MBA 8473 – Handout on implications of biases on DSS Design/
Deployment and De-biasing.
Name of the
bias
Framing effect
Availability bias
Overconfidence
bias
Illusion of
control
Implication consideration
DSS Design/ Deployment
(L.O. 52.A)
Positive framing of alternate
propositions lead to risk
averse behavior.
Debiasing (L.O. 52.B) capabilities
to be used in a DSS
 Explain what is meant by risk.
 Allow multiple alternate
framing capability.
 Make the decision makers
Negative framing of alternate
aware of the equivalence of
propositions lead to risk
alternate framing.
taking behavior.
Wrong estimates of
 Allow collection of ‘wider
probability or frequency of
range’ of data.
occurrence of an event.
 Allow de-categorization
 Simulation capability of
Biases estimates of
alternate hypothesis.
relationships, such as causal
 Synthesis capability of data
relationships, correlation,
viewed through different
and trends.
template.
More data (on the same
variable or factors under
consideration) leads,
wrongly, to more confidence.

Selectively seeking out
information that supports a
position, while disregarding
contradictory information.

Preempts collection of
disconfirming evidence.

Chance outcomes mistaken
for skill.

Regression effect ‘Outlier’ wrongly
emphasized to be new
normal or average behavior.



Sensitize the user to the
plummeting marginal return
of confidence with additional
data. (Maintain historical
examples.)
Allow alternative ideas or
hypothesis to be tested.
Allow (1) inductive logic (as
compared to) deductive logic
only) and (2) modeling.
Allow story telling (example:
case based systems)
De-emphasize significance of
repeat or successive success
or failures.
Allow visual (graphic
simulation) capability to show
the long term trend of the
phenomenon involved.
Keep historical score of past
outliers and their
‘performance.’