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This study aimed to identify the impact of Big Data technology on improving the quality of service in the pension system managed by the Office of Pension Normalization (ONP) in Peru during 2023. Its primary objective was to increase the percentage of affiliates, as data from the National Institute of Statistics and Informatics (INEI) and the Ministry of Economy and Finance indicated that Peru had approximately 2 million retirees by 2024. Of these, only around 25% were affiliated with the ONP, reflecting low coverage compared to those enrolled in the private regime of Pension Fund Administrators (AFP). This situation raised concerns among various sectors, including government agencies, public policy experts, and civil society, regarding the ONP’s capacity to ensure adequate retirement benefits. In this context, the adoption of Big Data technologies emerged as a potentially disruptive solution to drive reforms in the pension system managed by the ONP. The study was conducted using a quantitative approach, employing questionnaires administered to 139 beneficiaries of the system. It analyzed demographic, employment, and health-related aspects, which allowed for the identification of patterns and trends contributing to optimizing care and services offered to retirees, thereby improving their quality of life. Furthermore, the research sought not only to understand the application of Big Data in the Peruvian context but also to provide practical recommendations for modernizing the pension system, aligning it with global best practices in data management and public services.

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Peruvian Case Study for the Impact of Big Data on Service Quality

  • 会议论文

  • 发表日期：

    2025年

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  • Ricardo Manuel Arias Velásquez,
  • Blanca Rodríguez Dávila,
  • Carlos Enrique Núñez Palacios,
  • Sheila Sierralta Pinedo

摘要

This study aimed to identify the impact of Big Data technology on improving the quality of service in the pension system managed by the Office of Pension Normalization (ONP) in Peru during 2023. Its primary objective was to increase the percentage of affiliates, as data from the National Institute of Statistics and Informatics (INEI) and the Ministry of Economy and Finance indicated that Peru had approximately 2 million retirees by 2024. Of these, only around 25% were affiliated with the ONP, reflecting low coverage compared to those enrolled in the private regime of Pension Fund Administrators (AFP). This situation raised concerns among various sectors, including government agencies, public policy experts, and civil society, regarding the ONP’s capacity to ensure adequate retirement benefits. In this context, the adoption of Big Data technologies emerged as a potentially disruptive solution to drive reforms in the pension system managed by the ONP. The study was conducted using a quantitative approach, employing questionnaires administered to 139 beneficiaries of the system. It analyzed demographic, employment, and health-related aspects, which allowed for the identification of patterns and trends contributing to optimizing care and services offered to retirees, thereby improving their quality of life. Furthermore, the research sought not only to understand the application of Big Data in the Peruvian context but also to provide practical recommendations for modernizing the pension system, aligning it with global best practices in data management and public services.