knowledge elicitation is:
“a formal process to obtain information or answers to specific
questions about problems that need to satisfy certain analytical
goals”;
“a process transforming people knowledge and beliefs about one
or more uncertain quantities into appropriate forms”.
Using the elicitation methodology, analyst (project manager, risk
manager, etc.) sets a process aiming at eliciting from experts’
experience as much information as possible, for the purpose of
obtaining precise estimates about the impact and the occurrence
probability of an event.
November 5-6, 2009
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Slide 28
Qualitative approach:
elicitation process
The elicitation process is performed according to the following steps:
1. Preliminary information: event description, field where the risk comes from,
expert’s job, expert’s objective characteristics, ...
2. Explaining the reasons for the analysis: the analyst explains to the expert how
the analysis will be performed
3. Setting the analysis: a first range for all the possible values of both occurrence
times and impacts is defined
4. Conditioning: the analyst helps the expert look at the problem from different
points of view
5. Knowledge investigation: the analyst tries to understand the expert’s degree of
specific knowledge
6. Defining the probability distributions for the risky event occurrence and impact
7. Knowledge verification: the analyst shares the obtained results with the expert.
November 5-6, 2009
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Slide 29
Qualitative approach:
Failure Mode and Effects
(Criticality) Analysis
FMEA/FMECA
An analysis technique used in highrisk organizations to identify and
assess failure mode in
systems/processes and work out
response strategies.
November 5-6, 2009
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Slide 30
Qualitative approach:
FMEA/FMECA STEPS
TO CHOOSE THE PROCESS
TO ANALYZE THE PROCESS
TO IDENTIFY THE POSSIBLE “FAILURE MODES”
TO DETERMINE THE CONSEQUENCES
TO INDIVIDUALIZE THE CAUSES
TO DETERMINE THE CRITICALITY' INDEX
TO DEFINE REDUCTION ACTIONS
TO ESTIMATE EFFECTIVENESS REDUCTION
ACTIONS
November 5-6, 2009
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Slide 31
Qualitative approach:
FMEA/FMECA
TO CHOOSE THE PROCESS
TO ANALYZE THE PROCESS
November 5-6, 2009
ABS
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Slide 32
Qualitative approach:
FMEA
TO IDENTIFY THE “FAILURE MODES”
RBS
TO DETERMINE THE CONSEQUENCES
TO INDIVIDUALIZE THE CAUSES
TO DEFINE REDUCTION ACTIONS
November 5-6, 2009
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CARD
FMEA
Slide 33
Unique process risks :
scheda FMECA
TO IDENTIFY THE “FAILURE MODES”
TO DETERMINE THE CONSEQUENCES
TO INDIVIDUALIZE THE CAUSES
TO DETERMINE THE CRITICALITY INDEX
TO DEFINE REDUCTION ACTIONS
November 5-6, 2009
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RBS
CARD
FMECA
Slide 34
FROM RISK TO WASTE
A process out of control that causes
risks, it is also an inefficient
sequence of activities.
This a sure cause of waste.
Thus
in a similar could be useful to analyze
both the efficiency as the efficacy side.
November 5-6, 2009
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Slide 35
TOYOTA 7 WASTE:
Transport : Movement of materials is a waste. Minimize the amount
of movement by arranging processes in close proximity to each other.
Inventory : Too little inventory can lose sales, too much inventory can
hide problems.
Motion : Remove unnecessary motion of the operations and improve
the ergonomics of the workplace.
Waiting : Minimize waiting time and maximize "value adding" time.
Aim for a smooth flow.
Overproduction : Always aim to make exactly what the customer
orders, just in time, to the correct quality standard.
OverProcessing : Use machines which are of an appropriate capacity
and capable of achieving the required quality standard.
Defects : Reducing the number of defects directly reduces the amount
of waste. Aim for zero defects.
