1. Terminology 7 basic terms Risk Elements Risk Measures
Events – must have a loss
Sources (Causes, Hazards, Threats, Capability, Intent, Targeting) don’t have a loss
Consequences (Objectives, Assets)
Controls (Treatments)
Risk Measures
Likelihood (Probability)
Impact
Risk

2. Riskion Wording Template

3. Tie it together with a Bowtie Diagram

4. Comprehensive and Scientific Approach to Risk Analysis and Management
Hierarchy of Sources
Measurable and ‘Unmeasurable”
Hierarchy of Objectives
Quantitative and Qualitative
Many to many to many relationships
Inheritance and reciprocity

5. Comprehensive and Scientific Approach to Risk Analysis and Management
Matrix theory
Principle Right Eigenvectors for computing ratio scale priorities from ordinal input
Measurement theory
Monte Carlo simulations
Bayesian analysis
Queueing theory
Nonlinear integer optimization

6. Measuring/Estimating Likelihood of Events
Dependent on Sources?
Not necessary but often convenient
Understanding
What is known or can be estimated
e.g. accident given snow, rain, clear
Especially if you are estimating for Miami vs. St. Paul Mn

7. Riskion: Sources Contribute To:

8. Riskion: Sources Contribute To:

9. Mutually Exclusive
Both sources and events ‘should’ be mutually exclusive of one another
Otherwise, their likelihoods could exceed 100%
E.g. 2 sources for an event –
Shouldn’t double count the intersection
Riskion accounts for this by doing Monte Carlo Simulations as you will see soon

10. Measurements (estimates) from where?
Logic, History, Judgment
Measurement properties
Levels of Measurement
Nominal
Ordinal
Interval
Ratio
Needs for ratio scale measures to produce risks measures that are scientifically meaningful
Otherwise it is mathematically meaningless to multiply likelihood by impact when calculating risk
Also will need to take sum products of source likelihoods and event likelihoods given sources to compute event likelihoods (will see this on bow-tie diagram shortly)
Also will need to take sum products of event consequences on objectives and the priority of objectives to compute event impact (will see this on bow-tie diagram shortly)

11. Absolute and relative measures
Absolute represents likelihood of the source or event occurring
Relative represents the likelihood compared to the likelihood of other sources or events
Either adequate for many analyses
Optimizing Allocation of budget to treatments
Absolute better for some
Communicating
Deciding on treatments for a specific event on an event by event basis

12. Likelihood Measurements/Estimates How?
TAPPS
In practice, how are source or event likelihoods measured or estimated?
Identify processes, methods, tools for measuring/estimating the likelihood of risk events

13. Riskion Likelihood Measurement Methods
Rating Scale Most Common
Pairwise with Given likelihood
Direct
Step Function
Utility Curve
Pairwise of Probabilities
Pairwise Comparisons
Bayesian Updating

14. Two aspects of measurement in Riskion
1) Defining what measurement method to use for each source and event
PM does this in Structuring the model
2) Providing data and/or judgments
This is a separate step and conducted after the model is ‘set up’ and measurement methods and roles defined
It can be performed in ‘anytime’ or ‘teamtime’ modes
It can be performed on smartphones, tables, or computers – Silverlight is not needed
Participants do this in evaluating the model

15. Direct Measurement – if you know likelihoods of components from some database or simulations or …

16. Deriving Likelihoods from Pairwise Relative Comparisons
AHP math for deriving priorities from judgments
The $25 Billion dollar Eigenvector
AHP fundamental verbal scale
ordinal in, ratio out?
Redundancy and variety
Measure of inconsistency
Area Validation
Examining/reducing inconsistency

17. SQUARE C CIRCLE A RECTANGLE E DIAMOND D TRIANGLE B
1 Equal Equal to Moderate 3 Moderate Moderate to Strong 5 Strong 6 Strong to Very Strong 7 Very Strong 8 Very Strong to Extreme 9 Extreme
1. Circle A is _________ times larger than Triangle B
2. Allocate $100 among the five shapes in proportion to the area of each shape. (Write the amount you would allocate inside each shape).

18. Area Validation Exercise
Purpose
Verbal
Less Accurate
More ‘Appropriate’
Can enter judgments (computer or tablet or smartphone)

19. Measurement Options for Pairwise
Number of judgments
N*(N-1)/2 for all pairs
N-1+N-2 for 2 diagonals
N-1 for 1 diagonal
How many to show on a page
Verbal or Graphical
** In order for verbal to produce ratio scale measures, adequate redundancy and variety are required.
Otherwise use graphical/numerical

20. Pairwise with Known Likelihood
If know the likelihood of one source or event
Derive relative likelihoods for a set with pairwise comparisons
Normalize to the likelihood of the known source or event

23. Pairwise of Probabilities

24. Pairwise of Probabilities -- rates
Queueing Theory
Lambda is arrival rate –uniform, independent
Time to next arrival – Erlang probability distribution
Number of arrivals in unit of time – Poisson probability distribution
From Excel:
A process with an arrival rate of 1 per time interval has a .368 prob of no arrivals so a 63.2 prob of an arrival (event)
See preceding slide

26. Pairwise of Probabilities

27. Ratings – with ratio scale measures
Use pre-defined scales (ok, but not recommended in general)
Define intensities
Assign likelihoods (not recommended)
Derive likelihoods
Certain = 1
Example – do an assessment for a ‘Likert 1-5 scale’ for a specific source or event….

28. Utility curves

29. Step functions