Why data-driven decisions, rather than intuition-based ones, are essential today for tackling the complexities of Brazilian public administration.
*By Cesar Ripari
Public administration faces an increasing level of complexity. Managers must grapple daily with a complex puzzle: how to deliver quality services in crucial areas such as health, education, and security in a country as diverse and vast as Brazil? The pressure mounts as demands evolve, contexts change, and challenges accumulate, requiring agile, consistent, and fact-based responses. In this scenario, governing has come to mean, above all, the ability to base decisions on solid information to generate effective results, which becomes even more challenging considering that many agencies operate with fragmented legacy systems that hinder essential integrations and limit a complete view of society's needs.
When used strategically, data acts as a reliable compass. It allows us to identify patterns, anticipate risks, and guide actions with greater precision. Evidence-based public policies reduce waste, improve efficiency, and broaden social impact. In our country, where resources are often limited and inequalities are profound, this type of approach is urgently needed.
But digital transformation in the public sector goes far beyond digitizing forms or adopting new technologies. It requires a systemic vision with the integration of isolated and fragmented databases, infrastructure prepared for massive information flows, standardization of records, and distributed analytical capacity among agencies. Ecosystems that combine Artificial Intelligence (AI), the Internet of Things (IoT), and advanced connectivity can transform raw data—structured or unstructured, and originating from sensors, cameras, administrative records, voice, or images—into qualified information capable of guiding decisions in near real-time.
In security, the integration of criminal records, video surveillance, and emergency calls allows for the identification of risk patterns and more strategic operational planning. In healthcare, cross-referencing case histories, epidemiological indicators, and hospital occupancy makes it possible to anticipate outbreaks, adjust protocols, and distribute resources more efficiently. And in education, analyses that combine attendance, learning, and socioeconomic context help detect risks of school dropout and direct more precise and preventative pedagogical efforts.
Other sectors also directly benefit from this intelligent use of data. In urban mobility, for example, the continuous analysis of travel patterns, which can be obtained from electronic ticketing, traffic sensors, and geolocation, allows for the identification of bottlenecks, the redesign of public transport routes, adjusting frequencies and schedules, and prioritizing infrastructure investments. In social assistance, interoperability between municipal and federal registries, combined with health and education information, helps to identify vulnerable families with greater precision, ensuring that benefits reach those who truly need them and preventing duplication and fraud.
But none of these advances can be sustained without a solid foundation of data quality and governance, which ensures that the information used is reliable, up-to-date, and consistent. Without standardization, proper curation, well-structured metadata, and clear validation processes, simple errors, such as duplicates, can compromise the entire analysis and generate a chain reaction of failures. Furthermore, data governance acts as a mechanism that defines who is responsible for the data, the rules of use, and the quality criteria, ensuring the integrity of the information from beginning to end.
In addition, strict access controls and user authentication ensure that only authorized profiles handle sensitive data, while obfuscation and de-identification techniques protect Personally Identifiable Information. Thus, security and privacy become cornerstones of the ethical use of data, in full compliance with the LGPD (Brazilian General Data Protection Law).
Analytics platforms, data integration, and data quality make this possible by organizing dispersed databases, automating insight generation, and establishing a transparent data lineage where it's possible to track where each piece of information came from and how it was handled to generate the necessary insights. A single point of control for integration, API development, and the creation of data products makes it possible to centralize the tools and rules that allow different agencies to share information in a standardized, secure, and up-to-date manner. This reduces rework, avoids conflicting versions of the same data, and facilitates collaboration because everyone gains access to consistent information.
All of this also allows for greater transparency towards society, since when the government makes data available in an open, accessible, and understandable way, the population can monitor investments, verify whether goals are being met, identify points of inefficiency, and contribute with more well-founded suggestions.
Data-driven decision-making in public administration is not just a technological modernization, but a profound change in the way we govern and in the relationship between the state and society. Using data strategically, ethically, and in an integrated way is the best path to building a more inclusive, transparent country, better prepared for current and future challenges.
Cesar Ripari is the leader of the Data Intelligence and Governance Committee of the Brazilian Association of Software Companies (ABES) and Senior Director of Pre-Sales for Qlik in Latin America.
Notice: The opinion presented in this article is the responsibility of its author and not of ABES - Brazilian Association of Software Companies
Article originally published on the IT Forum website: https://itforum.com.br/colunas/dados-que-transformam-a-gestao-publica/
