Louis Dreyfus Company

Daniel Braga

Data Leadership Champion

My professional journey lies at the intersection of business process optimization and technology implementation. I began by focusing on systems integration and ERP modernization, progressively expanding into the use of data as a driver for smarter, faster decisions.

At Louis Dreyfus Company (LDC), a leading global merchant and processor of agricultural goods, I have had the opportunity to lead multidisciplinary teams through complex digital transformations, connecting legacy systems with modern data platforms to generate real business value. This journey has taught me that successful digital transformation isn’t just about tools, but also about aligning technology, people and data around a clear strategic vision.

Leading in a Complex, Global Supply Chain

Modern supply chains are increasingly complex, global and interconnected—requiring leaders to balance operational discipline with adaptability. My leadership approach focuses on the following principles:

First, I ensure that all teams have a clear understanding of our strategic objectives. This shared vision enables better decision-making and helps teams prioritize their efforts in line with broader business goals.

Second, I promote close collaboration between data and technology teams and the business domains they support—such as logistics, procurement and commercial operations. Embedding analytics within these functions breaks down silos and ensures solutions are relevant, timely and actionable.

 Successful digital transformation isn’t just about tools, but also about aligning technology, people and data around a clear strategic vision. 

Lastly, I lead with a product mindset. Rather than delivering isolated tools, we develop data products that serve specific use cases and are owned by multidisciplinary teams. This modular, outcome-focused approach enables us to respond quickly to market changes while maintaining scalability across LDC’s global footprint.

Ultimately, at LDC, strong leadership in supply chain transformation means fostering a culture of accountability, flexibility and shared success—where every team knows their role, understands the value they bring and is equipped to deliver meaningful results.

Navigating the Realities of AI in Supply Chain Optimization

AI brings enormous potential to supply chain operations, but its implementation comes with real-world complexities. One of the key challenges we faced was ensuring data readiness—particularly integrating structured data from ERP systems with unstructured or external data sources such as weather forecasts, sensor telemetry and market signals.

Another significant challenge is driving adoption. Even the most accurate AI model has a limited impact if people don’t trust or use its output. That’s why we emphasize transparency and usability over black-box complexity. Instead of building models that only deliver predictions, we design solutions that also explain the “why” behind the outcome – making it easier for planners and decision-makers to act with confidence.

We've also adopted a human-in-the-loop approach, where AI augments expert judgment rather than replacing it. Starting with targeted use cases like predictive maintenance or demand forecasting, where success can be measured in uptime or inventory turnover, helped us gain credibility and prove value early on.

By combining strong data governance, focused business collaboration and an iterative rollout strategy, we’ve been able to scale AI initiatives with greater trust, adoption and business impact.

Balancing Efficiency and Innovation: Our Framework

We operate under a dual-track model: one focused on operational excellence (standardized, stable reporting) and another on innovation and discovery (exploratory analytics, AI and simulation).

Both tracks operate under a shared architectural and governance framework, with centralized data standards but decentralized delivery. This approach allows us to meet regulatory and compliance requirements while still experimenting with cutting-edge technologies. It enables safe innovation: we innovate fast but always within guardrails that keep us aligned with enterprise goals.

Building Collaborative, Multidisciplinary Teams

In data-driven organizations like LDC, collaboration is nonnegotiable. We foster a culture of shared accountability by establishing cross-functional ‘squads’ where business analysts, engineers, architects and data scientists work as one team.

My role is to ensure these teams have a common language, shared purpose and clear ownership. Regular syncs, transparent roadmaps and incentives aligned around shared KPIs have been key to sustaining engagement and performance across regions and functions.

Advice for Fellow Leaders

To modernize global operations, start with your business challenges, not the technology. Understand the pain points and anchor your roadmap around real use cases. Then ensure your data foundation is strong. Don’t rush into AI or cloud without solid governance and integration strategies. Treat data as a product: design it for consumption, measure its adoption and iterate often.

And finally, prepare for the long game! Digital transformation isn’t a sprint. It’s a multi-year journey requiring patience, adaptability and strong sponsorship.