Talk
Data analytics applied to decision making in social security The case of Portuguese survivor’s pension
Joel Vilas, Boas (Boas, Joel); David Ferraz (Ferraz, David);
Event Title
IIAS-EUROMENA 2022 Joint Conference on Next Generation Governance and Young Global Public Administration
Year (definitive publication)
2022
Language
English
Country
Italy
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(Last checked: 2024-06-30 03:47)

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Abstract
Society expects that technological evolution will lead to an evolution of efficiency, effectiveness, and economy in the use of public resources, allowing better decisions to be made. With the application of big data techniques, several authors argue that it is possible to simplify the decision-making process, reduce costs, increase quality, achieve better operational and financial results, make governments more efficient and effective, better strategic, tactical and operational decisions, problems are identified and solved, results are optimized, greater productivity and alignment of the organizations’s objectives with the strategies defined through the analysis of performance indicators. In 2021, it was estimated that the budget of the Ministry of Labour, Solidarity and Social Security represented 32,16% of all budgetary expenditure in Portugal, and 49,65% of social security expenditure is related to pensions, supplements and complements. Having said this, it is fundamental that there is a public management based on the principles of efficiency, effectiveness, and economy, in order to ensure the sustainability of public finances, but also to guarantee that citizens can have an adequate and timely response to their problems. The author intends to answer the following research question, can data analytics contribute to improve decision making in the management of the survivor’s pension? For this, the objective is to develop a theoretical model of data analytics as a support for decision-making in the management of the survivors pension, by an exploraty interview to the decision makers of this benefit and interviews with data analytics specialists.
Acknowledgements
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Keywords
Big Data,Digital transition,data analisys,social security,Segurança Social,Reform,Governance

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