Article 1: From Intuition to Evidence – Why Data Must Drive Modern Decision Making
By Datuk Ts Dr. Hj Ramli Amir, former President of the Chartered Institute of Logistics and Transport (CILT) Malaysia and Vice-President of CILT International for Southeast Asia
KOTA KINABALU: For a long time, decision-making in organisations followed a familiar script. Experience mattered. Instinct was respected. Seniority often carried the final word. In simpler environments, this approach worked reasonably well. Markets moved slowly, information was scarce, and the consequences of being slightly wrong were often manageable.
That world no longer exists.
Today’s economic and operational environment is faster, more complex, and far less forgiving. Supply chains span borders, customer expectations evolve rapidly, and small disruptions can ripple widely. In this context, relying on intuition alone is no longer a strength—it is a liability.
The Limits of Intuition in a Complex World
Human judgment is valuable, yet it is selective. We remember successes more than failures, recent events more than long-term patterns, and dramatic cases more than routine realities. In complex systems—such as transport networks, logistics operations, or trade ecosystems—these biases quietly shape decisions.
Data does not eliminate judgment. It disciplines judgment.
By introducing measurable evidence into decision-making, organisations are forced to confront realities that intuition alone might overlook. Patterns emerge that no single person can see. Trade-offs become clearer. Assumptions are tested, not trusted.
Data as a Tool for Reducing Uncertainty
Every decision is made under uncertainty. The question is not whether uncertainty exists, but how it is managed.
Data-driven decision-making reduces uncertainty by providing context. Historical data shows what has happened. Real-time data reveals what is happening now.
Predictive analysis offers informed expectations of what may happen next.
This does not guarantee perfect outcomes, but it dramatically improves the odds.
Decisions become less reactive and more anticipatory—an essential shift in environments where delays and misjudgements are costly.
From Opinion to Accountability
One of the quiet yet powerful effects of data-driven decision-making is accountability.
When decisions are evidence-based, they can be explained, evaluated, and improved. Successes can be replicated, and failures can be diagnosed. Without data, organisations drift into opinion-based management, where decisions are difficult to question and even harder to learn from.
Measurement creates clarity. Clarity creates responsibility.
This is particularly important in public-facing systems such as transport and logistics, where performance affects not only organisations but also entire economies.
Speed, Scale, and the Modern Decision Environment
Modern organisations operate at a scale and speed that exceed individual cognitive limits. Thousands of transactions, movements, and interactions occur simultaneously. No manager, however experienced, can “see” the whole system.
Data fills this gap.
Dashboards, analytics, and performance indicators are not about control for its own sake. They enable timely intervention—spotting bottlenecks before they escalate, identifying inefficiencies before they become costs, and responding to changes while options remain.
In competitive environments, speed is not just about moving fast. It is about making good decisions quickly.
Data Is Not the Opposite of Experience
A common misconception is that data supersedes human judgment. In reality, the opposite is true.
Data is most powerful when combined with experience. It sharpens judgment rather than silencing it. Experienced decision-makers ask better questions of the data, interpret results more wisely, and understand the context that numbers alone cannot capture.
The shift, therefore, is not from people to data—but from unchecked intuition to informed judgement.
A Foundational Shift, Not a Technical One
At its core, data-driven decision-making is not a technological upgrade but a cultural and institutional shift.
It requires organisations to value evidence over hierarchy, learning over blame, and transparency over convenience. It asks leaders to be comfortable with being challenged by facts and to view data not as a threat but as an ally.
This shift is foundational. Without it, digital systems become underused tools. With it, data becomes a strategic asset.
Looking Ahead
As economies become increasingly interconnected and systems become more complex, the role of data in decision-making will only grow. Nowhere is this more evident than in sectors such as logistics, transport, and trade—where coordination, timing, and reliability are critical.
Understanding why data matters is the first step. Applying it effectively is the next challenge.
In the next article, we turn to logistics itself—and examine why, in the modern economy, logistics cannot function efficiently without data at its core.
