From a Number in a Table to a Mark on the Future: How Science Transforms Data into Wisdom
The world today no longer lacks data; quite the contrary, we live in a ceaseless digital deluge. Every hospital generates numbers, every school produces reports, every economic project leaves behind vast records, and every smartphone adds a new layer to this immense sea of information. But the question is not: Do we have enough data? Rather: Do we have enough wisdom to use it?
Transforming data into practical wisdom is the heart of scientific work in our era. Science is not limited to laboratory discoveries alone; it extends to the art of reading reality through numbers, then proposing solutions that fit this reality. Here, the role of Scientific Advisory Councils emerges as think tanks capable of holding both ends of the equation: the massive amount of data on one hand, and the realistic challenges of society on the other.
The journey of the “number” toward becoming a “mark on the future” passes through several overlapping stations, including:
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Choosing what we truly want to know: Before collecting numbers, clear questions must be asked: What are we looking for? What problem are we trying to understand? What decision do we want to improve?
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Cleaning and understanding data: Raw numbers can be misleading if not refined and interpreted accurately. This is where the role of experts in statistics and data analysis comes in.
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Linking results to the human context: A number telling you that “the school dropout rate is 10%” is meaningless if we don’t know where, why, and with whom?
Imagine, for instance, that education sector data reveals the dropout rate is higher in a specific region and within a specific age group. A decision-maker unsupported by science might settle for blaming students, families, or schools. However, the Scientific Advisory Council will look deeper: Is the problem economic? Is it related to unsuitable curricula? Is there a shortage of teachers or staff? Do social or cultural environments have an influence? Then, it proposes multi-level solutions, some short-term and others long-term.
Using science to read data means not only “understanding what is happening,” but also “preventing what might happen if we ignore early signals.” For example, hospital data might indicate a slow rise in a specific disease in a specific area. Ignoring this signal could lead to a health crisis later, whereas early intervention, based on a scientific reading, could prevent the problem before it grows.
On the other hand, reinforcing a culture of data-driven decisions fortifies societies against random and emotional tendencies. When decision-makers get used to a simple question before any major step—”Where is the data supporting this direction?”—they gradually open the door to a new mindset in management, making science a permanent partner, not a temporary guest.
Over time, the effects of this mindset appear in several aspects:
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Fewer failed projects, because feasibility studies become more realistic.
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Fairer development plans, because they are based on real knowledge of the needs of different groups and regions.
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Higher capability to predict risks, thereby reducing losses when crises occur.
In this sense, the number written today in a small table may transform tomorrow into a real mark on people’s lives, if it passes through an organized scientific mind and an institutional framework that grants science a central role in decision-making. As for data that finds no path to a responsible mind and a heart that cares for the future, it remains merely silent lines in forgotten files.
Here lies the crucial role of Scientific Advisory Councils: to ensure these numbers are not lost, and that science is not imprisoned in reports, but transforms into a vision, then into policy, then into a reality people live. The future is not built by big words alone, but is crafted every day, quietly, through small and large decisions, when we choose to listen to science and respect what our data tells us about ourselves and the path we are walking.
