Batapa-Sigue: Is the PH Government Data Driven?


Roughly 2,500,000,000,000,000,000 bytes of data. That is the amount of data that the world produces every day – in trillions. More than 90 percent of today’s global data was only generated in the last three or four years.

Today the world uses this vast amount of data to understand the past, solve current problems, and reshape the future. The application of data, especially in government, will have unlimited possibilities and potential to provide responsive, efficient, effective, competent and trustworthy public services. The big question we have to ask is whether our government is data driven when it comes to decision making, or is it just guessing most of the time?

In their study “A Data-driven Public Sector: Enableling the Strategic Use of Data for Productive, Inclusive and Trustworthy Governance” from 2019, Charlotte van Ooijen, Barbara Ubaldi and Benjamin Welby presented the idea of ​​the government’s data value cycle, which includes the phases that data must traverse to reach its maximum public value. The cycle helps track the path from handling data, including raw, isolated, and unstructured data sets, to identifying and understanding the relationships between that data, resulting in information and knowledge for governments to use as a basis for action and decision-making to serve, be it strategically, tactically or operationally.

This data-driven public sector model (DDPS) represents four phases of data in government, namely the collection and generation of data; the storage, backup and processing of data; sharing, curating and publishing data; and the use and reuse of data.

The government collects huge amounts of data and records on a daily basis from frontline public workers who have a direct mandate for data collection, which comes in many forms and from multiple sources. From various government transactions, health information, business permits and license transactions to feedback mechanisms for citizens. If our governments are smart, then daily data from various sensors with Internet of Things (IoT) devices can easily generate data from the street in real time.

Data can also be actively queried as part of the design of a public service, such as forms for collecting information from the public or in customer relationship management software for subsequent follow-up inquiries. Covid-19-related surveys and contact tracing applications generate a lot of data on which decision-makers can develop their strategies.

As a result of government activities such as procurement and supply contracts, data is generated that could serve as a basis for creating more transparent and accountable systems. There is data held by the private sector that works with the government to provide goods and services. All of this data can be used as a basis for effective policy making and good governance.

With data analytics, governments can use data for descriptive analysis to understand the current situation. diagnostic analysis to know what went wrong and how things happened; Predictive analytics, to create models for future use as solutions, and prescriptive analytics, to develop and mandate solutions in the form of government policies, guidelines, and programs.

Once data has been identified, collected and generated, it must be stored, secured and processed. This phase is very important to the role of data and public trust. Particularly when processing requests for information and agreements on the transfer of data that are not openly accessible, legal bases and legal bases must be observed. Countries that have clear guidelines for data sharing and interoperability between government institutions have addressed this problem head on. The Philippines still needs to strengthen its data exchange guidelines so that all institutions are interoperable.

The final phase of the cycle, the use and reuse of data, is seen as a clear opportunity to create visible public value. For data to be an asset, it must generate public value. However, the use and reuse of data can only be of public value if the process is supported by a broader data governance ecosystem.

The DDPS shows that by improving the management and use of data at every stage, policymakers and officials can increase their effectiveness by improving their data capacities and ultimately creating greater public value.

The potential public value includes the gathering of knowledge about existing political activity; Understanding the issues that stakeholders face; Anticipating new trends and needs; Providing quality services; Design and adaptation of innovative approaches; Monitoring ongoing implementation activities; and manage the resources used to address a particular challenge.


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