The advent of new data technologies is undoubtedly transforming the world. Realising the massive potential embedded within these technologies, 21st century governments began to utilise data algorithms and analytics in order to transform governance structures and improve service delivery. While developed countries have made significant progress in strengthening their respective capacities to use data strategically, developing countries such as Pakistan are finding it difficult to keep pace.
Numerous case studies highlight the significance of developing a coherent and comprehensive model of data governance. In 2015, the United States government, working with Google, initiated a project for crisis situations that uses geographic information systems (GIS) to combine data from across state agencies and map it in a way that is easy to understand. In the midst of a hurricane in Texas, the Google Imagery project shared hourly map updates to keep first responders abreast of the situation; in the aftermath, it was used to predict when school areas could be expected to reopen. This strategic use of data allowed rescuers and government agencies to make far more intelligent, real-time decisions than would have been possible previously. Perhaps if Pakistan had developed a similar crisis management system, millions of people would not have been left homeless and displaced by the on-going flooding in Sindh, Balochistan and South Punjab.
Similarly, the Government of India analysed data using certain data mining techniques to catch tax evaders in 2017. It rolled out a platform completely based on big data analytics known as ‘Project Insight’ to make this happen. The project tracked down approximately 50,000 such entities which were still in existence in spite of their deregistered firms. This helped in accumulating information about the black money potholes still in existence. In comparison, the total taxpayers in Pakistan constitute only 1% of its population and efforts to broaden the tax net are limited to amnesty schemes and banking incentives.
Browsing through the internet, one may find numerous case studies that illustrate the growing significance of data analytics in public policy. What happened in these countries was that they were successful in securing the leadership and vision to ensure strategic direction. At all governmental levels, we could see facilitation for the implementation of this data-driven public-sector framework across the administration a whole and within individual organisations. Governments also revisited rules, laws, guidelines and standards associated with data. They also ensured the existence of a data architecture that reflects standards, interoperability and semantics throughout the generation, collection, storage and processing of data, while developing the necessary data infrastructure to support the publication, sharing and re-use of data.
Moreover, these states have successfully applied data to generate public value through anticipation, planning, delivery, evaluation and monitoring. Through the right anticipation and planning, they continue using data in the design of policies, planning of interventions, anticipation of possible change and the forecasting of need. Similarly, the use of data in measuring impact, auditing decisions and monitoring performance is being integrated into policy making across the globe.
Countries at the forefront of digital transformation have also managed to gain trust through adopting an ethical approach to guide decision making and inform behaviour. They have taken strict measures to protect privacy, promote transparency and design user experiences that help citizens understand and grant or revoke consent for their data to be used. They also approach the security of government services and data in ways that mitigate risks without blocking the transformation of the public sector.
In contrast, transforming data into tangible, measurable and consistent outcomes remains largely elusive in Pakistan. In order to do so, the government must recognise data as a key strategic asset and define its value. It must make active efforts to remove barriers in the use of data and then apply data to transform the design, delivery and monitoring of public policies and services. The government should learn from the data governance models adopted by developed countries and must analyse how various countries have used data to transform and optimise service delivery, especially in the realms of health, education and social welfare.
Numerous case studies highlight the significance of developing a coherent and comprehensive model of data governance. In 2015, the United States government, working with Google, initiated a project for crisis situations that uses geographic information systems (GIS) to combine data from across state agencies and map it in a way that is easy to understand. In the midst of a hurricane in Texas, the Google Imagery project shared hourly map updates to keep first responders abreast of the situation; in the aftermath, it was used to predict when school areas could be expected to reopen. This strategic use of data allowed rescuers and government agencies to make far more intelligent, real-time decisions than would have been possible previously. Perhaps if Pakistan had developed a similar crisis management system, millions of people would not have been left homeless and displaced by the on-going flooding in Sindh, Balochistan and South Punjab.
Similarly, the Government of India analysed data using certain data mining techniques to catch tax evaders in 2017. It rolled out a platform completely based on big data analytics known as ‘Project Insight’ to make this happen. The project tracked down approximately 50,000 such entities which were still in existence in spite of their deregistered firms. This helped in accumulating information about the black money potholes still in existence. In comparison, the total taxpayers in Pakistan constitute only 1% of its population and efforts to broaden the tax net are limited to amnesty schemes and banking incentives.
Browsing through the internet, one may find numerous case studies that illustrate the growing significance of data analytics in public policy. What happened in these countries was that they were successful in securing the leadership and vision to ensure strategic direction. At all governmental levels, we could see facilitation for the implementation of this data-driven public-sector framework across the administration a whole and within individual organisations. Governments also revisited rules, laws, guidelines and standards associated with data. They also ensured the existence of a data architecture that reflects standards, interoperability and semantics throughout the generation, collection, storage and processing of data, while developing the necessary data infrastructure to support the publication, sharing and re-use of data.
Moreover, these states have successfully applied data to generate public value through anticipation, planning, delivery, evaluation and monitoring. Through the right anticipation and planning, they continue using data in the design of policies, planning of interventions, anticipation of possible change and the forecasting of need. Similarly, the use of data in measuring impact, auditing decisions and monitoring performance is being integrated into policy making across the globe.
Countries at the forefront of digital transformation have also managed to gain trust through adopting an ethical approach to guide decision making and inform behaviour. They have taken strict measures to protect privacy, promote transparency and design user experiences that help citizens understand and grant or revoke consent for their data to be used. They also approach the security of government services and data in ways that mitigate risks without blocking the transformation of the public sector.
In contrast, transforming data into tangible, measurable and consistent outcomes remains largely elusive in Pakistan. In order to do so, the government must recognise data as a key strategic asset and define its value. It must make active efforts to remove barriers in the use of data and then apply data to transform the design, delivery and monitoring of public policies and services. The government should learn from the data governance models adopted by developed countries and must analyse how various countries have used data to transform and optimise service delivery, especially in the realms of health, education and social welfare.