This chapter raised some questions that we cannot answer in this course. The numerical cash flow decision-making models are covered in detail in our Engineering Economics (ESM 605) or Finance (BA 625) courses. Many of the numerical and non-numerical decision-making models are covered in Operations Research (ESM 621) and Engineering Decisions (ESM 694, tentative). The issues about probability and uncertainly are covered in Statistics (ESM 620) and the decisions course. In this chapter you had a quick overview, that's all.

The word risk implies we know the probability. If we can say, "we are 90% sure our competitors are not working on the this." We are expressing a risk. With uncertainty, the best we can say is, "we don't think our competitors are working on this." One of the class put it this way: Risk indicates that a decision was made based on known expected values of alternative courses of action. In order to have known expected values, one must also know the expected outcome of an action and the probability that it will occur. If these things are not known or cannot be determined, then expected values of alternative actions cannot be calculated and decisions must be made under conditions of uncertainty.

Q. I wonder if part of the popularity of consultancy firms is in that these firms are free to take the time to analyze (or submit) a proposal thoroughly and without extensive interference versus actually forming project management teams and allowing them the time without extraneous commitments to make an informed proposal of their own?
A. Perhaps, but the consultants often are not given much time to do their work and the management people who hire the "independent" consultant often tell them the results they want the consultant to report. "He who pays the fiddler calls the tune." Management will often use an outside consultant when their own people have too much inertia to get anything done, or when the thing that needs doing will be unpopular with the own people, layoffs for example.

Q. In the reading I am still not clear about the way to assign weight or value to different aspects of a project. It seems to me most of it is still based on opinion and I am not sure attaching numeric values to opinions and coming out with one number to make a final decision is totally clear to me. However I do see the process
A. The models sometimes hide uncertainty, because after you make the assumptions regarding the input parameters into the model, then you get a definite answer out. GIGO.

An example of Operational Necessity versus Competitive Models:
I once owned a coffee shop in Nome, and our primary product was espresso coffee. The coffee machine was a two group machine which meant that espresso could be drawn from two locations, simultaneously. It was an operational necessity that the machine was dependable so it could produce coffee everyday. When the machine was not in operation, I was out of business. The coffee machine did break down, we were out of business for about two weeks, so that the machine could get overhauled in Anchorage. The cost of the overhaul was about $2,000 but we faced a problem of do we spend the money on the overhaul, or buy a new machine for $8,000. Dependability of the machine was the operational necessity. We were faced with the decision on how much money did we want to spend to ensure that dependability.

The competitive necessity part of this example is that if we spent $8,000 on a new machine we could have had a three group machine, which meant we could produce 50% more espresso in a give time. This would have allowed us to service our customers faster during rush hour, which would have given us an advantage over our competitors.

Q. The window-of-opportunity approach attempts to determine specific costs and performance levels that must be attainable by a new technology or process before it can be considered for R&D. It calculates the expected costs and performance as a fraction or multiple of the cost and performance of an existing process or technology. First, baseline data must be collected on the existing process or technology, then any differences in the new technology or parts in the existing process that may be affected are noted. This information is then used to calculate the economic impact of the new technology or process, and a decision can be made to go forward or hold off on the innovation.
A. Window of Opportunity is similar to a "break-even analysis" in engineering economics, where we determine the feasible range of the input parameters. Say we calculate that we must sell 5000 of the new product to break-even. If we know we can 10,000 easily, the project will be undertaken. If we have never sold more that 1000, of a similar product, it is unlikely we should undertake this project.