DECISION MAKING TOOL

WHY USE IT?

Impulsive, reactive decision making has no place in strategy creation and execution.

Seeking more evidence in lieu of forming an opinion of the situation can avoid jumping to the wrong conclusion and over-reliance on anecdote.

We can be "primed" by an initial piece of information (valid or not) in making comparisons and decisions.

Averaging multiple judgments yields an estimate more accurate than its individual components, on average.

In decision making, people often focus on irrelevant information rather than considering prior knowledge of the probability that something will occur.

Not looking for "reversion to the mean" is a trap: We see an outcome that in reality is extreme and unlikely to occur again, but we tend to predict it will recur.

Requiring or accepting that a choice must be made among limited strategy options is a false dilemma. But too many options can inhibit decision making. 

Power can lead to bad decision making.

The meaning of a situation or set of circumstances comes from the frame in which we view it. Reframing the "facts" gives the situation new meaning.

“Experts” who deal with the future and base their skills on the non-repeatable past (except short-term physical processes) “are close to a fraud, performing no better than a computer, blinded by intuition.” – Nassim Nicholas Taleb

A sunk cost is paid: It can't be recovered. Escalation of commitment to an activity based on sunk costs can block needed change and limit innovation.

Considering opportunity costs in strategy decisions helps ensure wise use of scarce resources.

Statistical analysis can lead to false conclusions because of bad data, loose confidence intervals, sample bias and erroneous assumptions. Bayesians look for the base rate and then revise predictions in light of new evidence.

Planning as group learning combats shared information bias and narrow framing.

Using a checklist, simulating, doing a pre-mortem and keeping score helps assure the quality of strategy decisions.