The visualization of analytical dynamics comes naturally to tools developed in Excel. This is largely due to the dynamic nature of graphs constructed in Excel. For example, if we wanted to depict the range of possible outcomes associated with specific decisions for which outcomes had a describable level of uncertainty or variation, it would be simple enough to introduce a random term into tabular forms of such estimates and then graph those tabular forms. As always, pressing the F9 key would simply draw another random number from the built-in generator, and augment associated data tables and plots to represent such the volatility of those outcomes.

For example, based on the Data Table generated in the Lobo's Reservations case, we could depict the variable nature of our results graphically using the high-low-close plot (tricked out a bit) provided in that workbook. Every time F9 is pressed we would see how much the variability in outcomes across policy types was subject to change (based simply on different separate and independent sets of random data draws). The result, as shown in Figure 1.1, would depict an alternative array of outcomes that could be associated with a set of decisions. Similarly with the second Data Table example in that case, shown in Figure 10.2.

This in itself might be entirely adequate in providing insights regarding the sufficiency of the number of variants examined.