Digital economy

Data-driven innovation for growth and well-being


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Data-driven innovation forms a key pillar in 21st century sources of growth. The confluence of several trends, including the increasing migration of socio-economic activities to the Internet and the decline in the cost of data collection, storage and processing, are leading to the generation and use of huge volumes of data – commonly referred to as “big data”. These large data sets are becoming a core asset in the economy, fostering new industries, processes and products and creating significant competitive advantages. For instance:

  • In business, data exploitation promises to create value in a variety of operations, from the optimisation of value chains in global manufacturing and services more efficient use of labour and tailored customer relationships.

  • The adoption of ‘smart-grid’ technologies is generating large volumes of data on energy and resource consumption patterns that can be exploited to improve energy and resource efficiency.

  • The public sector is also an important data user but also a key source of data. Greater access to and more effective use of public-sector information (PSI), as called for by the OECD Council Recommendation on PSI, can generate benefits across the economy.

Greater access and use of data creates a wide array of policy issues, such as privacy and consumer protection, open data access, skills and employment, and measurement to name a few.

For several years the OECD has been undertaking extensive analysis on the role of data in promoting innovation, growth and well-being within its multi-disciplinary project on New Sources of Growth: Knowledge-Based Capital (KBC). Objectives include:

  • Improving the evidence base on the role of data for promoting growth and well-being, and

  • Providing policy guidance on how to maximize the benefits of the data-driven economy, while mitigating the associated risks.

The project encompasses several building blocks:

  • The new data-driven era of scientific discovery
  • The role of data for enhancing health outcomes
  • Harnessing data for better governance
  • Cloud computing, analytics and other key enablers
  • Skills and other implications for employment
  • Ensuring trust in the data-driven economy
  • Measuring investments in data as knowledge-based capital

Recent work


Enhanced access to data: Reconciling the risks and benefits of data reuse

This OECD project analyses how enhanced access to data can maximize the social and economic value of data, and at the same time address legitimate concerns of individuals and organisations.

The November 2019 report "" identifies best practices to balance different interests in a way that ensures that the benefits of data access and sharing are reaped, while the associated risks are managed and reduced to a socially acceptable level. The report is based on the findings of an expert workshop on “Enhanced access to data - Reconciling risks and benefits of data re-use” held in Copenhagen, Denmark in October 2017.


Recommendation of the OECD Council on Health Data Governance

This December 2016 Recommendation of the OECD Council calls upon countries to develop and implement health data governance frameworks that secure privacy while enabling health data uses that are in the public interest. It is structured according to twelve high-level principles, ranging from engagement of a wide range of stakeholders, to effective consent and choice mechanisms to the collection and use of personal health data, to monitoring and evaluation mechanisms. These principles set the conditions to encourage greater cross-country harmonisation of data governance frameworks so that more countries are able to use health data for research, statistics and health care quality improvement, as well as for international comparisons.

See also:


Participants at this November 2016 forum agreed that advanced artificial intelligence is already here and that there are few limits to what it will be able to do. There was a call to focus on 'applied AI' that is designed to accomplish a specific problem-solving or reasoning task. However, several participants felt that policy-makers could not ignore the possibility of a (hypothetical) "artificial general intelligence" (AGI) whereby machines would become capable of general intelligent action, like a human being.

See also:

  • OECD Conference on AI: Intelligent Machines, Smart Policies (Paris, October 2017)
  • See more OECD work on artificial intelligence


Data-driven Innovation: Big Data for Growth and Well-being

Today, the generation and use of huge volumes of data are redefining our “intelligence” capacity and our social and economic landscapes, spurring new industries, processes and products, and creating significant competitive advantages. In this sense, data-driven innovation (DDI) has become a key pillar of 21st century growth, with the potential to significantly enhance productivity, resource efficiency, economic competitiveness, and social well-being.

Greater access to and use of data create a wide array of impacts and policy challenges, ranging from privacy and consumer protection to open access issues and measurement concerns, across public and private health, legal and science domains. The report Data-driven Innovation: Big Data for Growth and Well-being aims to improve the evidence base on the role of DDI for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.


Dementia Research and Care: Can Big Data Help?

OECD countries are developing strategies to improve the quality of life of those affected by dementia and to support long-term efforts for a disease-modifying therapy or cure.

This report follows a September 2014 workshop that aimed to advance international discussion of the opportunities and challenges, as well as successful strategies, for sharing and linking the massive amounts of population-based health and health care data that are routinely collected (broad data) with detailed clinical and biological data (deep data) to create an international resource for research, planning, policy development, and performance improvement. The workshop sought to provide new insights into the opportunities and challenges in making “broad and deep” data a reality – from funding to data standards, to data sharing, to new analytics, to protecting privacy, and to engaging with stakeholders and the public.