Decision Analysis and
Risk Management:
Two Sides of the
Same Coin
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Expert Reference Series of White Papers
Introduction
Every decision involves an analysis of possible future events (costs, outcomes, markets, etc.) and selection of a
choice among competing alternatives. Making a decision is making a selection.
Decision analysis is the process of dismantling a decision so as to determine the inputs and processes that
went into arriving at a decision.
Risk management is managing (preparing for) future uncertainties. Uncertainties are risks. They are the
unknowns associated with future events
.
The decisions we make today create the risks that we must manage tomorrow.
Risk management and decision analysis are effectively the same thing. They both involve the dismantling of
choices so as to understand the uncertainty of outcomes associated with particular options that have been, or
could be, made.
It follows that high quality decision making serves the purpose of risk management. If our decisions include a
thorough consideration of uncertainties
, then future risks are simplified or minimized.
But what is a high quality decision? How do we judge decision quality?
This white paper provides an outline of how to judge the quality of decisions by analyzing how effectively the
risks associated with various options have been analyzed. We begin with a definition for quality control in
decision making. This definition is then related to the four steps of the decision making process and finally to
the three types of error (risk) that occur in each of the four steps.
The paper concludes with an example of how methodical decision analysis leads to an understanding of the
degree of risk in a decision.
Defining Quality
Every decision is a balance between what we believe to be true and what we are forced to predict. Every deci-

(risks, implications) of future events. The quality of one’s decision making is measured according to how well
uncertainties have been considered.
Quality controlling decisions are based on analysis of risk. The thoroughness of the analysis determines the
“quality” of the decisions.
High quality decisions are not the best decisions in hindsight. They are the best decisions in foresight.
A high quality decision may not prove to be the optimum choice that could have been made. Instead, it is the
best decision that could have been made given the resources and information av
ailable at the time of the decision.
Decision Process
To fully understand the risks associated with a decision, and therefore to manage risks most effectively, it is
necessary to understand the four steps (broadly speaking) involved in making a decision.
1. Identify a problem
2.
Identify options or choices
3.
Comparative analysis
4. Make a decision or choice
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hen we speak of identifying a problem we mean recognition and interpretation of the problem. Your car is
dying of old age and you need to get to work every day. The problem might therefore be identified as “what to
do in terms of replacing the car”, or “how will I get to work if the car dies tomorrow”?
How one perceives the problem under consideration ultimately determines how the problem is analyzed in the
decision-making steps that follow. Do you need a new car or do you need inexpensive, flexible transportation
to work? How you frame the “problem” affects what choices are identified as possible solutions and how the
choices are ultimately compared.
Step 2 is the identification of options from which the selection will ultimately be made. The breadth and depth
of choices is determined by both the way the problem has been framed and the creative effort put into gener-
ating alternative choices.

be.
Unknown unknowns are risks (uncertainties) that are relevant to the decision but that are not included in the
analysis. This is the stuff that is ”off our radar”.
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hen choosing a new car the unknown unknowns are possible events like: the car manufacturer going bank-
rupt which voids the service warranty; repair parts being unavailable when needed; or the car being under-
insured in the event of a major accident.
Unknown unknowns are those possible events that you just would not normally think of in advance but could
crop up to cause problems.
Unknown unknowns are determined by your level of knowledge about a particular situation. The more
informed you are the fewer (or more obscure) the unknown unknowns.
For example, a lawyer can enter a courtroom with a full understanding of what to expect when defending a
client. They may be surprised by some events but the likelihood of surprise declines with a lawyer’s increasing
experience and knowledge base.
On the other hand, a layman who enters a court, preparing to defend himself, is likely to encounter many
unknown unknowns
. These are issues the layman was unaware needed to concern him. The more research and
education the layman undertakes before entering court, the fewer surprises there are likely to be.
Unknown unknowns are therefore the issues that increasing degrees of expertise will reveal.
The less you
know, the more unknown unknowns there are—that is, the fewer known unknowns that you know.
The third element of risk,
analytical bias
, relates to imperfections in our understanding and analysis of choices.
This is the stuff of habit, prejudice, and mental laziness.
Analytical bias may be referred to as the unknown unknowns of the known unknowns
. (Whew!) It is a conse-
quence of being human. Every analysis is a reflection (to some degree) of the person doing the analysis.