November 5-6, 2009
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Slide 36
Qualitative approach:
FMEA + WASTE:
TO IDENTIFY THE “WASTE”
RBS
TO DETERMINE THE CONSEQUENCES
TO INDIVIDUALIZE THE CAUSES
TO DEFINE REDUCTION ACTIONS
November 5-6, 2009
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CARD
Waste - FMEA
Slide 37
Qualitative approach:
CRITICALITY INDEX
TO DETERMINE THE CRITICALITY INDEX
RBS
FUZZY
FUNCTION
Risk priority numbers =
Probability X Impact
November 5-6, 2009
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Slide 38
Qualitative approach:
fuzzy functions
Traditional elicitation methods aim at obtaining a probability
distribution (for impact and occurrence frequency of risky events).
In our analysis we have replaced probability distributions with
fuzzy functions for the following reasons:
experts in any company are usually little familiar with the statistical
concepts of median, mode, quantile, and variance;
the consistency constraint is released, thus giving a further
degree of freedom to experts’ judgment;
fuzzy distributions provide experts with the same graphical
support as probability distributions, but without introducing too
many constraints and mathematical concepts.
November 5-6, 2009
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Slide 39
Qualitative approach: fuzzy
membership function
The fuzzy membership function is the analytical tool project manager use
to translate experts' knowledge into a formally correct language.
EXAMPLE: suppose you want to estimate the width of your colleague’s desk without
measuring it, but just interviewing the colleague. This person will give you:
a range of possible values, outside which he thinks the real width cannot be;
a range of most likely values including, in his opinion, the correct measure of the desk.
40-90 is the range of
possible values
60-80 is the range of
most likely values
November 5-6, 2009
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Slide 40
Qualitative approach:
standard ranges
Since the purpose of the first phase of the approach (individual
interviews) is identifying the less significant events from a risk point
of view, analysts need to provide experts with evaluation scales. The
proposed procedure suggests to define standard ranges basing on the
experience gained by analysts in the studied sector over time.
Class label
Impact
1.Negligible or very low
< 0,5%
2.Low
from 0,5 to 2%
3.Medium
from 2 to 5%
4.High
from 5 to 10%
5.Catastrophic or very high > 10%
November 5-6, 2009
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Slide 41
Qualitative approach:
standard ranges
The following step requires to translate range boundaries from
percentage to absolute values, strictly depending on the company
dimension.
In order to agree on a reference metric on which basing the
analysis, it is highly recommended to define the extreme values of
each range together with the company’s top management
Class label
Example:
company with a
turnover of
about 1.000.000
Euros
Impact
1. Negligible or very low
< 5.000€
2. Low
from 5.000 to 20.000€
3. Medium
from 20.000 to 50.000€
4. High
from 50.000 to 100.000€
5. Catastrophic or very high
> 100.000€
November 5-6, 2009
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Slide 42
Qualitative approach:
standard ranges
In order to determine the occurrence probability, a time
horizon is set, for example including the business cycles
related to the company’s processes. After that, the ranges
defining the number of times an event may occur in the
given time horizon are identified.
Class label
1.Negligible or very low
Example:
time horizon
of 18 months
0 - 0.2
2. Low
0.2 - 0.4
3. Medium
0.4 - 0.6
4. High
0.6 - 0.8
5. Very high
November 5-6, 2009
Probability
Copyright © 2009 PMI RiskSIG
0.8 - 1
Slide 43
Qualitative approach: range
representation
After performing individual interviews with experts, analyst
should have only two representations: one about the event impact,
and the other about its occurrence probability. The numbers 1, 2,
3, 4, and 5 on the x-axis correspond to the five classes of impact
and frequency defined before.
IMPACT
November 5-6, 2009
PROBABILITY
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Slide 44
Qualitative approach: combining
individual judgments (phase 1)
The judgment should result from the contributions of all the
experts, and not be a pure mathematical combination of individual
judgments.
IMPACT
PROBABILITY
1° expert
IMPACT
PROBABILITY
2° expert
November 5-6, 2009
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Slide 45
Qualitative approach: combining
individual judgments (phase 2)
The following step is aggregating individual judgments, in order
to come out with a univocal evaluation of the probability and
impact for each identified risky event.
The main aim of the group part of the analysis is basically
narrowing the range of possible values, and moving from a
distribution very similar to a trapezoidal to a uniform one.
