The boardroom needs a new language for uncertainty

By James Pierog, Founder and CEO of Glimpse

The modern boardroom is fluent in strategy but often poor at uncertainty. It has language for ambition: growth plans, transformation programmes, market leadership, operational excellence. It has language for control: KPIs, risk registers, budgets, governance frameworks.

What it often lacks is a disciplined language for probability. I believe this is a serious problem because executives operate in an environment where uncertainty is structural. Supply chains shift, interest rates surprise and political cycles move markets. In addition, artificial intelligence changes cost curves and consumer behaviour is mutating faster than annual planning cycles can capture.

A board can no longer assume that the future will resemble the spreadsheet with a few adjustments. And yet, many corporate forecasting processes still behave as if precision were possible. 

The same problem is visible across financial markets. Investors, analysts and executives are surrounded by forecasts, but many of those forecasts are static, unscored and quickly overtaken by events. What is missing is better mechanisms for turning uncertainty into probabilities that can be tested.

The annual plan becomes a ritual of false confidence. Revenue targets are debated until they feel acceptable, market assumptions are negotiated, risk scenarios are presented, but rarely weighted. The language of probability is replaced by the language of consensus.

Consensus can be useful for alignment but it is incredibly dangerous when mistaken for truth.

The central failure is that organisations make forecasts constantly but measure forecasting quality rarely. Assumptions about demand, capital availability, customer behaviour and market conditions shape investment, strategy and resource allocation, but they are often forgotten once the next planning cycle begins.

But once the quarter ends, the organisation tends to move on. The forecast is revised and the miss is explained away. That decision-making process remains largely untouched.

This is how companies become overconfident without noticing. The antidote is a recalibation in how leaders act. 

A calibrated leader does not avoid conviction but understand its limits. They can say: I believe this is the right move, and I assign it a 60 per cent probability of success. That may sound less heroic than the traditional CEO declaration, however, the reality is that, it is far more useful.

Probability turns vague disagreement into productive conversation. If one director believes a strategy has an 80 per cent chance of success and another believes it has a 35 per cent chance, the board has discovered something important. 

The next question becomes: what do you know that I do not? This is the power behind prediction markets and other market-based forecasting systems. That is why their most interesting use case may not be internal corporate forecasting, but public financial forecasting: markets that allow participants to express views on assets, prices and outcomes in a way that produces a visible signal for everyone else. They aggregate dispersed knowledge by giving people a reason to reveal what they believe. A price becomes a probability. A probability becomes a signal. The signal can be wrong, but it is at least explicit enough to be tested.

Business needs more of that discipline, but that does not mean every company needs to run an internal prediction market. For most leaders, the more important lesson is conceptual: make assumptions explicit, think in probabilities, update when new information appears and learn from markets that are designed to reward accuracy rather than confidence.

The same discipline is increasingly relevant to financial markets. When investors debate inflation, interest rates, energy prices, Bitcoin or broader market direction, the useful question is not simply who has the most confident view but what probability the market assigns to different outcomes, how that probability changes over time, and what new information causes it to move.

These are probabilistic questions disguised as strategic ones. The best executives already think this way instinctively. They understand that uncertainty is not a weakness to be hidden. It is a variable to be priced.

But organisations often punish this behaviour. The leader who expresses uncertainty can appear less decisive than the leader who tells a cleaner story. The team that assigns probabilities may look less confident than the team that presents a single forecast. The board that asks for calibration may appear slower than the board that approves the plan.

Over time, this creates a bias towards narrative over accuracy. And that bias is becoming more expensive. In stable environments, companies can survive poor forecasting because the range of outcomes is narrower. In volatile environments, mispriced uncertainty compounds quickly.

A hiring forecast becomes a margin problem, a demand forecast becomes an inventory problem, a rate forecast becomes a refinancing problem and a technology forecast becomes a strategic relevance problem.

At Glimpse, we approach this through public financial forecasting markets, starting with Bitcoin. Bitcoin is one of the clearest examples of an asset where opinion is abundant, volatility is constant and accountable forecasting is scarce. Our focus is not internal corporate forecasting, but the same principle applies to leadership: forecasts become more useful when they are explicit, measurable and exposed to reality.

The boardroom of the future will need more than confidence. It will need a better relationship with uncertainty. And I feel that starts with changing the question. Not what do we think will happen? But what probability do we assign to each outcome, and how will we know whether we are getting better at seeing the future?

The leaders and investors who learn to answer that question honestly will make better decisions. Not because they can eliminate uncertainty, but because they will stop pretending it is not there.