HOW DO we build a comprehensive data analytics and visualization portal for national and local development in the Philippines, so that we limit the number of variables in every situation? That question constantly nags me, and now even more with the extent of damage that "Odette" has caused in many parts of the Visayas, and some parts of Luzon and Mindanao. How do we make leverage of data, especially demographics and social statistics for predictive analytics and prescriptive analytics especially in the aftermath of a big storm such as "Odette."
My research this year exposed me to how nations in the twenty-first century must constantly keep up with the fast pace with innovation and address the rapidly evolving demands of society in the Digital Age. Citizens in the Fourth Industrial Revolution have required more responsive, more relevant, and faster services from their governments.
While the general public mandates remain almost the same across the globe, governments need to re-think and re-design the way they do things. Slow, inaccurate, and wasteful government programs are no longer simply acceptable. Hence, data-driven approaches in creating and designing government programs and policies need to be in place for meeting the expectations of citizens and rethinking the way governments and their constituents engage with one another.
Data has a very important role to play in identifying and setting programs and policies that will improve socio-economic conditions, enhance public services, effectively spend public resources and elevate the quality and standard of public service.
It is said government capacity should not remain static; it needs to adapt to societal and technological changes. Governments have to anticipate, adapt to and mitigate these change processes as part of their innovation.
Towards this end, the Philippine needs to create and strengthen clear and effective data-driven public sector frameworks that can help our cities, municipalities, and provinces, as well as the country identify, design, evaluate and assess the elements or parameters that are necessary for collecting, storing, analyzing, using, re-using or sharing data to make informed decisions.
Data-driven decision making is emerging around the world as a formal discipline in all walks of life, across different sectors. But this study agrees with many of its precursors and proposes that use of data will result in a wider impact when practiced by the public sector.
I am undertaking a study, among several initiatives for 2022 in the area of innovation, to establish a case for a unified data governance framework for the Philippines in the advent of big data. With the voluminous amount of data collected and stored every day through public channels, from the local up to the national level, supports the urgency of data-driven governance. But first, the government must craft and institutionalize a clear set of strategies for data analytics to gain insights that can support the development of data-driven decisions leading to effective programs and policies.
This set of strategies begins with developing a data governance framework to ensure quality indicators in the collection, storage, analysis, use and reuse of data. It shall also cover the process and ethics behind data mining and data visualization.
To create a data governance framework, there is a need to first understand the cycle of data in the public sector of each country. A data-driven public sector: Enabling the strategic use of data for productive, inclusive and trustworthy governance” presented the idea of the government data value cycle. This cycle is primarily composed of major phases namely, 1) the collection and generation of data; 2) the storing, securing and processing of data; 3) the sharing, curating and publishing of data; and 4) the use and reuse of data (van Ooijen, Ubaldi and Welby, 2019).
The application of data in government has almost limitless potential for improving governance and performance in the public sector and consequently in generating public value.
The research shall focus on understanding the public sector data cycle or various countries, the nature, patterns, structures, and consequences of handling data in the public sector in various stages, which are collecting and generating data; storing, securing and processing data; sharing, curating and publishing data; and use and reuse data.
But even before that, there is a need to revisit existing laws and policies on data privacy and protection and also determine whether there are laws that govern data-sharing among government agencies to identify the extent and impact of interoperability.
After establishing the data cycle, we must identify ways to establish and institutionalize standards in effectively using data in policymaking down to the local government level through a data governance framework. A data governance framework creates a single set of rules and processes for collecting, storing, and using data. This will help the country create a dashboard for disaster management in order to effectively predict, prescribe and deploy interventions holistically and in real-time and not on a piece-meal basis as we experience today. I hope it will not take many more “Odettes” before we can realize this vision.