How to turn uncertainty-led analysis into something leaders can read, present, and act on.
Alternatively, are you still building the concepts?
What do you say?What do you show?And when?
You've built the range. Walked into the room with it. And watched the conversation stall anyway: too much detail, too much hedging, or one number got picked out and the rest ignored.
The analysis and insight were probably fine. The delivery just didn't match the room.
But this? This might work...
We recommend Strategy B. Expect it to land nearer $118M than the $142M base case, given capacity constraints, with upside of $40M per year for every $10/bbl over the price deck, unless oil falls to $28/bbl, where the case breaks even.
That's what landing sounds like. The rest of this page is how you build one for your own numbers.
It depends. But there's a structure to it.
Options and ranges are a means.
What stakeholders need from them is the recommendation, the insight, the milestones, and the deltas that matter to them.
How you surface those depends on who's in the room, what they know, their risk appetite, and what the decision is. The choices later on this page map to exactly that.
Why it didn't land before
Most of the communication work happens before the final presentation.
Stakeholder engagement should run throughout the whole process.
Ideas need airtime. The goal is that nothing in the final presentation is a surprise, especially the bad scenarios. Each stakeholder has individual stakes. What's right for the portfolio may need to be worked through with some stakeholders, not just presented to them: buy-in built, compromises agreed: a loop of raising something, testing it against the model, and coming back with an answer. And then testing it with everyone else!
The analysis feeds this loop directly: concrete (if preliminary) numbers from the model often refine what stakeholders meant by their risk appetite, or their earlier definition of what success should look like. It only works if the 'dig in' step is fast enough to run more than once.
Not a one-way funnel — engagement iterates throughout the process.
Say it like a recommendation.
Everything before this is evaluation: the scenarios, the thinking, the engagement, the iteration.
This is the output:
We recommend [option], because [the driver that matters], unless [the condition that would flip it]. The risks that matter most are [A, B, C]; the decisions worth getting right are [the ones that actually move the outcome].
That's the paragraph your analysis has been building toward.
Next: what gives it substance, and how you show it.
The average is not the insight.
The insight lives in the contrast, the exceptional case, and/or the tail.Together, they round the recommendation out: the outcome to expect, the caveats that come with it, and where the upside or risk sits.
The gap between base case and expected value.
In a constrained system, upside is capped (you can't process, drill, or sell more than capacity allows even when conditions are good) while downside isn't, and there's limited ability to mitigate or catch up if things run behind. That asymmetry, not underperformance, is what pulls EV below the base case.
The same logic runs the other way on cost: overruns are typically more likely, and larger, than underruns, so expected spend often sits above budgeted capex for the same reason.
State this before someone anchors on the base case and holds you to it.
Expect the [variable name] outcome to land nearer [expected value's metric value] than the [base case's metric value]: a [delta value] gap that reflects [capacity / schedule / supply chain / reservoir] constraints capping the upside.
Example: "Expect the NPV outcome to land nearer $118M than the $142M base case: a $24M gap that reflects the facility capacity constraints capping the upside."
None of the above are mutually exclusive. A single recommendation often draws on more than one at once. Here's the base case adjusted for constraints, the named upside if things go well, and the named downside with its mitigation already lined up, all in the same breath:
Example: "We recommend the base development. Expect it to land nearer $118M than the $142M base case, given capacity constraints, with upside to $40M if we land a P10 production outcome, and downside exposure if oil falls below $60/bbl, which we could manage by farming down our share."
Other things...
Not every recommendation fits that shape cleanly. Three other things often worth having ready, alongside the paragraphs above:
When does it make sense to choose this?
Useful when the decision isn't now-or-never. “We don't need to sanction the water expansion until the gas production forecast falls below X” reframes a single recommendation into the circumstance that would trigger it. That's closer to how staged decisions actually get made, and a direct answer to “why not just decide now?”
What fraction of the downside does this actually fix?
The same kind of question as the tail mitigation above, just answered as a coverage percentage instead of a dollar figure, a reserves impact or a structural fix: useful when the real case for an option is insurance, not upside. “The water expansion removes gas-constraint risk in 60% of our scenarios” argues necessity directly, without needing a single best-guess number to carry the whole argument.
When does the case count itself matter?
In risk-averse or heavily governed rooms, stating what was actually tested becomes part of the credibility: evidence of diligence rather than insight. Everywhere else, skip it; the number of scenarios you ran is your process, not their answer.
Choose the elements that fit the audience and the question.
Seven elements, used individually or combined. Which ones work depends on who's in the room and what you're showing.
Single anchor number
One figure, full-size, nothing else competing with it: EV, or the probability of hitting the goal, stripped of its chart. The floor of the set, for a room that doesn't need the “why,” just the “what,” and trusts you to have already checked the why yourself.
Direct comparison chart
The starting point. What are we voting on? Cashflow under Strategy A vs B vs C, shown cleanly. Not 16 permutations, only the options that actually matter. Often a line chart or simple bar chart. Everything else below is derived from this.
Multi-metric comparison table
Multiple KPIs across options in a grid. Option A/B/C vs IRR, payback, capex, production target. Use when stakeholders need to interrogate trade-offs across several metrics simultaneously, not just follow a single trend line. The direct comparison chart shows a shape; the table lets them pull on individual numbers.
Decision tree
Paths taken only, everything else collapsed. Shows structure of a staged or branching decision. Great to fill in the “unless” and the “because” caveats.
Waterfall
A to B, per change. How you got from best guess to expected value, why the forecast changed, what each component contributed.
Delta vs base, plus any critical milestones
A header and a couple of labeled numbers, not paragraphs: annotations to complement, not a standalone view, pulled from the sensitivity range you've already worked through.
Three kinds earn a spot: business-critical values worth tracking regardless (breakeven, budget cap), values that would actually flip the recommendation (your “unless,” made visual), and, if you've presented this before, the delta since your last update.
Probability of hitting a goal
“This improves our likelihood of hitting the production target by 6%.” Or the probability of staying within the $310M capital budget cap.
Either way, computed directly from the model, not estimated after the fact.
Match to the room
The seven elements above aren't a package. Different rooms need different subsets, and using all seven on everyone is how you lose the room a second time. Here's a rough map from who's in front of you to what to lead with, and, in a couple of cases, what to leave out.
Technical reviewers / peers
Full decision tree, distributions, multi-metric table. This room can take the full set; they'll ask for whatever's missing.
Time-pressured executives
Direct comparison chart, plus one milestone. Save the rest for the follow-up.
Senior / board rooms
A single anchor number, the probability from the goal chart, or the EV figure already sitting on your comparison chart, stripped of everything around it, that they can apply their own view to.
Cross-functional / mixed room
Direct comparison chart as the spine, with one or two supporting elements layered in live. You're reading the room in real time here more than anywhere else.
The range didn't fail last time.
What matters now is what you walk into the room with: a recommendation, the mitigation already priced, and a read on who's in the room and what they need to see.
You have all of that now. That's enough to try again.
One more thing, if it applies:
Is this decision a single commitment, or a staged one?
Often you only commit to part of a project now, and know you will learn more later. What you commit to today, and how you communicate that option value, is a different problem.