APM North East branch evening event - Risk and Resilience: Towards a more effective narrative - 14 November 2019 - Newcastle

1. Research Consulting

2. Industrial Risk Reasoning Systems

3. Human Factors of Risk and Social Contracts

4. Resilience Systems Modelling

5. Industrial Reasoning Software
Global Mapping for Supply Chain Stress Testing and Risk
John will consider ‘the strategic gap’ in the industry-standard
approaches. He will lay out practical examples from the triple
challenge of ‘Motivation, Meaning & Measurement’ for the
design of Risk and Resilience Reasoning Systems to add
demonstrable insight and value.

6. Doing what is says on the tin…
•Practical examples from ‘the triple challenge’
•Motivation
•Meaning
•Measurement
•Design parameters of Risk and Resilience
Reasoning Systems to add demonstrable
insight and value.
•The strategic gap in the industry-standard
approaches to Risk and Resilience

7. Tolerance for
Complexity…
Risk and Resilience – Towards a More Effective Narrative…

9. What motivates us to pursue
Risk and Resilience Systems?

10. Motivation: Types of system this gives rise to
in practice?

11. Why do we crave simplification?

12. 5 Reasons why people are confused by risk?
• Naïve realism
• Assurance / Reporting led culture (and thinking)
• Incomprehension of the science
• Pragmatic obfuscation in silos
• The dominance of the desire for ‘simplification’ (as the
design constraint) rather than ‘complexity reduction’

13. Identify Discrete
Risk Events
Assess the
Probability Plot the
Probability Impact
Matrix
Choose
Prioritisation
Rubric
Consign Risk
Events to Action
CategoriesAssess the
Impact
Repeat Xn times
with frequency Z

14. Identify Discrete
Risk Events
Assess the
Probability Plot the
Probability Impact
Matrix
Choose
Prioritisation
Rubric
Consign Risk
Events to Action
CategoriesAssess the
Impact
Repeat Xn times
with frequency Z
• Epistemologically unsound – has the imprimatur of science
• Etymologically incoherent – uses words interchangeably
• Operational logic is weak – not based on model of the target
• Organisational Psychology is non existent – e.g. decision theory
and bias
• Statistical rigour is completely absent – e.g. just everything really
Did you design this system yourself or did you inherit it?
Did you have evidence that it adds demonstrable insight and
value?
Should you use bad science to promise what only good science can deliver?

15. Tolerance for
Complexity…
Risk and Resilience – Towards a More Effective Narrative…

17. Risk is…

18. “Risk is a conceptual pollutant”
Jack Dowie 1999

19. ‘Risk’, whether used separately or in conjunction
with other terms (as in expressions such as risk
assessment, risk factors, acceptable risk, and risk
communication) is an obstacle to improved decision
and policy making. Its multiple and ambiguous
usages persistently jeopardize the separation of the
tasks of identifying and evaluating relevant evidence
on the one hand, and eliciting and processing
necessary value judgements on the other.
Jack Dowie 1999

20. Ethics Diligence Providence Pedantry
POLICY
NARRATIVE
PROCESS
NARRATIVE
Assurance

21. Risk is a (dialectic) narrative system

22. Risk is a (dual appetite) dynamic
system

23. 5 Questions
Technical General Global Strategic Licence
Risk Definition
Knowledge Extraction
Control Features
Expert Judgement
Business Integration
The Key to Narrative 5 Industry Dialects

24. Technical General Global Strategic Licence
Risk Definition
Knowledge
Extraction
Control
Features
Expert
Judgement
Business
Integration
Micro Risk
(Very small discretised)
Project Risk Programmatic Risk
Strategic or
Corporate Risk
Business Ethos Risk
Re-scripting of
Technical
Knowledge
Aggregation of
generalised event
descriptors
Forming Reasoning
Constructs
Strategic
Intentionality
Impact Analysis
Econometric
Forecasting
Mainly around
identification and
”measurement”
Risk by Risk Action
and Responsibility
planning
Performance
Shaping Factors
Satisficing for Audit Narrative Diligence
Domain dependent
Operational
Process-Led
Discipline
Organisational
Goal Alignment
Strategy
Development
Controlling Values
and Senior
Judgement
Independent Assurance Process
Integrated in
Control Decisions
Strategic Course
Correction
Corporate Policy
Drivers

25. Technical General Global Strategic Licence
Risk Definition
Knowledge
Extraction
Control
Features
Expert
Judgement
Business
Integration
Micro Risk
(Very small discretised)
Project Risk Programmatic Risk
Strategic or
Corporate Risk
Business Ethos Risk
Re-scripting of
Technical
Knowledge
Aggregation of
generalised event
descriptors
Forming Reasoning
Constructs
Strategic
Intentionality
Impact Analysis
Econometric
Forecasting
Mainly around
identification and
”measurement”
Risk by Risk Action
and Responsibility
planning
Performance
Shaping Factors
Satisficing for Audit Narrative Diligence
Domain dependent
Operational
Process-Led
Discipline
Organisational
Goal Alignment
Strategy
Development
Controlling Values
and Senior
Judgement
Independent Assurance Process
Integrated in
Control Decisions
Strategic Course
Correction
Corporate Policy
Drivers