IMPACT
November 5-6, 2009
PROBABILITY
Copyright © 2009 PMI RiskSIG
Slide 46
Graphical representation
of results
IMPACT
PROBABILITY
IMPACT
November 5-6, 2009
PROBABILITY
Copyright © 2009 PMI RiskSIG
Slide 47
Alfa Company Case
1. Available materials analysis
2. Risk Breakdown Matrix methodology application
• Alfa core process identification
• Potential risky causes analysis
• Risky events causes and process intersection
• Risky events identification
3. Identified risks must be divided into 2 big groups:
• Unique process linked risks
• Repetitive process linked risks
4. Unique process linked risk analysis: qualitative method is
based on expert judgment
November 5-6, 2009
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Slide 48
Risk Breakdown Matrix
November 5-6, 2009
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Slide 49
Risky events (1)
A specific consequence is associated with risky events identified
in RBM cells.
EVENT
CONSEQUENCE
1
Non-application of the existing development
process
2
Insufficient collaboration of suppliers in
partnership/codesign relations
3
Insufficient information from the marketing
sector
Lower innovation and quality degree towards
competitors
4
Lack of resources in product development
process
Product launch delays
5
Sensitive information diffusion
Information appropriation by competitors
6
Little reliability of funded dealers
Failed payback from the marketing network
7
Poor quality of supplied components
Production delays and non-quality cost
8
Failed optimization of productivity
Unsatisfied demand or underuse
9
Lack of Human and material Resources
Inadequate production (qualitative and quantitative)
Lack of materials on the line edge
Line breakdown
10
November 5-6, 2009
Missing deadlines
Product launch delays
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Slide 50
Unique process risks: a
qualitative approach
Event 3: “not sufficient information from the marketing sector",
imply a “lower innovation and quality degree towards competitor".
The search for quantitative measures describing the situation is both utopist and
having negative implications on reality.
Qualitative approach
Step 1 Single interviews
Events with lower
values are taken out
Step 2 Group interaction
November 5-6, 2009
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Slide 51
Unique process risks :
process card
PROCESSES
MARKETING
ACTIVITY
Resources
Commercial staff
Input
Market Information, product costs
Description To compare market demand with company
offer
Time
1 week; after market survey, before
product selling
Control
Marketing manager checks the analysis
Tools
Market survey, company cost database
Output
Product price
November 5-6, 2009
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Slide 52
Unique process risks :
scheda FMECA
Cod. Subprocesses
Failure
Modes
Causes
Effects
Expert
Criticality Index
Probability
(class label)
Impact
(class label)
Survey
methodology
Failure Modes
Actions to
Reduce Failure
mode
Pegging
selling
prices
Wrong
price
determi
nation
Wrong
market
inform
ation
Not
correct
market
target
Market
ing
manag
er
2-4
2-4
Benchmarking
on retail
network
Two
indipendent
market analysis
Pegging
selling
prices
Wrong
price
determi
nation
Mistak
es in
cost
evaluat
ion
Not
competit
ive
product
Compa
ny
control
ler
2-4
2-3
Benchmarking
on retail
network
Deeper
industrial cost
reporting
November 5-6, 2009
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Slide 53
Unique process risks :
FMEA + WASTE:
Cod.
Subproc
Pegging selling
prices
Waste
Mode
Excess of
data
collecting on
useless
sectors
November 5-6, 2009
Causes Effects
Survey
methodology
Waste Modes
Market
analysis
not well
focused
Definition of a
market analysis
standard
Incomplete
informatio
n for price
definition
Copyright © 2009 PMI RiskSIG
Actions to
Reduce
Waste mode
Deeper segmentation of
the market
Slide 54
Unique process risks: a
qualitative approach (step 1)
The results collected in the interviews to 2 experts about "not
sufficient information from the marketing sector " are
represented in the following fuzzy function.
IMPACT
PROBABILITY
1° expert
IMPACT
PROBABILITY
2° expert
November 5-6, 2009
Copyright © 2009 PMI RiskSIG
Slide 55
Unique process risks: a
qualitative approach (step 1)
On the basis of the 2 experts’ judgments we may
notice a partial discrepancy: different value ranges
about event manifestation probability and money
impact.
