I had the opportunity to attend Gartner Data and Analytics Summit in São Paulo, Brazil, March 25-27. The conference brought together industry leaders, experts and practitioners to discuss the latest trends, strategies and best practices in data and analytics. Brazil’s growing importance in the AI landscape was evident throughout the event, with many informative presentations and discussions focused on AI adoption and innovation.
One of the interesting lectures I attended was given by Eduardo Cantero Gonçalvessenior manager of data analysis at Mercado Livre (Free market). Mercado Livre is a leading e-commerce and fintech company that has established itself as a dominant player in the Latin American market. With operations in 18 countries, including major economies such as Brazil, Argentina, Mexico and Colombia, Mercado Livre has built a vast e-commerce and payment ecosystem. The company’s strong market presence and large user base have made it a leader in the region.
During his presentation, Gonçalves shared Mercado Livre’s remarkable journey in democratizing data and AI within the organization while fostering a strong data-driven culture. As AI continues to transform industries around the world, Mercado Livre’s experience offers valuable lessons for organizations looking to harness the power of AI and build a data-driven culture.
In this article, we’ll explore the key takeaways from Gonçalves’ presentation, focusing on the company’s approach to democratizing data, empowering non-technical users with low-code AI tools and by cultivating a data-driven mindset throughout the organization.
Mercado Livre’s data democratization journey
Mercado Livre’s journey toward data democratization has been a transformational process that has reshaped the company’s approach to data and AI. Gonçalves highlighted the importance of moving from a centralized data environment to a decentralized one, allowing teams across the organization to access and leverage data for decision-making and innovation.
A key aspect of this transition has been the development of internal data tools. By creating its own tools, Mercado Livre was able to tailor the solutions to its specific needs and ensure seamless integration with its existing systems. This approach not only provided greater flexibility, but also fostered a sense of ownership and collaboration between teams.
One of the most important steps in Mercado Livre’s data democratization journey was the introduction of machine learning tools designed for both data scientists and business users. Gonçalves emphasized the importance of enabling non-technical users to harness the power of AI and ML without relying heavily on data science teams. By providing low-code tools and intuitive interfaces, Mercado Livre has enabled business users to experiment with AI and ML, thereby driving innovation and efficiency across different departments.
The democratization of data and AI has had a profound impact on Mercado Livre’s operations and culture. It has fostered a more collaborative and data-driven environment, where teams can easily access and analyze data to inform their strategies and decision-making processes. This change has not only improved operational efficiency, but also opened up new opportunities for growth and innovation.
Empowering Non-Technical Users with Low-Code AI Tools
One of the highlights of Mercado Livre’s data democratization journey is its focus on empowering non-technical users with low-code AI tools. During his presentation, Gonçalves highlighted the importance of enabling business users to experiment with AI and machine learning without relying heavily on data science teams.
To achieve this, Mercado Livre has developed an internal tool called “Data Switch”, which serves as a single web portal allowing users to access all data-related tools, including query builders, dashboards and machine learning tools. This centralized platform makes it easier for non-technical users to leverage AI and ML capabilities without the need for in-depth programming knowledge.
Gonçalves specifically mentioned that Mercado Livre introduced low-code machine learning tools to enable business users to conduct experiments independently. By providing intuitive interfaces and pre-built templates, these tools enable domain experts to apply their knowledge and ideas to AI-based solutions. This approach not only democratizes AI, but also accelerates innovation by enabling more people within the organization to contribute to AI initiatives.
The impact of empowering non-technical users with low-code AI tools has been significant for Mercado Livre. Gonçalves noted that the company has seen a substantial increase in active users, data storage, ETL tasks and dashboards following the introduction of these tools.
Mercado Livre’s success in this area provides a valuable case study for other organizations seeking to democratize AI and empower their workforce. By investing in low-code AI tools and providing the necessary training and support, businesses can unlock the potential of their non-technical users and foster a culture of innovation.
Foster a data-driven culture
In addition to democratizing data and AI tools, Mercado Livre recognized the importance of fostering a data-driven culture across the organization. Gonçalves highlighted several key initiatives the company has undertaken to cultivate a mindset that embraces data and AI-driven decision-making.
A notable step was the creation of a space dedicated to Data Culture within Mercado Livre. This team was responsible for promoting data literacy, providing training, and supporting data-driven initiatives across the organization.
To measure the success of its data literacy efforts, Mercado Livre developed a “Data Driven Index” that tracks user engagement with data tools. This index provides a quantitative measure of how employees adopt and leverage data in their daily work. By regularly monitoring this index, the company can identify areas for improvement and adjust its strategies accordingly.
Another key initiative was the “Data Champions” program, which aimed to train power users who could then help spread the data-driven culture throughout the organization. These champions serve as advocates and mentors, promoting best practices and helping their colleagues effectively leverage data and AI tools. By empowering a network of champions, Mercado Livre was able to scale up its data culture efforts and drive adoption across the company.
Lessons learned from Mercado Livre’s experience
Mercado Livre’s journey in democratizing data and AI offers valuable lessons for other organizations looking to embark on a similar path. One of the key takeaways from Gonçalves’ presentation was the importance of executive sponsorship in fostering a data-driven culture. Having strong support and advocacy from leadership is critical to driving organizational change and ensuring data and AI initiatives receive the necessary resources and priority.
Another important lesson is the value of collaborating with HR to integrate a data-driven culture into employee onboarding and development programs. By making data literacy and AI skills an essential part of employee training, organizations can ensure their workforce is well-equipped to leverage these tools effectively. Mercado Livre’s partnership with HR has helped them scale up their data literacy efforts and make it a fundamental part of their employees’ growth and development.
Finally, Gonçalves emphasized the importance of continuously measuring and iterating data-driven initiatives. By tracking key metrics like the Data Driven Index and regularly seeking employee feedback, organizations can identify areas for improvement and make data-informed decisions to optimize their strategies. This iterative approach ensures that data and AI initiatives remain aligned with business objectives and drive meaningful impact.
As organizations navigate the challenges and opportunities of the AI era, Mercado Livre’s experience provides a valuable case study for democratizing data and AI while fostering a data-driven culture. By empowering employees at all levels to leverage these tools and cultivating a mindset supportive of data-driven decision-making, businesses can position themselves for success in our AI-driven world.
