Sensitivity: one or two assumptions

Methods and settings

Set target and axes

Choose the output in the correct period and scenario, then select X in the workspace. Enter an increasing low/high range in the displayed unit. Add Y for a two-dimensional test. Run the analysis and use the chart or table; expand the matrix when needed. No financial assumptions are committed by calculating the grid.

Base and tested points

The exact current input is included when it lies within the selected range. Integer restrictions can reduce the number of distinct points. A Base marker identifies the current context, not the average outcome. Invalid cells remain unavailable; a two-axis grid is not made valid by replacing unavailable cases with zero.

Interpret a two-axis example

For a supported LBO sponsor-return target, vary entry and exit assumptions within meaningful bounds. Each cell answers one pair of assumptions while the connected model is recalculated. It does not assign a probability to that cell. Similarly, a DCF output can be tested against eligible assumptions; distinguish this generic Layer from the DCF operator’s native sensitivity grids.

Check ownership and interaction

Both axes must be eligible and independently configurable for that target. Two references to overlapping coupled 13W profile components are not independent axes. Nonlinear relationships may need a narrower range and more focused follow-up. Re-run after changes to the underlying model or context; a stale grid describes the earlier model.

Public models do not store this analysis session

Sensitivity axis configuration, selections and result grids are not persisted in public model snapshots. Publication preserves operator inputs and deterministic operator outputs. After Fork, run this analysis again locally against the restored editable inputs. A reviewed change explicitly applied to an underlying operator input can be published as that input; the analysis session that produced it is still excluded.