How to Answer “How do you build a DCF sensitivity table (e.g., WACC vs. terminal growth or exit multiple)?” in Investment Banking Interviews

Start by stating you only build sensitivities after the base DCF is complete and consistent. Your model should have one clear output cell that you’ll table—most commonly implied equity value per share (or equity value), already reflecting: PV of forecast free cash flows, PV of terminal value, the enterprise-to-equity bridge (net debt and other adjustments), and diluted shares.

Emphasise auditability: the sensitivity table must reference one output cell that updates as inputs change. In interviews, implied price per share is often the cleanest output because it’s directly interpretable; if you use enterprise value, you should say how you’ll bridge to equity.

Clarify the terminal value method before you build the table (perpetuity growth vs exit multiple) and avoid mixing terminal approaches in one grid.

Explain that the classic two-way sensitivity varies WACC on one axis and a terminal driver on the other:

• WACC vs terminal growth (g) if using a perpetuity-growth terminal value.
• WACC vs exit multiple (e.g., EV/EBITDA) if using an exit-multiple terminal value.

For ranges, show judgement rather than arbitrary spreads. A typical interview-ready setup might use 5–9 points per axis (e.g., WACC in 0.5% increments across a ~2–3% band; g in 0.25% increments across ~0.5–1.0%; exit multiple in 0.5x increments across ~2–4 turns), centred on your base case.

Add reasonableness anchors: terminal growth should generally be below long-run nominal growth in the relevant market; exit multiples should be consistent with comps/precedents and your forecast-year margins.

Walk through the Excel mechanics clearly (this is where many candidates get vague). You create a grid where the top-left cell (the cell above the matrix) links to your chosen DCF output (e.g., implied share price).

Then:

• Put one variable down the rows (e.g., WACC values).
• Put the other variable across the columns (e.g., terminal growth rates or exit multiples).

Use Excel What-If Analysis → Data Table:

• The Row input cell must link to the model assumption cell for the row variable (e.g., the WACC input cell).
• The Column input cell must link to the model assumption cell for the column variable (e.g., terminal growth or exit multiple input).

Practical modelling hygiene: keep sensitised assumptions in dedicated input cells (not hard-coded inside formulas), and remember data tables can slow large models—so you may switch calculation settings once built.

After the table populates, sanity-check it quickly. Valuation should decrease as WACC increases, and increase as terminal growth or exit multiple increases. If it’s not monotonic, it usually means the table references the wrong input cells, the output cell doesn’t depend on the inputs you’re varying, or there’s a circularity issue.

Then interpret the output like an analyst: call out the base-case cell and summarise a reasonable valuation band around it rather than presenting a single point estimate. In dcf sensitivity analysis in investment banking, WACC and terminal value often drive a large portion of the valuation, so the table is a tool to communicate robustness.

Close with an insight: if small moves in WACC or terminal assumptions swing value materially, revisit discount rate inputs (beta/ERP, capital structure, after-tax cost of debt) and ensure the terminal assumptions are consistent with the business’s long-term economics.