Why averaging fails
The instinct when eight experts disagree is to find the middle: average the price targets, split the difference on timing, soften the strongest claim until no one objects. This feels balanced. It is, in fact, the most reliable way to destroy the information the panel was convened to produce.
Disagreement among competent experts is rarely random noise around a shared truth. More often it encodes a real conflict between objectives — the CFO protecting runway, the CMO protecting momentum — or a genuine uncertainty about the world. Averaging treats both as error to be smoothed away. The result is a recommendation no expert would have made and no one will defend when it fails.
Dissent is signal, not noise
A well-run council treats a strong minority view as a leading indicator, not an inconvenience. The single dissent on a capital decision is frequently the one perspective pricing a risk the majority has discounted. The operator’s job is not to suppress that voice into the consensus but to surface it, name the condition under which it becomes decisive, and carry it forward on the record.
A protocol for synthesis
Synthesis that preserves information follows a sequence. First, collect positions independently, before exposure to one another, so early confidence does not anchor the group. Second, separate disagreements about facts from disagreements about values: the former can be resolved with evidence; the latter must be decided by the accountable human. Third, write a single recommended path — but attach the dissent, the confidence band, and the conditions that would reverse the call.
The output is not a compromise. It is a clear decision plus an honest map of where it might be wrong.
Implications for the operating review
An operating review built on this protocol looks different from the usual march through green dashboards. It spends its time where the experts diverge, because that is where the information is. It rewards the person who registers a dissent that later proves correct, because that is how calibration improves. And it produces a record that — win or lose — lets the organization learn why a decision was made, not merely what was decided.