Articulating Sensitivities to Boards: Clear Sensitivity Table Narration Language for Executive Settings

Step 1: Framing the Role of Sensitivity Table Narration in Executive Settings

A sensitivity table in a fairness opinion serves a precise and limited purpose: it shows how the valuation output changes when selected input assumptions move within reasonable, disclosed ranges. It is not a tool to re-argue the valuation model, revisit the transaction’s strategic logic, or imply a probability distribution. In executive settings—especially boardrooms—your narration should lower cognitive load, connect directly to the decision at hand (the fairness assessment), and avoid any language that could be misread as a value prediction. Think of the table as a transparent window into the mechanics of the model, not as a negotiation lever.

The sensitivity table supports the fairness conclusion by demonstrating robustness and by mapping key drivers to valuation effects. Boards want to see that if discount rates are modestly higher or lower, or if terminal growth is nudged up or down, the valuation behaves as expected and remains within a defensible range. The narration must therefore align with the overall conclusion: it should confirm that the base case is reasonable in light of disclosed scenarios and provide comfort that valuation shifts are understandable and bounded. If the table suggests large swings under small changes, your narration should calmly explain why (for example, because of the compounding effect in long-duration cash flows), without implying that such swings are likely.

Importantly, narration is about clarity and neutrality. It is not advocacy for a particular price. Avoid emotive words (for example, “optimistic,” “aggressive,” or “conservative”) unless your opinion explicitly defines and discloses them as technical calibration terms. Use precise, factual descriptors like “higher,” “lower,” “wider,” and “narrower,” and refer consistently to the base case. In executive contexts, consistency builds credibility, while inconsistency invites unnecessary questions.

Finally, your narration should integrate with the broader materials. It must reference the same base case assumptions used in the DCF or multiples analysis and should align with any ranges disclosed elsewhere. If the table relies on model simplifications—like a single-stage terminal period or constant margins—declare these plainly. Clarity on what the table includes and excludes is essential to avoid misinterpretation.

Step 2: A Reusable Micro-Structure for Narrating Any Sensitivity Table

Use a simple, repeatable structure to guide your narration. This micro-structure keeps your language tight and defensible, while making it easy for board members to follow.

• Context: Identify the base case and state the purpose of the table. Make clear that the table shows directional valuation effects when a specific driver moves within a disclosed range.
• Variable definition: Define the driver in plain terms. For instance, explain that WACC is the blended cost of capital, terminal growth affects the perpetuity assumption, EBITDA margin shapes operating profitability, revenue CAGR influences top-line scaling, and exit multiple reflects market comparables at the valuation horizon.
• Direction/magnitude: Describe how valuation changes when the variable is higher or lower. Use clear directional terms, and quantify the magnitude if it is helpful and accurate (for example, “moves approximately X% per Y change” if your model supports that precision). Point to the table ranges rather than inventing new ones.
• Boundaries/assumptions: State the bounds of the sensitivity (the low and high tested points), and declare any model features that limit interpretation (for example, single-stage vs. two-stage terminal value, or any cap/floor applied to margins). This section also covers non-linearities: warn if the relationship bends or steepens at the edges.
• Implication for valuation range: Conclude by mapping the sensitivity back to your fairness range. Clarify whether the deal price remains inside or outside the indicated valuation band under given points without implying probabilities. Separate sensitivity outcomes from your likelihood judgments; your role is to show the shape of valuation responses, not to estimate how likely those responses are.

This micro-structure is deliberately compact and scalable. You can apply it to a single-variable table (for example, WACC only) or a two-dimensional table (for example, WACC by terminal growth). In both cases, the structure creates a predictable listening pattern: what we are looking at, what it means, how it moves, where it is bounded, and how it informs the overall valuation view.

Step 3: US/UK Board-Ready Sentence Templates and Mini-Scripts for Common Sensitivity Dimensions

Below are standardized narration templates tuned for clarity, neutrality, and defensibility. The US versions are slightly more direct; the UK versions use a tone that is polite and measured. Choose the tone that fits your audience, but keep the structure and content consistent.