26. Tolerance for
Complexity…
Risk and Resilience – Towards a More Effective Narrative…

27. Doing what is says on the tin…
•Practical examples from ‘the triple challenge’
•Motivation
•Meaning
•Measurement
•Design parameters of Risk and Resilience
Reasoning Systems to add demonstrable
insight and value.
•The strategic gap in the industry-standard
approaches to Risk and Resilience

28. Measurement?

29. Why do we crave simplification?

30. Risk = Probability x Impact

31. If you ask people to define what they mean
by probability…
CONTINUOUS UNCERTAINTY
Stochastic: Situations or models containing a random element, hence unpredictable and without a
stable pattern or order. Businesses and open economies are stochastic systems because their internal
environments are affected by random events in the external environment.
KNOWABLE PREDICTABILITY
Frequentist: Situations containing frequent events where an event's probability can be expressed as
the limit of its relative frequency over many observations. Experimental scientists can determine
probability by repeatable objective trials.
…they usually look at you as if it is you who has a
problem with reality

32. People get probability, right?
In the toss of a fair coin what is the probability of a head or a tail?
= 50%
= 100%
= 99.99999999…%
Cognitive
Heuristic

33. People get probability, right?
In four tosses of a fair coin which is the more probable outcome
HTH or HHH?

34. So does that mean that HHH or HHT or HTH or HTT or TTT or
TTH or THT or THH are not equally likely outcomes?
Application of Hombas’s technique (1997) to all possible
triplets shows that “waiting times” range from 8 to 14 tosses
• HHH and TTT have the longest waiting time - 14 tosses in
both cases
• HTH and THT have a medium waiting time – 10 tosses
• All other triplets have a shorter waiting time – 8 tosses
THTH will beat HTHH in a race about 64 times out of 100

35. “The phenomena discussed in this article are illustrative of
counterintuitive relationships that can hold among probabilistic
variables…
… Such surprises are compelling evidence of the wisdom of caution
in drawing conclusions about probabilistic relationships even if they
appear, at first blush, to be obvious.”
Nickerson (p527,528)
Risk Can = Probability x Impact but
even the simplest probability
judgements are counter-intuitive
to untrained people

36. Is the most representative form of probability in a
risk register…

37. If you ask people to define what they mean
by probability…
CONTINUOUS UNCERTAINTY
Stochastic: Situations or models containing a random element, hence unpredictable and without a
stable pattern or order. Businesses and open economies are stochastic systems because their internal
environments are affected by random events in the external environment.
KNOWABLE PREDICTABILITY
Frequentist: Situations containing frequent events where an event's probability can be expressed as
the limit of its relative frequency over many observations. Experimental scientists can determine
probability by repeatable objective trials.
…they usually look at you as if it is you who has a
problem with reality
EXPECTED BELIEF
Bayesian: Situations requiring an interpretation in which, instead of frequency or propensity of some
phenomenon, probability is interpreted as reasonable expectation representing a state of knowledge
quantifying a rational or personal belief.

38. YOU CANNOT ADD DEMONSTRABLE INSIGHT AND VALUE

39. Tolerance for
Complexity…
Risk and Resilience – Towards a More
Effective Narrative?

40. Better Risk Measurement
= Better Risk Modelling

41. Model With Real Business Outcome Values
Narrative = General (Programme)

42. Adopt a Psychometric Approach
Narrative = Strategic

43. Model Volatility Instead of Probability
Narrative = Global

44. Model risk relative to the value chain
Narrative = Strategic

45. Use phenomenological data
Narrative = Licence

46. Any Risk or Resilience reasoning system must be
both elegant and fit for purpose

47. Understanding the Relationship Between
these Factors Leads to a More Effective
Narrative in Any Risk or Resilience System…

48. An Example of a More
Effective Narrative -
Resilience

49. Question:
How do you increase the
resilience of a 5.3 Billion
Euro Supply Chain?

52. Speaking multiple and
nuanced dialects of risk to
suit the
“Plan-Source-Make-Deliver”
context

53. PLAN

54. SOURCE

55. MAKE

56. DELIVER

57. This adds demonstrable insight because it curates
a complexity-reducing narrative that the business
can act upon
This adds demonstrable value because the
outcomes are expressed in business value

58. A More Effective Narrative in Any Risk or
Resilience System…
4 Rules to Help you Plan

59. Semmatics Abstraction Measurement Materiality
Towards a More Effective Narrative…
Exposure and
Control
External Data and
Business Outcomes
Heuristic and
Cost Benefit
Countermeasure and Cost
and Continuing Risk

61. The strategic gap in the industry-standard approaches
to Risk and Resilience
YOU

62. jon@j-arthur-consult.co.uk
07795612950
Reach back out