Why data alone will not make better decisions

Ed Smith’s tenure as England cricket’s chief selector coincided with one of the most dramatic turnarounds in modern sport. But his reflections are less about cricket and more about how decisions are made when the stakes are high, the data is abundant and the answers are rarely clear.

At the centre of his thinking is a rejection of the idea that complex decisions can be systemised. “There’s something in all of us that wants to turn difficult processes into a system that can’t be. It’s always a judgment,” he says. In an era where leaders are increasingly surrounded by dashboards, models and analytics, Smith’s point is a useful corrective. Data matters, but it does not remove the need for human judgment. The skill lies in combining both.

That balance is not straightforward. Smith describes decision-making as “weighing and reconciling different forms of information”, from data and expert input to intuition and experience. The temptation is to over-index on what feels objective, but doing so risks missing what cannot be measured. The most effective approach, he argues, resembles what chess grandmaster Garry Kasparov discovered after losing to a computer: the strongest outcomes come from a combination of human and machine intelligence.

Underlying this is an acceptance of uncertainty. Smith draws on behavioural economics to highlight the fallibility of human judgement, while also insisting on the value of it. “You’re constantly living with that tension,” he says. Leaders who seek certainty often create false confidence. Those who acknowledge uncertainty are better placed to make resilient decisions over time.

Nowhere is this clearer than in how teams are built. Smith reframes his role not as selecting individuals but as creating a system that wins. “My job is to help England teams to win more through selection rather than picking England players,” he explains. The distinction matters. It shifts focus from individual performance to collective effectiveness and requires difficult trade-offs. The best individuals do not always create the best team.

This idea challenges a common bias towards optimisation at the individual level. Smith instead focuses on how resources fit together. “Can we think in terms of teams rather than just individuals?” he asks. It is a question that becomes more important as organisations grow in complexity, where marginal gains depend less on standout performers and more on how capabilities combine.

Strategy, in this context, is often misunderstood. Smith is sceptical of how loosely the term is used, arguing that real strategy is defined by trade-offs. “If you’re focusing there, you can’t do everything all the time,” he says. The implication is uncomfortable but necessary: prioritisation inevitably creates weakness elsewhere. Avoiding that reality leads to diluted execution.

Innovation adds another layer of difficulty. While widely celebrated, Smith argues it is often misunderstood. “Innovation brings with it an implied insult; you’re picking a fight if you’re innovative,” he says. Challenging conventional wisdom invites resistance, particularly from those invested in the status quo. The reward, however, is differentiation, provided leaders are willing to absorb criticism along the way.

Data plays a critical but specific role in all of this. Contrary to expectation, Smith argues it is less useful for making individual decisions and more valuable for understanding broader patterns. “Where data is very useful is that it shows you how the game is changing,” he explains. In other words, it informs context rather than dictates action.

Perhaps the most striking insight is his emphasis on accountability. In a world of increasing complexity, it is tempting to defer to models or consensus. Smith resists that instinct. “We accept responsibility for the decision,” he says. Ultimately, leadership is not about outsourcing judgment, but owning it.

For business leaders, the parallels are clear. The challenge is not simply to make better decisions, but to navigate uncertainty, balance competing inputs and commit to choices that cannot be fully proven in advance. Over time, success is not defined by any single call, but by the quality and consistency of decisions made along the way.