WACC / Discount Rate

• US: “This table shows how the indicated equity value changes as the weighted average cost of capital moves within the disclosed range. WACC reflects the blended return required by equity and debt providers. As WACC increases, the indicated value decreases; as WACC decreases, the indicated value increases. The table tests [X% to Y%] around the base case of [Z%]. Results at the edges reflect the standard present-value effect on long-duration cash flows. Within this range, the transaction price sits [inside/near/outside] the indicated values, which supports our stated fairness range.”
• UK: “The table illustrates the movement in indicated equity value as the weighted average cost of capital varies within the disclosed range. WACC represents the blended return expected by providers of capital. Higher WACC leads to lower indicated value, and lower WACC leads to higher indicated value. The analysis examines [X% to Y%] around a base case of [Z%]. The edge outcomes reflect the usual sensitivity of discounted cash flows to changes in the discount rate. Within these bounds, the consideration is [inside/near/outside] the indicated values, consistent with our fairness assessment.”

Terminal Growth

• US: “This table varies terminal growth within the disclosed range to show its effect on terminal value and total equity value. Terminal growth captures the long-run growth rate applied in the perpetuity phase. Higher terminal growth increases indicated values; lower terminal growth reduces them. We test [A% to B%] around a base case of [C%], using a standard perpetuity formulation. At higher values, the model remains bounded below WACC. The transaction price remains [inside/near/outside] the indicated range under these parameters.”
• UK: “We vary terminal growth within the disclosed range to indicate its effect on the terminal value and the resulting equity value. Terminal growth represents the long-run rate applicable in the perpetuity phase. Higher rates imply higher indicated values, while lower rates imply lower values. The analysis tests [A% to B%] around a base case of [C%], with a conventional perpetuity approach and a growth rate below the discount rate. The consideration remains [inside/near/outside] the indicated values under these assumptions.”

EBITDA Margin

• US: “This table shows the change in indicated value as EBITDA margin shifts within the disclosed range. EBITDA margin affects operating cash generation and, therefore, free cash flow. Higher margins translate to higher indicated values; lower margins reduce indicated values. We test [M% to N%] with a base case of [P%], holding other drivers constant as disclosed. At the upper and lower ends, effects are proportional to the margin change. The transaction price is [inside/near/outside] the indicated range for these scenarios.”
• UK: “The table presents the movement in indicated value as EBITDA margin varies within the disclosed range. EBITDA margin influences operating cash generation and free cash flow. Higher margins are associated with higher indicated values, while lower margins reduce values. We examine [M% to N%] around a base case of [P%], with other factors held constant as disclosed. Effects at the boundaries reflect the proportional relationship between margin and cash flow. The consideration lies [inside/near/outside] the indicated values within this set of assumptions.”

Revenue CAGR

• US: “This table varies revenue CAGR within the disclosed range to show the effect on indicated value via scale and operating leverage. Higher revenue growth increases indicated values; lower growth decreases them. We test [R% to S%] around a base case of [T%], with margins and capital intensity held as disclosed. At higher growth rates, the effect is amplified by operating leverage. The transaction price is [inside/near/outside] the resulting range.”
• UK: “We vary revenue CAGR across the disclosed range to indicate its influence on value through scale and operating leverage. Higher growth corresponds to higher indicated values; lower growth corresponds to lower values. The analysis reviews [R% to S%] around a base case of [T%], holding margin and investment assumptions as disclosed. At higher rates, operating leverage amplifies the effect. The consideration is [inside/near/outside] the indicated range.”

Exit Multiples

• US: “This table presents indicated values as the exit multiple varies within the disclosed range, reflecting market comparables at the horizon. Higher exit multiples yield higher indicated values; lower multiples yield lower values. The analysis tests [x.yx to z.zz] times EBITDA/revenue with a base case of [y.yy] times. The price is [inside/near/outside] the indicated range across these points.”
• UK: “The table shows indicated values as the exit multiple varies within the disclosed range, consistent with market comparables at the valuation horizon. Higher multiples are associated with higher indicated values; lower multiples with lower values. We examine [x.yx to z.zz] times EBITDA/revenue around a base case of [y.yy] times. The consideration is [inside/near/outside] the indicated values for the scenarios presented.”

