The Value of Big Data Analytics in the Definition of Public Policies

Data analysis helps all types of entities and public and private organizations to make better evidence-based decisions more quickly and effectively. In today’s world, this area is constantly evolving: more and more data is available and its momentum continues to grow, playing a vital role in business and policy decision-making around the world.

The Big Data Analytics for Policy Making report, drawn up by the Directorate-General for Informatics (DG DIGIT) of the European Commission, addresses Big Data and data analysis initiatives launched by public authorities, paying special attention to the potential or added value that these contribute to the different levels of government or the different areas of action.

This extensive and well-documented dossier puts together just how data analysis is used in the public sector and how many organizations approach the challenge of obtaining value from data. It collects and analyzes more than a hundred cases -103 to be exact- in which public administrations use and apply data analysis in the policy field (from policy planning and design to implementation, evaluation and review), and that show the possibilities that come with the use of diverse sources of data (administrative data, sensor data, social media, etc.) and analytical techniques (predictive, descriptive, visualization, etc.).

The cases analyzed and documented have been grouped into five areas (strategy, people and skills, processes, data and technology); and around five main categories of initiatives: general eGovernment initiatives, studies (university research and feasibility studies), open data portals, applied cases and training. A selection that includes key elements such as the different areas of policy (security, justice, domestic, health…), the level of government (supranational initiatives such as the United Nations and OECD, national, regional and local), types of data sources (business data applications, public web, social media, records -both human and machine generated- and sensors), as well as types of analysis (descriptive, predictive or prescriptive).

Along with the role of big data and its analysis in policy making, the DIGIT Directorate-General of the European Commission defines the concepts that are related to big data, presents its characteristics and challenges, and proposes that the traditional architecture of business intelligence is no longer sufficient when it comes to addressing Big Data.

Of the hundred analyzed examples, the report selects the ten most relevant cases of data analysis in the public sector:

1. UNECE Sandbox (United Nations Economic Commission for Europe).
2. Statistics from the Netherlands on Innovation and Big Data
3. Flanders Education (Department of Education and Training of the Flemish Government)
4. Data Consumption Index (ISTAT-the Italian National Institute of Statistics)
5. Transport Data Analysis from London (Transport for London – TfL)
6. Danish Ministry of Health
7. Flanders Employment Service – Innovative Data Analytics
8. Analysis of Customs, Lithuania
9. Taxes and Customs, Estonia
10. The National Archives of the United Kingdom – Big Data for the Law

The report concludes by compiling the best practices and shared knowledge on the application of data analysis to policy, and it proposes a series of recommendations for governments and public organizations that work with analytical data and big data:

• “A public organization must be involved in the era of big data analytics”: think and dialogue with key figures in the organization regarding the potential for optimizing, redefining and transforming the data analytics initiatives.
• “Treat data as crown jewels”: invest in knowledge that is related to ways of managing information and data.
• “No one can whistle a symphony, it takes an orchestra to play it”: there is a need to combine technical skills with business skills in order to face the challenges of big data.
• “The technology you use, impresses no one: the experience you create with it, is everything”: design scalable and flexible IT architectures prepared to adapt to multidisciplinary agents and a continuous technological evolution.
• “It’s not a destination, it’s a journey”: maturity in this area is considered a journey with multiple challenges and designing a detailed road map is important in order to face them.
• “Interoperability challenges must be addressed”: understand that the management of information and metadata are not only important within my organization.
• “Always keep a strong focus on what truly matters”: consider the analysis of big data as a relevant area in which administrations will obtain a huge benefit by collaborating with other public or private entities.

It also points out that the large number of suppliers of different technologies, both open source and proprietary, is a challenge for public organizations when it comes to building an ICT architecture.