5 Minute a-connect General 29/12/2025

Blending AI, data analytics, and optimization to transform agribusiness

Djavan De Clercq is an Independent Consultant with a-connect specializing in AI-powered solutions for agriculture. With a background in engineering, data science, and global consulting, Djavan combines scientific rigor and entrepreneurial drive to deliver real impact for clients. With his four-step framework, 1) Measure, 2) Diagnose, 3) Anticipate, and 4) Optimize, he helps organizations make smarter, data-driven decisions in complex environments.

We wanted to learn more about Djavan and what his key learning from your consulting journey is, so we asked her a few questions:

Can you provide a brief synopsis of your professional background?

Djavan:

“I am an engineer by training with a quantitative background, having conducted PhD-level research in engineering and data science at Tsinghua University and the University of Oxford, and graduate-level work in mathematical optimization at UC Berkeley. My career has woven together research, consulting, and entrepreneurship: I spent several years at McKinsey & Company managing global projects at the intersection of AI and agriculture, especially in supply chain analytics and food security. Alongside this, I gained hands-on experience in Chinese tech companies, building recommendation systems and data engineering solutions. Today, I channel this mix of scientific rigor, consulting insight, and entrepreneurial drive into building AI-powered ventures in agriculture that deliver real impact for clients worldwide.”

What brought you into consulting?

Djavan:

“I was drawn to consulting for the variety and impact of projects across sectors and geographies, and I’ve always enjoyed solving complex problems by blending technology with economics. Today, in conjunction with AI tools, I can deliver high-impact solutions to clients just as quickly and effectively as large consulting organizations, bringing results faster, with the same cutting-edge resources, but far more flexibility.”

What motivates you most about working with a-connect?

Djavan:

“I’m motivated by tackling difficult problems in agriculture that require both high-level strategic thinking and deep technical execution. What I enjoy most is taking a broad strategic question; how to build resilience, improve yields, or reduce supply chain risk, and turning it into a practical, day-to-day system that people actually use. That often means combining Python-based analytics, machine learning, and engineering know-how with an understanding of real agricultural operations. For example, I’ve built optimization engines that help producers adapt their supply chains to uncertainty, and satellite-driven monitoring tools that allow teams to respond to field conditions in real time. Working at this intersection of strategy, technology, and on-the-ground implementation is what I find most meaningful.”

What is a key learning from your consulting journey that you would like to share?

Djavan:

“A major learning is that AI only creates real impact when it follows a disciplined, end-to-end problem-solving sequence. The sequence is simple but powerful:

• measure what is happening,
• diagnose why it is happening,
• predict what will happen next, and
• optimize what to do about it.

This turns AI from a buzzword into a practical decision engine.

In agriculture, I’ve seen this repeatedly. Weather, soil, or satellite predictions only matter when they directly inform real operational choices, adjusting planting windows, irrigation schedules, harvest timing, or supply chain allocation. 

For example, for growers, forecasting sunshine hours or crop maturity becomes meaningful when it reduces post-harvest losses, prevents packhouse bottlenecks, or aligns supply with market demand.

Agricultural traders and commodity desks can use this framework to forecast production, understand risk exposure, and make better pricing or hedging decisions.

Governments can use this framework to structure to strengthen food-security systems, anticipating production shortfalls, pre-positioning resources, and planning import strategies before a crisis emerges. The consistent pattern is that AI delivers the most value when it is tightly linked to an operational decision, embedded into day-to-day workflows, and continuously improved with feedback.”

What’s something people might be surprised to learn about you?

Djavan:

“When I’m not consulting, I love to travel with family and friends, play guitar and sing, play basketball, and read. Also, I run a weekly newsletter, Agri-Ninja, which is read by major agri companies. ”

Click here to access his newsletter: https://agri-ninja.com/

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