In all templates, note the consistent elements: a clear definition of the driver, directionality, bounded ranges, and a direct linkage to the fairness range. The phrasing avoids probability language and speaks to relationships, not predictions.

Step 4: Practice and Refinement—How to Convert Raw Tables into Tight Narration, Avoid Pitfalls, and Prepare Q&A Defenses

When you convert a raw sensitivity table into narration, proceed in three passes: content check, structure, and wording. First, confirm that the table uses the disclosed base case, matches the time horizon and definitions used elsewhere, and applies reasonable ranges that align with the qualitative commentary. Second, apply the micro-structure to frame context, define variables, explain direction and magnitude, state boundaries and assumptions, and tie outcomes back to the valuation range. Third, adjust wording to the US/UK tone needed, ensuring consistent terminology with the rest of the materials.

Avoid common pitfalls that create confusion or undermine defensibility:

• Over-precision: Do not state exact percentage changes in value per basis-point shift unless the model’s linearity and stability justify it. If the relationship is non-linear, say so plainly and avoid a single conversion rate.
• Implicit probabilities: Do not call edge cases “unlikely” unless you have disclosed and supported likelihood judgments elsewhere. Sensitivity is about mapping responses, not ranking plausibility.
• Hidden assumption changes: Keep other drivers constant unless the table is explicitly a multi-driver sensitivity. If items co-move in reality, address that in narrative caveats, not by quietly changing inputs.
• Inconsistent anchors: Always restate the base case value and the tested range. If the board must search for the base case elsewhere, you increase cognitive load and risk misinterpretation.
• Unexplained non-linearities: If the table bends at the edges (for example, terminal growth approaching WACC), flag the mathematical reason simply and directly.

To preempt executive Q&A, build concise, standard defenses into your narration:

• State the base case clearly: “Our base case uses a WACC of [Z%], consistent with the assumptions in the DCF on page [X].”
• Anchor to disclosed ranges: “We test [X–Y] as disclosed in the methodology section; no additional scenarios are introduced here.”
• Flag non-linearities or model limits: “At the higher end of terminal growth, the relationship steepens because the perpetuity factor increases; we maintain growth below WACC to preserve model discipline.”
• Separate sensitivity from probability: “These outcomes show how value responds to assumption shifts; they do not assign likelihood or represent forecast scenarios.”
• Reaffirm the fairness lens: “Within the tested range, the consideration remains [inside/near/outside] our indicated valuation band, supporting the stated fairness conclusion.”

If questioned on why a simple change leads to a large value swing, refer to duration and compounding. For discount rate sensitivities, explain that longer-duration cash flows are more sensitive to discount changes, which is intrinsic to present-value mathematics. For terminal growth, clarify that a small change in the growth rate changes the perpetuity factor materially when applied to a large base of terminal-period cash flows.

If asked whether multiple drivers should be moved together, acknowledge the real-world co-movement but maintain the communicative utility of single-factor analysis: single-parameter tables isolate effects transparently. If needed, you can reference a scenario analysis elsewhere that co-moves drivers, but keep the sensitivity narration focused on the disclosed single-variable intent.

Finally, refine for brevity without sacrificing clarity. In high-stakes meetings, even well-prepared boards have limited time. Use short sentences, avoid jargon except where defined, and maintain a steady cadence: identify the driver, state the direction, cite the bounds, and link to the fairness range. Consistency across drivers helps board members track the logic quickly, compare effects across tables, and ask targeted, high-value questions.

By following this structure and language, you transform a dense table into a crisp narrative that supports decision-making. You show exactly what changes, by how much within disclosed bounds, why the movement occurs, and how it relates to the fairness conclusion—without implying probability, inviting re-litigation of the model, or overcomplicating the message. This disciplined approach makes your narration clear, neutral, and defensible across both US and UK board settings, and it scales effectively from simple, single-variable sensitivities to more complex two-dimensional tables. The result is a consistent, low-cognitive-load explanation that strengthens the credibility of the fairness opinion and helps the board focus on the decision in front of them.