Breaking down silos: why savvy data management is essential for effective governance

By on 12/10/2021 | Updated on 12/10/2021
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Governments often face events that threaten their country’s financial stability, create unemployment and increase the need to provide social support services. COVID-19 is one such example – and a big one.

In the case of the pandemic and other scenarios, government leaders have had to make critical decisions and respond expeditiously in order to ensure the wellbeing of citizens.

Faced with such events, governments need to have as much data at their disposal as possible to help inform decisions and carry out relevant actions. For example, they need to know which segments of the population require the most help, anticipate the direction certain events will take, and what they can do to mitigate their impacts.

The answer to these and other questions is found in the data. For this reason, it is essential that governments have access to the correct data and the ability to turn it into useful information, as well as having effective channels to communicate it so that citizens and companies have the information they need to react.

However, this is easier said than done – both in emergencies and in normal times – due to data being scattered across different government bodies and kept in silos; because it is often collected manually; and because the necessary tools to assess and manage the data are not always available.

The biggest challenge for governments is freeing the data contained in departmental databases. Lack of data sharing between departments and agencies prevents government from taking advantage of data to improve processes, workflows, and to provide services quickly and effectively. For example, disjoined data presents only a partial view of citizens who are receiving health and social support.

When data is kept in silos, opportunities are missed to unearth bad practices such as fraud, waste and abuse, as well as to learn lessons from service delivery shortcomings and make improvements. Hence the importance of governments having an effective data management strategy.

Data management is a critical resource that unlocks the potential of an organisation, and carrying it out efficiently requires having a data strategy, and reliable methods to access, integrate, clean, govern, store and prepare data.

In an increasingly digitised world, governments receive data from a myriad of sources including transactional systems, sensors, social media, and records. It is important that they know that the value of the data does not lie in the source from which it comes, but in what is done with it. This is where data management comes in.

In essence, data management capabilities include:

Data quality and integration

The ability to consolidate data from various sources (internal and external); trace its lineage through the associated sources and processes; reduce errors and inconsistencies; and promote standardisation so that data can be exploited fully.

Data preparation

Preparing data for analytical processes and its use within reports without the need for programming or IT assistance. This enables civil servants to spend less time preparing data and more time focusing on analysing it and, in turn, adding value.

Data governance

Processes that guarantee that the data complies with the established policies and standards of the organisation.

Personal data protection

Complying with the regulations on the protection of personal data and privacy, allowing appropriate access, identification, governance, protection and auditability. 

IT and data management Simplifing administration, access points and data security in order to offer a consolidated and complete view in a user-friendly format.

Together, data management and analytics lay the foundation for industry modernisation and provide a broad and clear picture of what is happening across all levels of government. They are tools that offer enormous potential to help make resource management more transparent and to combat corruption and fraud problems, among many others.

Data-driven governance

In times of instability and uncertainty, when normal capital flows decline and the need for new programmes and services increase, governments need to be able to adapt and respond as quickly as possible in three key areas: impact on revenue; economic development; and financial transparency.

Here, data management and analytics play an even more strategic role in government initiatives to address these challenges.

The main challenge is a reduction in income – during the pandemic, for example, when normal economic activity came to a halt due to lockdowns and travel restrictions.

Supported by data management and analytics, governments can make accurate forecasts to make better decisions during crises. Among other things, they must incorporate data from both traditional and new sources to predict revenue. Being able to quickly onboard and test non-traditional data sources is a critical capability, and one that must be easily replicable if governments are to understand how revenue is affected by various factors.

By doing this, government organisations can effectively manage their revenue streams by assessing the environment that generates them, assertively forecast revenue, and understand the impact of policy decisions.

Economic development

After a period of economic uncertainty such as the one we are currently experiencing, policies are required to support the economy, and to maintain a stable as possible network of financial relationships between employees and companies, and suppliers and consumers, to guarantee recovery. The ultimate purpose is to reduce the damage caused by a temporary crisis from job losses and company bankruptcy filings.

Therefore, government entities have to be able to analyse as much data as possible to identify the most affected citizens and companies. Understanding the impact of policies enacted during previous periods of economic instability will serve as a foundation for evaluating new policies. And recovery will depend on data-driven policies and their effective enforcement.

Financial transparency

Governments strive to help citizens, businesses, and economies by providing monetary assistance through stimulus, fringe benefits, and flexible fiscal policies. It is expected that the funds – being public money – will be used in the best way, and it is possible to understand what was paid, who was paid for what services, and who benefitted.

Offering financial transparency comes down to two factors: the speed with which governments distribute funds and the number of recipients; and the systems used to track them.

With analytics and data management, governments can take advantage of platforms that allow timely access to systems that accept and release funds. This facilitates scrutiny of spending and the ability to identify and resolve anomalies. A financial transparency platform generates the expense reports and dashboards necessary to monitor spending, and allow for public examination.

In today’s environment, it is critical that organisations utilise an advanced analytics and data infrastructure that enables them to understand the challenges they face and react to them appropriately. The pandemic is a serious threat but it is also an opportunity to solve longtime data problems.

Improving the way data is shared between government agencies can increase their ability to generate data-driven insights and allow them to make more informed and timely decisions, so that the resulting actions are as effective as possible. Not only that, but it gives them greater capacity to respond to the challenges they face today and in the future.

Impact areas

Among the areas in which data management and analytics have an effective application, the following stand out:

Public sector finance

Data management and analytics guarantee the proper administration of tax collection and payment management, and can be used to understand the economic impact of different policy alternatives. They help in the detection of fraud, tax evasion or avoidance and other abuses, to provide a real view of government agency operations and the behaviour of taxpayers.

Public safety and justice

They increase the precision and speed of investigations and allow better decisions to be made to protect citizens. In law enforcement, they provide a structured environment for gathering, managing, and analysing intelligence.

Social services

They ensure better results by enabling government to offer benefits to the people who need them in a timely manner; improve resource management by detecting and mitigating improper payments; and improve operational efficiency and service delivery.


They enable understanding of the impact of health policies. Good data management and analysis techniques help responsible agencies make more informed and innovative decisions to improve results, guarantee the accessibility and quality of services, and control costs.


It is possible to understand students’ potential and trajectory and to identify those at risk of dropping out. Proper data management and analysis also allows data to be translated into insights so that educators better understand the needs, challenges, and opportunities of their students, and ensure transparency around funding for schools. 

To learn more about governments can incorporate AI-driven decisioning into existing business process to take advantage of digital transformation benefits, please read this Transformational Decisioning E-book.


Miriam Ramirez, pre-sales manager, SAS Mexico

Miriam specialises in fraud and risk prevention issues and solutions. She has 10 years’ experience in consulting and the development of analytical tools and models.

Miriam is a graduate of applied mathematics from the Autonomous Technological Institute of Mexico and has an Erasmus Mundus masters in data mining and knowledge management from the Lumière Lyon II University.

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