Should we chosen a one step elicitation process, at
that point we have to combine mathematically the
2 experts’ functions, by keeping in mind the
reliability degree associated to each expert.
November 5-6, 2009
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Slide 56
Unique process risks: a
qualitative approach (step 1)
In the graph below impact evaluations, combined the
2 expert’ judgments. The area colored in blue displays
the result of the intersection only.
IMPACT
November 5-6, 2009
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Slide 57
Unique process risks: a
qualitative approach (step 2)
Instead, the group interaction path is different: the goal is an exchange of views
and information sharing among experts, leading each expert to formulate a
judgment which is not exactly in harmony with that expressed by the others.
IMPACT
PROBABILITY
0.2
0.4
0.6
0.8
Group session effectiveness is well represented by the graph, reflecting the
uncertainty reduction initially associated to individual judgments. A lower
uncertainty means lower complexity: the analyst at this point has at his disposal
a range of possible values both in terms of probability and impact.
November 5-6, 2009
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Slide 58
Unique process risks:
Fuzzy Function
Event 5 :“Sensitive information diffusion” imply a
“Information appropriation by competitors”
IMPACT
PROBABILITY
IMPACT
PROBABILITY
1° expert
2° expert
November 5-6, 2009
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Slide 59
Unique process risks: a
qualitative approach
In this case both experts gave low values about the
manifestation probability and impact.
Following a Pareto analysis after all preliminary individual
evaluations, the event would inevitably fall within zone C
with the subsequent exclusion from the group analysis.
Such an exclusion is essentially linked to external and internal
resources cost: decreasing the number of events to be assessed
following individual interviews is fundamental to gather the
limited resources and employ them for the most important
events.
November 5-6, 2009
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Slide 60
Unique process risks: a
qualitative approach
In this case the agreement of the 2 judgments is carried out by the
project manager through a mathematical combination, where all
the experts’ judgments are equally considered. See graphs below.
IMPACT
PROBABILITY
0.2
November 5-6, 2009
0.4
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0.6
0.8
Slide 61
Unique process risks: a
qualitative approach
Event 2: “insufficient collaboration of suppliers in
partnership/codesign relations".
Information provided by expert are characterized by a very high
precision level. Unlike the 2 previous 2 risky events, no group
aggregation follows the individual interview.
IMPACT
PROBABILITY
0.2
November 5-6, 2009
0.4
0.6
Copyright © 2009 PMI RiskSIG
0.8
Slide 62
Unique process risks
Following a qualitative analysis of the risky events we
find risk map. The table below summarizes the results
obtained from the 3 events considered.
ID
Event
Impact
Probability
3
Not sufficient information from
the marketing sector
25.000 – 40.000 €
0.3 – 0.4
5
Sensitive information diffusion
5.000 – 25.000€
0.1 - 0.2
2
Insufficient collaboration of
suppliers in
partnership/codesign relations
83.000 – 85.000 €
0.2
November 5-6, 2009
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Slide 63
Unique process risks
This risk map is a bidimensional graph with the manifestation
probability on the x axis and impact on the y axis; each event is
represented by a segment. In this way we may have a direct picture of
assessment- associate uncertainty corresponding to the segment length.
[C. Chapman]
November 5-6, 2009
Copyright © 2009 PMI RiskSIG
Slide 64
Conclusion
The described methodology allows to analyze the
operational risks characterized by incomplete or by
low-quality data. This methodology proposes
framework integrating critical process analysis with a
careful understanding and managing of sources of
risks and waste. Following the proposed approach,
decision makers can identify, implement and review
strategies driving them towards efficiency The output
is a risk map that clearly shows relative importance
among the risks and clarifies interventions priorities.
November 5-6, 2009
Copyright © 2009 PMI RiskSIG
Slide 65
November 5-6, 2009
Copyright © 2009 PMI RiskSIG
A collaboration of the
PMI, Rome Italy Chapter
and the RiskSIG
“Project Risk Management –
An International Perspective”
RiskSIG - Advancing the State of the Art