Unleashing the potential of a data-driven economy will require policies that enable data to flow and be exchanged freely across geopolitical boundaries, while minimizing risks and harms to enterprises and individuals globally. This is a difficult balance that requires local, national, and regional governments to agree on which data can be shared, how they can be used, who should have access, and which nations would have jurisdictions in resolving disputes.
Regulations that are too lax can expose both corporations and individuals to higher risks; regulations that restrict data collections, flow and use can hamper new innovations, services, business models, and scientific findings – ultimately harming everyone.
The policy considerations required to develop the data ecosystem include the following:
Develop adequate knowledge of the data-driven economy for all stakeholders in the data ecosystem and support research on how big data can drive socio-economic welfare.
– Data stakeholders, including users, service providers, regulators, and researchers, must be made aware of the socio-economic benefits of data flow.
– Government should examine the data sources they already have, either in digital or physical form, and consider how they can be used to improve specific government initiatives, e.g., disaster preparedness, epidemic control, and energy efficiency.
– Incentives should be provided to encourage the development of innovative uses of data to deliver new economic value and societal benefits.
Build a flexible policy framework that will enable the flow of data while ensuring adequate user protection, including security, privacy, data governance, and data sovereignty issues.
– Security: this is critical to big data, given its potential to impact large populations. As a result, data-breach regulations must be at the forefront of any digital agendas, ensuring a trustworthy foundation for the data-driven economy.
– Privacy/data governance: the data economy is built on new insights derived by commingling a variety of data sets, including personal data. Regulators concerned about inappropriate use of personal data may favor the more traditional approach of imposing restrictions at the time data is collected. However, this will impede the flow of data, slow innovation and deprive individuals and economies of many potential benefits. In reality, it is the inappropriate use of data that is the main source of potential harm – and what is considered appropriate use of data is contextual and personal. Policy makers need to consider the value that data can deliver throughout its lifecycle, the data governance that is needed to ensure trustworthy data practices by all stakeholders in the data ecosystem, and how technology can enable all of this.
– Data sovereignty: these issues arise when competing claims on data jurisdiction are made by different countries. These are complex issues that are not easily solvable, however, in a global digital economy where the Internet has accounted for more than 20% of GDP growth in the world’s major economies over the last five years, it is critical that data be able to move seamlessly across borders.
Develop and grow the skills needed to fuel and support the data-driven economy.
– The use of data will become a key basis of competition and growth for the private sector. For example, McKinsey has estimated that retailers can increase their operating margins by more than 60%; and services enabled by the use of personal location data can result in an estimated $600 billion in additional global consumer spending.
– In the US alone, it is estimated that by 2018, there will be a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts with the know-how for effective decision-making with big data.
– Big data analytics require new techniques and algorithms that are yet to be developed, requiring new research and development. In addition, the promises of big data come from inter-disciplinary collaborations. These types of research must be enabled and encouraged.
Democratize big data: broaden the potential impact and value of big data by adopting and making available supporting cloud services and appropriate tools.
– Many domain-knowledge and/or sector-specific experts may not have access to the resources required or be well versed in the latest computational technologies for big data. Appropriate policies and encouragements of public-private partnerships are needed to make available to the research communities these capabilities and appropriately large data sets for testing. This would enable more effective use of big data, facilitate data re-purposing and cross-discipline collaborations, and create more opportunities for innovation and commercialization based on insights derived from large research data sets. Both the pace of dissemination and the breadth of impact of research results would be improved.
– One example is Microsoft’s collaboration with government agencies around the world to offer cloud services and massively scalable tools in support of universities and government-sponsored research. This has resulted in more than 80 research engagements globally, a number that continues to grow.
This is an exciting time for us and we see that as a confluence of technology, economic, and societal factors has fueled an exponential growth in the volume, variety, velocity, and availability of digital data, creating an emerging and vibrant data-driven economy.