Week 2 Flashcards

1
Q

Hazard vs Risk

A

Hazard
A hazard is something with the potential to cause harm
(e.g. when crossing a road cars are a hazard)

Risk
= likelihood x consequences

-> something additional (heavy machine is moving around) -> risk a person is in front of the machine, the driver can’t see the person

is the likelihood (probability) of harm taking place
(e.g. when crossing a highway, the risk of an accident) /

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Types of hazard

A
  • physical hazards -> e.g. someone falls form a roof
  • chemical hazards -> substances
  • biological hazards -> substances
  • psychological hazards -> hunman are getting sick because of stress
  • environmental hazards
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Hazard of a container ship

A
  • Weather
  • collision
  • human error
  • technical issue
  • grownding
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Formula risk

A

Risk = likelihood x consequences

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Hazard Switzerland

A
  1. Cyber
  2. Energy crisis
  3. Business interruption (e.g. Gotthard tunnel, war)

The impact of the energy crisis is a new risk entry and a core concern for firms.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Hazard Germany

A
  1. Business interruption -> supply chain disruption
  2. Cyber
  3. Energy crisis

Business interruption remains the top risk, while firms are also worried about the energy crisis.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Hazard Australia

A
  1. Natural catastrophe
  2. Business interruption
  3. Climate change

Natural catastrophe is the new top risk, drivne by events such as flooding, which resultetd in the country’s costliest-ever natural catastrophe

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Classifaction

A

Diversifiable Risk
* fire / flooding -> diversifiable

Undiversifiable Risk (e.g. inflation)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Classification of Risk
Pure risk vs Speculative Risk

A

Pure risk
* can only be negative (property risk)
* Property risk, people risk

Speculative risk
* coud be a positive and negative risk
* economic / market

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Difference between
* Hazard riks
* Operational risk
* Financial risk
* Strategic risk

A

Hazard risk
Arises from property, liability or peronnel losss exposure
* fire, never positive

Operational risk
Arises form people, processe, systems or controls
* cyber attack

Financial risk
Arises form the effect of market forces on financial assets or liabilities
* change in electricity prices -> could be positive and negative

Strategic risk
Arises form trends in the economy and socitey
* missing a trend -> could be positive, only a hype

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Analytical Tools and Statistics in Risk Management
Measuring the effectiveness of risk prevention measures

A

We rarely can link safety decisions to individuals / specific accidents, However, we often can get aggregate results
-> Seatbelts saved an estimated 14,955 lives in the United States in 2017

Except when we can’t:
Antilock brakes (ABS) have zero net effect on fatal crashes, people think they can drive faster because the breaks are better
-> Risk compensation theory

And sometimes the data are misleading:
since the introduction of steel helmets the number of head injuries has increased considerably … because before their introduction many of
those injured were killed outright

–> are we looking at the right thing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Taxonomy of Uncertainty

A

Taxonomy of Uncertainty

The known unknowns -> Aleatory uncertainty
describes the probability of future outcomes
determined by a known random process
(the known unknowns)

Unkown unknowns -> epistemic uncertainty
describes uncertainty regarding statements where causality and fundamental principles are only partially known

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Decision Tree

A

Structuring decisions allows us
to:
- Calculate the expected value of decisions
- Understand and combine the implicit assumptions of experts
- Calculate the value of perfect and imperfect information
- Update our state of knowledge as additional
information becomes available

Wir rechnen geringste Kosten aus und höchste Kosten -> bei Wahrscheinlichkeit XY
-> Differenz = Value of Information, dass wir sicher sind

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Bow tie analysis

A
  • what happens when we lost control and the hazard is releast -> what will happen then
  • left side: threats -> how can we prevent this?
  • rigt side: Cosequences -> how do we limit the extend of the consequences?
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Delphi method

A

we ask different experts one questions, then we write a factsheet and distribute this to everyone, but they don’t know which statement is from wich person -> Anonimity to avoid group dynamics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

How to avoid a catastrophe?
-> near misses

A

Near misses
There are often unremarked small failures that permeate day-to-day business but cause no immediate harm. People are hardwired to missinterpret or ignore the warning embedded in these failures.

Multiple near misses preceded every disaster and business crisis we studied and most of the misses were ignored and missread.

17
Q

How to avoid a catastrophe?
-> Cognitive biases conspire blind manager to the near misses

A

Normalization of deviance (Abweichungen)
* the tendency over time to accept anomalies (Unregelmässigkeiten)

Outcome bias
* When people observe successful outcomes, they tend to focus on the results more than on the complex processes that led to them. Whenn people observe a successful outcome, their natural tendency is to assume that the process that led to it was fundamentally sound, even when it demonstrably wansn’t.

18
Q

How to avoid a catastrophe?
-> latent errors and enabling conditions

A

Latent errors often exist for long periods of time before they combine wiht enabling condtions to produce a signifcant failure. Wheter an enabling condition transforms a near miss into a crisis generally depends on the chance; thus, it makes little sense to try to üredict or control enabling conditonts. Instead, companies should focus on identifiy and fixing latent errors.

19
Q

How to avoid a catastrophe?
-> Seven strategies can help mangers to recognize and learn from near misses Managers should.

A
  1. Heed High Pressure: be on alert when time or cost pressure are high
  2. Learn form Deivations: watch for deviations form the norm, do not think it is an acceptable risk
  3. Uncover the deviations’ root causes: don’t correct the symtoms, correct the cause
  4. Demand Accountability: hold themselves accountable for near misses, don’t downgrade the importance of near misses
  5. Consider worst-case scenarios: people tend to not to think through the possible negative consequences of near misses
  6. Evaluate projects at every stage: look for near misses masqueradin as successes
  7. Reward indivdiuals for exposing near misses
20
Q

Decision making
-> important facts

A

➢There are no risk-free activities
➢Risk management is a quantitive exercise
➢Risk management often involves a difficult tradeoff between financial considerations and human lives
➢There is a difference between voluntary and involuntary risk exposure, and among different risk magnitudes
➢ Organizational (e.g., principal-agent, culture, incentives) and individual (e.g., cognitive: small probabilities, tunnel vision) factors can have a significant impact
➢ Cannot expect to think logically in the middle of a crisis–scenarios, alternatives and decision guidelines need to be worked out ahead of time
➢ There is usually no «one correct answer»
➢ The rewards for taking the correct decision is «nothing» or a small loss
➢ Often the most significant risk is the one not modeled
➢ There is a difference between a good decision and a good outcome