Reading Data, Reading the Future

Today, various economic news arrives almost simultaneously. Non-subsidised fuel prices have undergone adjustments once again. The Rupiah exchange rate remains under pressure. The capital market also shows a decline, reflecting the caution of businesses and investors.

For some members of the public, these news items might only be a series of numbers passing across a mobile screen. However, for policymakers, both in government and the business world, these figures are signals that must be read carefully.

Every major policy should ideally be born from a long process. Before a decision is made, data is collected, trends are analysed, risks are calculated, and various possibilities are simulated.

In the context of energy, for example, the government must pay attention to global oil price movements, the nation’s fiscal condition, exchange rate stability, public purchasing power, and the impact on inflation. Good policy must be able to read reality more accurately and may not necessarily be a popular one.

In the world of artificial intelligence, there are two classic errors that often occur when a model is built using inaccurate data: overfitting and underfitting. Overfitting occurs when a model is too focused on past patterns, failing to adapt to new conditions.

Conversely, underfitting occurs when a model is too simple, failing to capture important patterns that actually exist within the data. Both can result in erroneous predictions because they stem from an incorrect understanding of the data.

Data scientists strive to avoid both errors by continuously testing models from various perspectives. Based on diverse data sources, they endeavour to ensure that the models built are capable of facing new situations that have never appeared before. The goal is to produce models robust enough to withstand various changes.

The same principle applies to public policymaking. Policies that rely too heavily on old assumptions risk failing to understand ongoing changes.

On the other hand, policies that merely react to momentary volatility without looking at long-term trends also have the potential to produce erroneous decisions. Therefore, reading data is not enough to simply look at the numbers appearing today. What is more important is understanding the patterns, context, and the direction of ongoing change.

The same lesson is highly relevant for universities today. Amidst the economic pressures felt by the public, family decisions regarding choosing a university are becoming increasingly selective.

Education costs, career prospects, service quality, and financing flexibility are becoming increasingly important considerations. Universities that fail to read changes in societal behaviour may lose prospective students because their policies are no longer aligned with the reality faced by students and their families.

This is where the management of modern universities can no longer rely solely on intuition. Data regarding the regional origin of prospective students, interest in specific study programmes, promotional effectiveness, the affordability of education costs, and industrial needs must be analysed systematically. The better an institution reads data, the better its ability to respond to the changes occurring around it.

The world is always moving dynamically and does not always proceed according to the assumptions or predictions we made yesterday. Data changes, context changes, and decisions must also adjust. Governments, businesses, and universities all face the same challenge: how to read reality honestly, understand data carefully, and make decisions wisely.

Allah SWT says: “Indeed, Allah will not change the condition of a people until they change what is in themselves.” (QS. Ar-Ra’d: 11).

Change is never born from mere hope, but from the ability to understand the reality being faced. In a world increasingly filled with data, the ability to read reality becomes as important as the ability to change it. Because a good decision is not one based on assumptions, but one grounded in facts. Data is no longer just numbers; it has become a means to carry out responsibilities more wisely.