Marcus Bernardi is the Head of Data & Analytics at Daki, specializing in leveraging data for business transformation and operational efficiency. With a career spanning multiple industries, he began in market intelligence at Natura and held significant roles at Telefónica, Carrefour, and JOKR. At Carrefour, he led data governance initiatives to enhance omnichannel strategies. As Global Head of Analytics at JOKR, he fostered a data-driven culture through advanced analytics and BI tools, now driving data strategy at Daki to enhance customer experiences.

Through this article, Marcus explores the critical role of data and analytics in driving digital transformation and operational efficiency. He discusses common challenges in fostering a data-driven culture, the successful implementation of an agnostic data architecture, and the importance of agile methodologies. Marcus also highlights strategies for utilizing self-service BI tools and staying ahead of consumer behavior trends in the food retail industry.

Common Challenges in Implementing BI Tools and Data Governance Models

In the early stages of my career, particularly at Natura and Telefónica, the biggest challenge was fostering a data-driven decision-making culture. Leveraging data for strategic insights was new, and getting stakeholders on board was complex. To address this, I simplified data analyses, communicated clearly, and involved internal stakeholders in solution development, building trust and engagement around data.

At Carrefour, the challenge centered on digital transformation—upgrading from outdated data infrastructures to modern, scalable tools. The main obstacle was convincing stakeholders of the need for these investments and driving behavioral change. The Brazilian market lacked a deep understanding of what true digital transformation entailed, requiring technology changes and shifts in mindset and processes.

Today, with a robust data architecture and self-service BI tools, the challenge has shifted toward delivering real value through advanced analytics and AI. While these technologies are exciting, their practical application is often limited to specific use cases. Moving beyond curiosity toward scalable, business-aligned AI solutions is the next frontier we are tackling.

"Building a data-driven culture and embracing flexible infrastructures is essential for leveraging data to drive meaningful digital transformation."

Successful Digital Transformation Initiative: Building an Agnostic Data Architecture

One recent success is the development of an agnostic data architecture within our organization. System changes are frequent in a startup environment; for some data sources, we have already been on the third system for as many years. To mitigate the disruption of these changes, we designed an architecture where the data structure is independent of the systems feeding into it.

The key was building a data lake as a historical repository for all tools, enabling system switches without losing data or rebuilding infrastructure. This architecture has provided us with system independence and significantly reduced costs. It has allowed us to avoid costly migrations while maintaining operational efficiency and flexibility, making it a game-changer for our data management strategy.

Staying Ahead of Consumer Behavior Trends Through Data Analysis

Keeping pace with market trends and consumer behavior is essential in the food retail industry. We utilize data sources that offer granular insights on competitor assortments and pricing strategies at a lat/long level, allowing us to adjust our offerings in real time to maintain competitiveness.

Additionally, we integrate data from our app, competitor behavior, and sociodemographic information to create detailed audience models. These models enable us to segment customer behavior and tailor our assortment and marketing efforts to specific customer groups. We also share this intelligence with our suppliers, empowering them to execute high-ROI targeted actions.

The Impact of Agile Methodologies on Project Success in Data and Analytics

Operating within an Agile framework, I find this methodology one of the best for managing projects and ensuring continuous value delivery. Agile enables us to maintain a steady pace of progress, consistently delivering value to stakeholders. By adhering to the principle that “done is better than perfect,” we can evolve solutions to stay aligned with business needs over time.

However, Agile methodologies, particularly SCRUM, can challenge long-term planning. With a heavy focus on sprints, there's a risk of overlooking opportunities for structural improvements that could drive transformative change. Balancing short-term wins with long-term innovation remains an ongoing challenge, but Agile has been pivotal to our project's success.

Training Teams for Effective Use of Self-Service Data Tools

We implemented a multi-layered training approach to ensure teams effectively utilize self-service BI tools. It begins with onboarding, where short video modules introduce new employees to our data structure and tools. We also offer team-oriented training to ensure the content is relevant to specific departments.

Weekly problem-solving groups play a crucial role, allowing teams to clarify tool usage. Hackathons promote cross-departmental collaboration and rapidly disseminate knowledge. Finally, we prioritize documentation—a lesson learned after discovering that incomplete documentation hindered our ability to leverage automated content generation with LLMs fully.

Advice for Professionals Driving Digital Transformation with Data and Analytics

First, cultivate a data-driven culture by simplifying data for stakeholders and involving them in solution development. Second, embrace flexibility in your data infrastructure to prevent system changes from disrupting operations. Finally, while Agile methodologies can deliver short-term wins, they focus on long-term improvements. By balancing these elements, you can effectively leverage data to drive digital transformation and achieve meaningful business outcomes.