TO WHAT EXTENT COULD THE USE OF BIG DATA MAKE PERUVIAN LABOUR INSPECTIONS MORE EFFECTIVE?

The Peruvian authority responsible for supervising the fulfilment of labour rights, the Superintendencia Nacional de Fiscalización Laboral (“SUNAFIL”), currently relies on traditional inspection methods.

When it comes to selecting companies for inspection, the SUNAFIL still uses a traditional selection formula. This means that inspections are performed in the following instances:

– When workers make a petition.

– When inspectors decide to perform an inspection randomly.

– When companies file private petitions.

– When unions make a petition.

– When a specific authority from the National Labour Department (the Ministerio de Trabajo y Promoción de Empleo or “MTPE”) submits a petition.

– When a labour judge files a judicial petition.

SUNAFIL oversees the selection of companies for inspection and initiates investigations. Although SUNAFIL has long practical experience in company selection, the efficiency of this process could be significantly improved by implementing a computationally efficient system to simplify the selection of companies for labour inspections.

This Insight will focus on how Big Data and Algorithms could be beneficial for SUNAFIL in achieving a more effective selection process, thus avoiding unnecessary waste of time and resources in its inspection tasks. It will also address the risks and challenges that need to be overcome to make efficient use of Big Data.

MAIN PROBLEM IN THE USE OF THE TRADITIONAL SELECTION METHOD

According to El Comercio newspaper, 65% of the labour inspections conducted by SUNAFIL are initiated through workers’ petitions, while 35% are initiated through organised public campaigns by SUNAFIL.

Brian Avalos Rodriguez, an expert in Peruvian labour law, stated in an article for Gestión newspaper that, during the pandemic, eight out of ten labour inspections were initiated due to worker petitions against companies.

Consequently, if SUNAFIL has to address each independent petition at the expense of well-planned inspections, it is likely that the administrative inspection system will be overloaded in the short and long term. Therefore, it is highly relevant for SUNAFIL to allocate resources efficiently and sustainably.

The role of Big Data is crucial in this context because it enables more precise responses and computational methods for selecting companies that require inspection to ensure their compliance with labour rights, rather than relying on the traditional inspection formula.

ADVANTAGES OF THE USE OF BIG DATA FOR LABOUR INSPECTIONS

Preventive Measures: The aim is to identify companies at high risk of infringement before any infringement occurs. The use of Big Data should significantly heighten companies’ awareness of the potential for labour inspections, creating a positive impact on their commitment to labour rights compliance.

Cost Reduction: Big Data will lead to cost savings in terms of time management, financial resources, and human capital. Consequently, this technology should enable SUNAFIL to allocate its economic resources more efficiently in the long term, achieving better preventive outcomes with minimal intervention.

Reducing Reliance on Traditional Inspections: Traditional inspection methods will become a secondary tool when Big Data is employed. If companies with a higher risk of infringement fail to take preventive measures, traditional inspection methods can be employed in conjunction with technology-based methods.

Creation of Company Profiles: The use of Big Data also aims to establish company profiles and categorise them based on the probability of labour rights infringement. This approach will allow SUNAFIL to build comprehensive profiles for each company, enabling it to focus preventive inspection efforts on those companies with a higher risk of infringement.

RISKS AND CHALLENGES OF THE USE OF BIG DATA FOR LABOUR INSPECTIONS

The first risk pertains to the objective of computational law, which is defined as follows by  Michael Genesereth:

“Computational Law is the branch of legal informatics concerned with the automation of legal reasoning. While there are many possible applications of Computational Law, the primary focus of work in the field today is compliance management, i.e., the development and deployment of computer systems capable of assessing, facilitating, or enforcing compliance with rules and regulations.”

Therefore, in line with this definition, when using Big Data as a tool for automating legal reasoning, it must adhere to all regulations. In this specific context, it must not infringe upon data protection legislation or fundamental rights related to privacy and non-discrimination.

In Peru, data protection is governed by Law 29733. Article 7 of the Peruvian Data Protection Law emphasises the importance of respecting the principle of proportionality and ensuring the appropriate and non-abusive use of personal data:

“Article 7: All processing of personal data must be adequate, relevant, and not excessive for the purpose for which they were collected.”

The second risk arises from the outsourcing of Big Data since many of these technologies are developed by private companies. Public authorities are thus responsible for establishing legal profiles and specialists in law and technology to supervise the correct application of Big Data while respecting fundamental rights such as due process, non-discrimination, and privacy. These rights are explicitly stated in the Peruvian Constitution, the Universal Declaration of Human Rights (UDHR), the Charter of Fundamental Rights of the European Union (CHREU) and the International Covenant on Civil and Political Rights (ICCPR).

Finally, the third risk revolves around determining liability in the case of damages resulting from the use of Big Data. In other words, who will be held liable in case of damages? SUNAFIL or the outsourcing company? These are questions that need to be carefully analysed and discussed within the existing civil regulations on liability in order to adapt them accordingly.

CONCLUSION

In conclusion, if SUNAFIL begins to apply Big Data for legal analysis in inspection tasks, this will enable it to establish company profiles with a view to preventing labour-related risks, ultimately enhancing the efficiency and effectiveness of its action. The successful use of this technology could also serve as a model for other public authorities (including the Tax Authority, Judicial Authority, Consumer Authorities, Competition Authorities, among others). However, to benefit society it is essential that the Big Data tool be applied while respecting fundamental rights, constitutional law and human rights guarantees established by hard law, such as the UDHR, CHREU and ICCPR referred above. A legislative approach at the national level must thus be approved for harmonisation and to inspire other countries to follow the same approach.