RESULTADOS ESPERADOS

As of today, there are no broad implementations of Big Data in the public sector, neither it is has been a sector that traditionally has been using data mining technologies in such an intensive way as other sectors have done.

However, there is a growing concern among public sector of the potentials of Big Data for the improvement of public sectors in the current financial environment, as described later in section 3.4.1Characteristics of the European Public Sector.

Some examples of the growing awareness among public sector globally are, the Joint Industry/Government Task Force to drive development of Big Data in Ireland, announced by the Irish Minister for Jobs, Enterprise and Innovation on June 2013 (Government of Ireland.

Department of Jobs, Enterprise and Innovation, 2013), or the announcement made by the Obama administration (The White House, 2012) on the “Big Data Research and Development Initiative” where six Federal departments and agencies announce more than $200 million in new commitments to greatly improve the tools and techniques needed to access, organize, and glean discoveries from huge volumes of digital data.

3.3. Analysis of Industrial Needs

3.3.1 User Needs

The user in this section is understood as the public sector itself, and the analysis has been done through desktop research of existing big data initiatives in the public sector, and the analysis of the potential of these technologies in the sector. The benefits of Big Data in the public sector can be grouped in three major areas, based on a classification of the types of benefits (effectiveness and efficiency) and ground-breaking features (analytic), as shown in Figure 2 below:

Big Data analytics. This area covers applications that can only be performed through automated algorithms for advanced analytics to analyse large datasets for problem solving that can reveal data-driven insights. Such abilities can be used to detect and recognise patterns or to produce forecasts, not possible to perform without such technical means. Some examples of application in this area are:

 Fraud detection (tax, pensions, unemployment benefits, public subsidies to businesses, money laundering). (McKinsey Global Institute, 2011)

 Supervision of regulated activities in the private sector (on-line game, energy and financial markets).

 Sentiment analysis, through the tracking of information from internet content, including social networks. This can help policy makers to the prioritization of new services or to uncover potential areas of civil unrest. (Oracle, 2012)

 Threat detection from external data-sources (social networks, media and Internet content) for application in homeland security, crime prevention, national intelligence and cyber security of critical infrastructures. (Oracle, 2012)

 Threat detection from internal data-sources (government data networks) for application in government cyber security from both, internal and external attacks. (Oracle, 2012)

 Predictive analytics for planning purposes of public services based on forecasts in given scenarios (education, social services for elderly, public transport, etc…) or to perform analysis and forecasts on fundamental areas of economic activity (e.g. financial, food and raw materials markets). (Yiu, 2012)

Improvements in effectiveness. This area covers the application of Big Data to provide greater internal transparency, thus producing an increase of productivity with respect to current processes among public bodies, and externally, to citizens and businesses, providing them access to public data. Citizens and businesses can take better decisions and be more effective, and even create new products and services thanks to the information provided. Some examples of applications in this area are:

 Data availability though public agencies, making data available across agencies and organizational silos, reducing search times and automating access to data. (McKinsey Global Institute, 2011)

 Sharing and transparency of information through public sector organizations avoiding problems from the lack of a single identity database (like in UK), or providing solutions to fulfil the once-only principle, therefore not requesting information from citizens and businesses that is already available within public administration. It also facilitates the pre-filling of information on forms for tax declaration, making life easier for taxpayers and avoiding errors. (Yiu, 2012)

 Open government and Open data. By facilitating the free-flow of information from public organizations to citizens and businesses greater trust between citizens and government is promoted. In addition, more governments are beginning to adopt Open Data by making raw government databases available to the public. This raw data can be re-used in innovative processes combined with other multiple datasets from different sources to provide new and innovative services to citizens. (McKinsey Global Institute, 2011)

Improvements in efficiency. This area covers the applications that provide better services and continuous improvement based on the personalization of services and learning from the performance of such services. Some examples of applications in this area are:

 Personalization of public services to adapt to citizen needs. This is achieved through the segmentation and tailoring of public services to individuals, and by increasing efficiency and citizen satisfaction. For example providing a tailored service to unemployed people in the employment agency providing personalized guidance and even a training plan to adapt their skills to the current needs in the job market. This segmentation can also be used for tax audits to target specific segments of taxpayers more prone to commit fraud or with a professional activity more difficult to control. (McKinsey Global Institute, 2011)

 Improving public services through internal analytics, based on the analysis of performance indicators. Exploiting information already available from current processes can help to improve performance and compare it across different geographical units, or even provide information on vendors and service providers, allowing better procurement decisions, and therefore, saving money. (Yiu, 2012)

In relation to the use of information from internet content, including social networks, it should be noted that the data that users provide voluntarily, or as a requirement for users to create their accounts, is not always reliable, and quite often extracted data may be clearly biased from reality. However through the connections a user of a social network has, it is possible to determine the actual user profile.

Specific user’s needs

From the surveys performed during the elaboration of this report the following benefits where reported for the public sector. More information on the survey can be found in section 3.1 Implementation of Research Methodology.

According to Figure 3, from the 22 representatives from public sector that answered, none of their organizations is using currently Big Data. One is building its scenario to plan the deployment of a Big Data solution, 10 organizations have medium term plans to use Big Data, and the other 11 have not defined a strategy yet. From these data it can be understood that the public sector is not one of the most advanced in the application of big data technologies for the improvement of its operations.

According to the results presented in Figure 4, sharing data with 3rd parties and providing better service to citizens could be the greatest benefits of the use of big data in public sector organizations, followed by providing new services and the internal efficiency. So breaking the silo culture and improving the service are the top issues in public organizations where big data can help.

According to results from Figure 5, the most valuable information to collect for Big Data strategy is current data (information required for developing the functions of the public body) and citizen data (so, that is, having a better knowledge of the “customer”).

Figure 4: In your opinion, what benefits for your organization will the use of Big Data have?

The data currently collected or planned to collect, as shown in Figure 6, the data collected by most of public bodies is historical and current data, followed by citizen and service data. Compared with the information from Figure 5, it is a good starting position so mostly the current data managed for the provision of services and citizens’ data are already being collected, and that is the data with the most perceived value.

Regarding the use of cloud storage for the data in public bodies, it is still a minority who is using (15%) and for the rest opinions are divided among those who will implement the use of cloud storage and those who does not have any intention of using it. This can be linked with the opinions from the survey performed for the formulation of the European Big Data Value Partnership, where one conclusion was that the public sector still needs some regulation development to trust cloud solutions.

Figure 7: Your organization and data storage in the cloud?