Why Isn't Everyone Doing This Already?
As this paper has described, methods are available for addressing all of the reasons organizations choose the wrong projects, including quantitative methods for identifying the efficient frontier. Some organizations that regularly make high-stakes, project selection decisions, e.g. some financial institutions, oil and gas exploration companies, pharmaceutical companies, the military and some other government agencies, are already using many of these methods. But, most organizations are not. A fair question is, "If these methods are so great, why isn't everyone using them?"
In my experience there are two pitfalls explaining why these methods are not being used as much as they could be: fear
of complexity and a belief that there may be too much uncertainty to justify sophisticated methods.
Fear of Complexity
For some organizations, trying to select optimal project portfolios is just too complicated to tackle. Psychologists identify fear of complexity as one of the key pitfalls that prevent people from overcoming important problems. They point out that the perception of complexity is reduced, however, when people use information processing structures, i.e. description languages that provide a good fit to the complexities they encounter.
Systems modeling, the foundation for the methods described in this paper, is a language for describing and understanding complex problems because models break a complex problem down into its individual pieces. The critical components are sorted out, identified, and analyzed separately. Computers perform the required synthesis at the end. Thus, system modeling is the means for breaking down and overcoming complexity. As long as the concepts are understood, the fact that the math may be difficult is not really an issue; computers can handle the math.
Admittedly, systems modeling and the related methods described in this paper can themselves seem complex. Remember, though, that the most sophisticated tools need not be applied in all situations. If projects do not involve significant risks there is no need for probabilities and concepts like risk tolerance. More critical decisions require more sophisticated methods.
Follow the often quoted advice of Albert Einstein, "Seek the simplest possible solution, but no simpler." With learning and familiarity that come from experience, the appropriate methods will no longer seem complex. In any case, the real issue is not whether the methods seem complex, but rather whether the costs and effort required to apply the methods are justified in terms of increased value from better and more defensible decisions.
As sophisticated methods gain use, hard evidence of their value is beginning to surface. For example, an article in the journal Oilfield Review reported a study of 20 oil exploration companies that "established a strong positive correlation between the degree of sophistication in the companies' use of decision and risk analysis and the success of their project decisions." The same article also described another oil company study that found that "Companies that integrated workflow and used decision and risk analysis saw their performance improve shortly after the introduction of this methodology".
Discomfort with Uncertainty
The second pitfall is discomfort with uncertainty. People ask, "Doesn't the great uncertainty in the costs and benefits of projects invalidate the application of sophisticated mathematics to project selection?" My experience in discussions of this sort is that skeptics will quickly agree that sophisticated methods based on probability can work. Roughly 40 years, ago, for example, probabilistic analysis was used to "beat" the game of blackjack. The sticking point is whether the same methods have merit when probabilities must be based on subjective judgment rather than on "objective data."
1. W. Bailey, B. Couet, F. Lamb, and P. Rose, "Taking a Calculated Risk," Oilfield Review, Autumn 2000.