The result of each simulation is both an absolute and a normalized risk index. The unit for the absolute index is currency and is simply the standard deviation of the possible economic outcomes of the business case. The normalized risk index is the ratio of the standard deviation and the expected, or average, economic outcome.
Another important result from these simulations is the exposure of the critical variables in the project's performance. Many organizations do not track ongoing project performance, and only some do passively track results. Knowing which variables have the largest or most pertinent effect on a project's economic performance allows "active tracking," in which critical variables are tracked over time and compared to predicted values. In this way, a project manager can see when some facet of the project has gone awry and, critically, take the proper action in response.
Two examples clarify this proposition:
* An aircraft pilot follows a given glide path for his approach to a landing strip. The instruments alert the pilot when the aircraft leaves the glide path and the pilot makes active corrections to bring the aircraft back on the proper course.
* A manager heading the development of a new product finds that of three variables — delivery date, manufacture cost and project budget — two have the largest impact on the eventual profitability of his product — delivery date and manufactured cost. Knowing this, the product manager is willing to expand the project budget by adding additional resources to meet a delivery date, knowing that this one-time cost would not significantly degrade the eventual profitability of the program.
Once the benefits and risks for each potential component have been identified and quantified, they can be aggregated for an analysis of the proposed portfolio as a whole. The first step in this process is the ranking of the components by the indicators of financial return, risk, strategic alignment and others unique or important to the organization's business or technical environment (e.g. interoperation with existing computing platforms). These variables must be weighted to reflect their relative importance to the organization.
The organization's strategic alignment guides the weighting of the variables. For instance, if the firm's goal is to grow by merger and acquisition, then greater weight might be given to platform interoperability to ensure smooth and fast integration of new corporate elements, to lower acquisition costs and to ensure that the new assets produces profits as soon as possible. If the firm is the technology leader, then management might place emphasis on ground-breaking technologies that will attract innovator and early adopter customers willing to pay a premium for access to the latest technology. This weighting should take place external to the technology purchase process to avoid bias in favor of one project or another.
Organizations may also want to introduce a range of allowable values for each indicator. Indicators whose value falls outside this range would be considered "deal breakers" that automatically eliminate the project from consideration. For instance, there may be an upper limit to the amount of risk an organization may be willing to bear; this risk limit would be represented by a maximum allowable value for the risk variable. Similarly, an organization planning to merge with another within two years may prohibit projects that do not show a positive return in that time or add significant permanent headcount in that time.
Once the indicators are chosen and weighted, each component's score is simply an average of their weighted variables. These scores are ranked from highest to lowest. In reviewing this list, managers should be aware that it is only a ranked list, not an optimized portfolio. There is one final step needed to ensure the optimum mix of components.
The "Efficient Frontier"
Choosing the optimum set of components might seem to be a simple task of beginning at the top of the ranked list and selecting projects until a budget, personnel or capital constraint is met. However, a highly-ranked component may consume an inordinate amount of one resource or another and thereby prohibit the inclusion of another highly-ranked component. Choosing the best possible mix of components within these constraints is a matter of plotting the value of each portfolio (each portfolio's aggregate score) against that portfolio's combined risk.