Summary
Even with unbiased judgments and project calculations, an insidious bias
will still be present in an approved projects portfolio. The screening and
ranking process used to select projects causes an optimizer’s curse (OC) effect
(Smith and Winkler 2006). A portfolio's true outcome value will tend to fall
below the forecast distribution mean. Stated another way, we should expect to
be disappointed in the value of the eventual outcomes. This optimizer’s curse
effect can be huge: the true portfolio value might be half its forecast value
when forecast in the usual way.
This paper describes a correction process based upon Bayesian inversion
obtained with Monte Carlo simulation. Estimate/Actual distributions
characterize component evaluation errors. The mean and standard deviation of
the E/A distribution measures the quality of judgments and estimates. Examples
demonstrate the value of better information in project or asset evaluation,
portfolio optimization, and competitive bidding.
The premise of our approach to correct for optimizer’s curse is
straightforward enough, though implementing this method requires judging the
population of evaluated projects—or at least assessing the shape of this
population’s distribution. We offer a process and guidelines for correcting for
the optimizer’s curse in both project and portfolio value calculations.
Correcting estimates for systematic biases restores luster to the recommended
expected value-maximizing decision policy. We also tie back to the winner’s
curse phenomenon (Capen et al. 1971) experienced in competitive bidding and how
it affects bid optimization.
Preface—Why Project Managers Should Be Interested
Most of this paper deals with the optimizer’s curse afflicting project
appraisal, selection, and portfolio management processes. Project management
begins well before a project is commissioned. Project requirements and scope
define the project, and project modeling is usually the basis for forecasting
costs, schedule, and, perhaps, performance.
Depending upon the quality of a candidate project, substantial project
planning may be required for the economic evaluation. Very poor projects are
easy to reject, and very good projects are easy to approve. Marginal projects
require the most evaluation effort, and this typically involves detailed
project design and planning in order to obtain confident estimates of costs,
schedule, and performance under uncertainty.
Following are some additional thoughts about what we feel are the most
important aspects for project management.
Consolidating Decision Criteria. Making tradeoffs is inevitable, and
decision making is more complicated with multiple criteria. We recommend
translating all criteria into monetary-equivalents. Project cost is in the
money units already, though best if translated into after-tax, present value.
Translating schedule and performance into monetary terms is straightforward, as
these directly affect value to the asset owner: The project appraisal model
represents how schedule and performance drive project value. Health, safety,
environment and other considerations also influence project value, and the most
straightforward way to reflect these dimensions is to convert their metrics
into monetary-equivalents (e.g., $25/ton of CO2 abatement). (Please note that
all costs in this paper are presented in U.S. dollars.)
© 2008. Society of Petroleum Engineers
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History
- Original manuscript received:
11 February 2007
- Meeting paper published:
1 April 2007
- Revised manuscript received:
30 October 2007
- Manuscript approved:
25 October 2007
- Version of record:
15 March 2008
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