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BREXIT10 (Part 1): Numbers Don’t Always Win

Ten years after Brexit, perhaps the most important lesson is not how much it cost the British economy. It is that modern leaders — whether politicians or corporate executives — still tend to overestimate the role of rationality in decision-making.

From the perspective of ten years, Brexit looks less like a political event and much more like a leadership case study. In the months before the referendum, economists, international organisations and financial markets issued warnings about the expected economic consequences of leaving with near-unprecedented consensus. Calculations were made on GDP, investment, trade and the labour market. On one side of the campaign stood graphs, models and statistics. On the other, far simpler concepts: sovereignty, control, identity and the promise of ‘Take Back Control’. We know the outcome. The numbers didn’t lose because they were wrong. They lost because they didn’t answer the question people were actually asking.

One of the most persistent errors in modern leadership is viewing people primarily as rational decision-makers. This assumption is deeply embedded in economics and business thinking alike. If sufficient data is available, if a strategy is logical, if the financial benefits are clear, then the decision should be equally clear. Brexit, however, showed that reality is far more complex. People rarely choose purely on the basis of economic optimum. Far more often, they seek security, predictability, belonging or dignity — none of which can be modelled in a spreadsheet. This insight reaches far beyond politics. The same dynamic is visible in the corporate world. When a company introduces artificial intelligence, carries out an organisational restructuring, or recalls its employees to the office, leaders typically argue with efficiency metrics. They show the expected cost reductions, productivity figures or market trends. Employees, however, ask themselves entirely different questions. Will I still be needed? Will I lose my autonomy? Can I trust the leadership? What does this change mean for me? Two different conversations are happening simultaneously: one about numbers, the other about identity.

Organisational psychology has long recognised this. People are not afraid of change itself, but of losing what they use to define themselves. For an accountant, an AI system is not simply new software. For a salesperson, working from home is not merely a way of working. For a middle manager, an organisational restructuring is not just a new org chart. Every significant corporate change can also trigger an identity crisis. Yet leaders often continue to communicate as though a few more charts or cost calculations would be enough to persuade people. This is precisely why one of Brexit’s most important lessons is that leadership is not primarily analysis but meaning-making. The most successful leaders are rarely those who possess the most data. They are far more likely to be those who can tell a story in which people recognise their own role. The pro-Brexit campaign simplified reality, but it offered a clear narrative. The Remain side generally produced more accurate economic analyses, but was less able to articulate what the European Union meant to the identity of an average British voter. Between the two, it was not the more detailed analysis but the stronger story that ultimately proved more persuasive. This distinction determines the competitiveness of companies today as well. The most successful organisations are not necessarily those with the best strategy, but those capable of giving meaning to their strategy. Apple sold not computers or phones but creativity and simplicity for decades. Patagonia sells not clothing but environmental responsibility. Nike sells not shoes but the promise of performance and self-transcendence. These companies instinctively understood what the Brexit political campaign also demonstrated: people rarely choose a product or a decision. Far more often, they join a story.

In the age of artificial intelligence, this insight becomes even more important. AI can analyse data, generate forecasts and optimise processes. The technological side of rationality is increasingly automatable. This is precisely why the leadership capabilities that algorithms cannot easily replace are becoming ever more valued: building trust, managing emotions, articulating shared purpose and interpreting the human meaning of change. Paradoxically, the more data we have at our disposal, the more important it becomes to understand that people do not make decisions on the basis of data alone.

Ten years after Brexit, much debate still centres on whether leaving was economically successful or not. That is an important question, but perhaps not the most interesting one. The enduring lesson is rather that, in the modern world, economic rationality alone is increasingly rarely sufficient. Markets, companies and societies are still made up of people who both think and feel, who both weigh and hope. The greatest mistake of leaders is therefore not making poor calculations. It is believing that the numbers are sufficient on their own.

Brexit ultimately did not prove that economics is wrong. It proved, rather, that economics is only one of the languages in which human decisions can be described. The other language is that of identity, emotion and belonging. And when the two collide, history shows again and again the same thing: the strongest arguments are not always the most persuasive. Sometimes, the best stories win.