As highlighted by Andre de Barros Faria, a technology specialist and CEO of Vert Analytics, digital transformation has expanded access to information within organizations, but that does not necessarily translate into better decisions. A lack of data literacy has become one of the main obstacles for companies seeking efficiency, growth, and competitive advantage. Throughout this article, you will understand why having more data does not solve problems on its own, how poor interpretation compromises results, and what approaches can make analysis more strategic and useful in the corporate routine.
Why having more data does not mean better decisions
The increase in data volume has created the idea that more information automatically leads to better decisions. However, this logic does not hold up in practice. Without proper interpretation, an excess of data can generate confusion rather than clarity. This happens because quantity does not replace the quality of analysis, making the decision-making process more complex rather than efficient.
Many professionals deal with complex reports and indicators that are poorly aligned with business strategy, which makes decision-making more difficult. According to CEO Andre de Barros Faria, this scenario compromises both agility and consistency in decision-making. In this context, Main, a solution developed by Vert Analytics, uses AI agents to automate up to 80% of tasks, solve complex demands without requiring specialists, and speed up service processes, reducing operational costs and freeing teams to focus on more strategic activities.
In addition, a lack of context further aggravates the issue. Isolated data does not tell a complete story. To be useful, data must be analyzed collectively, considering variables, trends, and impacts. Without this integrated perspective, the risk of error increases significantly. The absence of a broader view makes it harder to identify patterns and limits the ability to anticipate future scenarios.
What prevents efficient data interpretation
According to Andre de Barros Faria, one of the main factors is the lack of an analytical culture within organizations. Having access to data is not enough if teams are not prepared to interpret it. Data analysis requires critical thinking, business knowledge, and the ability to identify patterns.
Another relevant factor is how data is presented. Disorganized information, non-integrated systems, and overly technical reports make understanding more difficult. When interpretation becomes complex, the strategic use of data tends to decrease.
How to turn data into more strategic decisions
The first step is to simplify access to information. Organized, structured, and integrated data facilitates interpretation and enables more consistent analysis. When information is clear, decision-making becomes faster and more reliable. This reduces the time spent searching for data and increases confidence in the choices made.
It is also essential to develop a data-driven culture. This involves training teams, encouraging the use of information in decision-making, and creating processes that prioritize analysis. The more natural the use of data becomes in daily operations, the greater its effectiveness. This behavior strengthens consistency in decisions and improves alignment across departments.
Another important aspect, as emphasized by technology specialist Andre de Barros Faria, is the strategic use of technology. Tools that organize, cross-reference, and present data intelligently help transform information into insights. However, technology should be a means, not an end. The real value lies in interpretation and practical application. When properly applied, it enhances analytical capabilities and increases operational efficiency.
Author: Diego Rodríguez Velázquez
