Tuesday, August 16, 2016

Evaluating prospects -- alternatives

Daniel Kahneman and Amos Tversky may be a project manager's best friends when it comes to understanding decision making under conditions of risk. 

Of course, they've written a lot good stuff over the years.....my favorite is "Judgement under uncertainty: Heuristics and biases".

The original prospect thinking
Tversky and Kahneman are the original thinkers behind prospect theory..  Their 1979 paper in Econometrica is perhaps the best original document, and it's entitled: "Prospect Theory: An analysis of decision under risk".  It's worth a read [about 28 pages] to see how it fits project management

What's a prospect?

 A prospect is an opportunity or possibility with both an upside advantage and a downside risk. Said another way: by opting fo a prospect, you might gain something you don't have or lose something that you do have, that something usually measured in monetary terms.

Prospect theory addresses decision making when there is a choice between multiple prospects, and you have to choose one.

And, a prospect choice can be between something deterministic or certain and something probabilistic or uncertain.

What's the Theory? The big idea
So, here's the big idea: The theory predicts that for certain common conditions or combinations of choice, there will be violations of rational decision rules

Rational decision rules are those that say "decide according to the most advantgeous expected value [or the expected utility value]".  In other words, decide in favor of the maximum advantage [usually money] that is statistically predicted.

Ah yes! Statistics .... lies, damn lies, and statistics!
Shocking news -- sometimes, we ignore the statistics. Ergo: violations of rational decision rules.

Evaluating alternatives and prospects: Violations of decision rules driven by bias:
Prospect theory postulates that violations of decision rules are driven by several biases which we all have, to some degree or another:
  • Fear matters: Decision makers fear a loss of their current position [if it is not a loss] more than they are willing to risk on an uncertain opportunity.  Decision makers fear a sure loss more than a opportunity to recover [if it can avoid a sure loss] 
  • % matters: Decision makers assign more value to the "relative change in position" rather than the "end state of their position"
  • Starting point matters: The so-called "reference point" from which gain or loss is measured is all-important. (A small gain matters more to those that have nothing, than the same amount matters to those that have a lot) The reference point can either be the actual present situation, or the situation to which the decision maker aspires. Depending on the reference point, the entire decision might be made differently.
  • Gain can be a loss: Even if a relative loss is an absolute gain (to wit: I didn't get as much as I expected), the lesser outcome affects decision making as though it is a loss
  • Small probabilities are ignored: if the probabilities of a gain or a loss are very, very small, they are often ignored in the choice.  The choice is made on the opportunity value rather than the expected value.
  • Certainty trumps opportunity: a bird in hand ... in  a choice between a certain payoff and a probabilistic payoff, even if statistically more generous, the bias is for the certain payoff.
  • Sequence matters: the near-term counts for more. Depending upon the order or sequence of a string of choices, even if the statistical outcome is invariant to the sequence, the decision may be made differently.

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