five risk management rules for the project manager
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The top five risk management rules for the project managerTRANSCRIPT
1 Copyright 2011 Square Peg Consultiing, All Rights Reserved
Five rules for risk management A presentation
Produced by Square Peg Consulting, LLC
Orlando, Florida www.sqpegconsulting.com
What does PMBOK say about risk management?
• Risk: Events or conditions with uncertain potential to impact project objectives
• Risk management: Actions to minimize unfavorable impacts or maximize favorable possibilities
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More than Chapter 11; More than the risk register
• I want to forecast a risk (Chapter 11)
• I want to take a risk (Decision policy and risk-adjusted
process)
• I want to be confident (Risk adjusted estimating paradigms)
• I want to test my hypothesis (Risk adjusted reasoning
paradigms)
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Where’s the risk?
• In the baseline: work estimates, project architecture, product architecture
• Off the baseline: risk register possibilities
• In the ether: stakeholders, regulators, users, customers
• Friends and neighbors: portfolio and program dependencies
• Among opportunities: Do this, or perhaps that ….
• After it’s over: post-project adoption & support
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5 Rules: Begin with the end in mind
1. There are no facts about the future: Facts are in the past;
estimates, biases, and perception are the future
2. Requirements (and tests) are never complete: No one can
imagine everything
3. Central tendency rules the metrics: Optimism and
pessimism find a balance
4. Merge bias dominates schedule risk: Confidence takes a hit
when paths, work streams, or projects join
5. If it’s mission critical, it often takes a model: PRA isn’t for
everything
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(Rule 1) There’s no objective estimate
• Adjustment and Anchor bias: – Initial value sets anchor (Boss to Dilbert: I think it oughta cost …. )
– Anchor limits adjustment
• Representative bias: – A is part of B, B caused by A, A will cause B
– Because there’s progress now, there will be progress when …..
• Availability: – Imaginable, retrievable comparisons, easily recalled
– This is just like ……
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Amos Tversky and Daniel Kahneman: “Judgments under Uncertainty”
(Rule 1) Utility maps perceived reality
• Utility maps reality to perception
• Hubris inflates estimated advantage and mitigating effects
• Dread inflates expected impacts
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Hubris: This
solves
everything!
Dread: This is going to kill us!
Utility value
Objective
value
“Against the Gods” by Peter Bernstein
(Rule 1) Facts v. Future—Project balance sheet
• Sponsors are more optimistic (under estimate resources)
• Project managers are more pessimistic (over estimate risks)
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Value
Proposition
for the
Project
Management’s investment
Scope
Time
Resources
Quality
Project’s use of
investment
Risk gap
(Rule 2) Requirements are never complete
• Sampling errors in the V model
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Requirements
Specification (Backlog)
Vision
Strategy → goals
Validate
design/development
Verify deliverables
Correct
(refactor) errors
Sampled elicitation,
and elaboration
Iterate
(Rule 3) Central tendency is smoothing
• Asymmetrical extremes wash out • Pessimism and optimism balance
10 Copyright 2011 Square Peg Consultiing, All Rights Reserved Image: http://herdingcats.typepad.com/my_weblog/2011/05/deterministic-versus-probabilistic.html
Project
manager
Work package
manager
(Rule 3) Antithesis to Central Tendency
• Black swan: made famous by Nassim Taleb
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(Rule 3) Extreme impact events
• 3 rules of Black swans 1. An outlier, beyond realm of reasonable expectation, with
nothing in the past to convincingly point to its possibility 2. Carries an extreme impact 3. After the fact, it’s “explainable” and “predictable”
• 1% doctrine* – If the impact is extreme, no matter it’s probability, consider
the event a certainty
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* Ron Suskind: “The One Percent Doctrine”
(Rule 4) Merge bias dominates schedule risk
• Confidence degrades exponentially (geometrically) at joining paths
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Confidence: 64% ≤ 4
Confidence: 80% ≤ 4 Before merge
After merge
(Rule 4) Buffer to mitigate merge bias
• Akin to Critical Chain method *
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Plan slack (buffer) in one path
Eliyahu Goldratt: “Critical Chain”
Rule 5: It often takes a model
• Probabilistic risk analysis (PRA) of large number of conjunctive constituents may be meaningless (everything has to work = success)
• Model behavior, failures, and safety – Confirming (prediction & control)* – Exploratory (insight & understanding)*
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*Steve Phelan, The Interaction of complexity and management
Rule 5: Three common models
1. FMEA: Failure Mode and Effects Analysis** – MilStd 1629, NASA, Others
2. FTA: Fault tree analysis – Bell Telephone, Boeing, others
3. Event trees; Event Logic Diagrams
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** Also: FMECA, Failure Mode Effects and Criticality Analysis
Rule 5: FMEA is inductive
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Inductive: Observations Cause
Rule 5: FMEA Example
• How would you control the loss of a nail ?
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The author of this seminar
John C Goodpasture, PMP
Program manager, author, coach,
and instructor • PMI eSeminarsWorldsm instructor for
Advanced Risk Management, and Agile
Project Management
• Project coach in Europe, Asia, and the
United States
Portfolio manager and business unit
leader • Operations and IT professional
• System engineer in the Department of
Defense and the aerospace industry
johngoodpasture.com
Read more …..
• “PMBOK Risk Management Practice Standard”
• “Black Swan” by Nassim Taleb
• “Against the Gods” by Peter Bernstein
• “Judgments under Uncertainty” by Amos Tversky and Daniel Kahneman
• Probability and statistics online: Khan Academy videos (khanacademy.org)
• Schedule risk analysis by David Hulett (projectrisk.com)
• FMEA NASA Practice Standard, DoD MilStd 1629
• Project balance sheet (http://www.slideshare.net/jgoodpas/the-project-balance-sheet)
• “The Flaw of Averages” by Sam Savage
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22 Copyright 2011 Square Peg Consultiing, All Rights Reserved
All done and ready for questions!