A scenario is best built around a particular view of the future. Examples might be “Covid-19 Slow Demand Recovery” or, borrowing from Shell, “Sky Scenario: A technically possible, but challenging pathway for society to achieve the goals of the Paris Agreement”. Other scenarios may be built around single constraint assumptions such as Low CapEx, Base CapEx or High CapEx, where each assumption leads to a different set of “what and when”.
Useful scenarios can also be built by making assumptions about the top two or three items on the tornado charts (i.e. the items that have the most impact on the results). It is healthy to push these items to the extreme end of their respective ranges to help understand what program changes would result should those changes materialize.
Price is one factor that can be used to frame a scenario AND can also be used as a sensitivity variable in a sensitivity analysis. As an example, a scenario can be built around spending cash flow using a LOW price assumption. This could result in the selection of 50 projects over the next year. An alternative scenario could be built around spending cash flow using a HIGH price assumption. That might result in the selection of 80 projects over the next year. Either of these scenarios can then be subject to a sensitivity analysis at various different prices; if I choose the High price scenario (80 projects), what happens to my cash flow using a low price sensitivity?