Data Mexico - Observatory of Public Sector Innovation

Data Mexico was developed to integrate and transform public and private sector data to enable a better understanding of the economic and social context. The platform facilitates strategic decision-making through key evidence and integrating databases with technologies for aggregating, filtering and reorganising information. In this way, it innovates in public access to data, contributing to the development, diversification and promotion of the Mexican economy.

Innovation Summary

Innovation Overview

Data Mexico (DataMéxico) aims to address the growing need to access and visualise the economic and social information collected in Mexico over the last few years, allowing the Federal Government to articulate an economic promotion strategy. While there has been a substantial improvement in the efficiency and technology of data collection tools, there was no project close to the economic community that was able to bring together the functionality, analysis and information needed to understand the context in the sector. In a globalised economy, the availability of strategic and up-to-date information is an important advantage for leveraging and diversifying foreign investment in key areas of interest, so a platform that would enable evidence-based planning was essential for the optimal development of the area. The platform is an effort from the Mexican Ministry of Economy (Secretaría de Economía - SE), who together with the National Institute of Statistics and Geography (Instituto Nacional de Estadística y Geografía - INEGI) and Datawheel (software service provider), have managed to integrate various public and private sector databases to create thousands of profiles of industry, city, occupation, product, institution and country with which Mexico is commercially related; thus generating a platform as a centre of digital economic innovation.

The databases are integrated through Datawheel's own technologies called Tesseract and Bamboo, which allow the aggregation, filtering, search and transformation of the files into elements that are then understandable by the platform's Content Management System (CMS), thus generating thousands of data connection points and automatically populating the aforementioned profiles. Each profile includes detailed information coming mostly from INEGI databases, and updated monthly with relevant indexes, visualisations and maps that allow to understand in a simple way and with an articulated narrative the development of each sector available on the platform. In this way, investors, companies, local governments and educational institutions can benefit from the availability of data, enabling research and analysis, and generating better proposals for public policies in the country.

DataMéxico integrates a wide range of data on trade, production, employment, education and demographics, among others, for the whole country, with high spatial resolution at regional and municipal level, which has allowed optimising the resources destined to inform industrial, business, local government and civil society actors, among others. Users can also build their own visualisations with the data available through the "Vizbuilder", customising different metrics, filters, selecting datasets of interest and finally being able to download all the information necessary for their analysis, thus facilitating access to the information for any entity interested in the economic analysis of the country.

Innovation Description

What Makes Your Project Innovative?

A fundamental element of the platform relates to the analysis of Economic Complexity in Mexico. This methodology allows using the data available in a given geography to predict development dynamics. Complexity considers and relates capabilities, resources, technologies, human capital and infrastructure to their development potential. This is expressed through the calculation of the Economic Complexity Index (ECI), thus allowing the quantification of the probability of success in the development of a given economic activity. The calculation can also be performed for Product Economic Complexity (PCI) by analysing manufacturing, sales or export data; and for Economic Activities (ACI) by considering employment or production data. The platform is already implemented and has proven to be of great help to the economic sector in Mexico, becoming a reliable source of data, especially for institutions.

Innovation Development

Collaborations & Partnerships

The Ministry of Economy is the main entity driving the development of DataMéxico, obtaining resources for its development and establishing the main design guidelines. The National Institute of Statistics and Geography provides much of the data, facilitating its collection and enabling its use. Finally, Datawheel is the company in charge of building the platform, providing the technologies and technical knowledge for its development.

Users, Stakeholders & Beneficiaries

Economic stakeholders are the main interest group for the development of the platform and have benefited the most from it. Investors and companies have been able to obtain strategic information for the development of their activities. However, educational institutions have also benefited enormously from having this type of information available for the development of research in the economic sector.

Innovation Reflections

Results, Outcomes & Impacts

Nearly 2,000 people (citizens, public servants, investors and researchers) have been trained to learn how to use and take advantage of Data Mexico. Also, from January to September 2022, the platform has received 1.9 million visits. Among the impacts is access to more information for decision-making. Companies from different sectors have shared with the Ministry of Economy that Data Mexico allowed them to identify data to evaluate their investment projects.

Challenges and Failures

One of the challenges faced during the development of the platform was working with anonymised data. Many institutions set conditions for making data visible and, in some cases, a certain minimum value must be met in the records in order to be shown publicly and not leave individual records in evidence. In DataMéxico, an algorithm was developed to hide records that must be anonymised, displaying only values that meet the conditions set by the institution providing the data. This allowed them to dynamically publish their data on the platform, and to generate an innovation in the management of individual data. This, added to the difficulties for the Ministry of Economy to argue the justification and relevance of the project in a public platform with data coming from external entities, generated a bureaucratic process that, despite affecting the technical development of the platform, did not stop its progress.

Conditions for Success

In addition to the budget to have the technological infrastructure, maintenance and updating of the platform, it is necessary to have a team and leadership that manages and institutionalises the processes of data selection, integration and updating. In the absence of a proprietary data platform, it is important to align the objectives of the public institution that owns the platform with the platform's information integration planning. It is also important to follow good management and evaluation practices.

Replication

It has not been replicated.

Lessons Learned

We want to share our experience as data-driven innovators in collecting, opening, integrating, analysing and visualising multiple sources of information from the public, private and social spheres. Especially the experience in Business-to-Government (B2G) data collaboration. From Data Mexico, we have identified a supply chain that starts with a diagnostic programme to obtain the required data, an identification of the main data owners, and subsequently, a collaboration with them in data sharing practices. Data Mexico has taken a leadership role in integrating multiple data sources from different actors, telling stories that in the past were not possible to explore due to lack of interaction. We also want to share the challenges, such as access to information, data quality in the collection processes, different methods of identification at different levels (geographical, sectoral and personally identifiable), leading to the exploration of different techniques to anonymise sensitive data. We would also like to share our experience in disseminating such projects (e.g. organising Data Challenges).

A project based on public sector-driven data collaboration is not sustainable without data governance. Data governance is necessary for coherent implementation and coordination, as well as for strengthening institutions on policy, capacity and technical grounds. Data governance has taught us how to better control and manage the data value cycle. Overall, we can share our experience on the way to build, from government in coordination with the private sector, academia and other actors, data governance as a mutual agreement.

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