Where Will Your Next Bestseller Grow?

Introduction

The food industry is always changing. Consumer tastes change quickly. A small trend today could be a bestseller tomorrow.

So, how do you find these opportunities first? The answer is data.

This article will show you how to use an Terno AI to analyze global food production trends and uncover new market opportunities. We'll explore a real-world dataset to demonstrate how, with a few simple prompts, you can gain a significant competitive advantage.[See the full Terno AI conversation here]

Getting the Big Picture

Before diving into a specific product, it's smart to get a high-level view of the entire global food landscape. This helps you understand the major players for all key commodities at a glance. For this, you can ask for a comprehensive visual overview:

Prompt: Plot a heatmap of food production by country and commodity.

This map is your "at-a-glance" guide to the world's food supply. You can instantly see which countries are the powerhouses for which foods (e.g., USA for maize, Brazil for soybeans). This helps you spot regional strengths and potential sourcing hubs in seconds.

Identifying Top-Producing Regions

Let's say your company is looking to expand into the plant-based food market. Soybeans, a key ingredient in many plant-based products, would be a critical component of your supply chain. To identify the top producers of soybeans, we can ask:

Prompt: Create a map showing top producers of soybeans.

This map zooms in on your specific ingredient. It answers the question, "Who are the biggest, most reliable suppliers for my product?" This is the first step in building a strong supply chain.

Analyzing Key Commodity Trends

Once you've identified the top-producing regions, the next step is to understand the stability of the supply. A region might be a top producer, but what if its production has been declining over the years? To analyze the historical trend of a key commodity, you could ask:

Prompt: Show me the trend of global wheat production from 2000 to 2020.

This chart shows you the risk and stability of an ingredient. A steady, upward trend means the supply is reliable. A chart that's flat, declining, or wildly inconsistent is a red flag. It could mean higher prices or future shortages.

Assessing Food Production Diversity

The next step is to understand the broader agricultural landscape of different regions. A diverse food production ecosystem can indicate a more resilient supply chain and a wider range of potential ingredients for new product development. To compare the food production diversity between two continents, you could ask:

Prompt: Compare food production diversity between Asia and Africa.

This helps you understand sourcing risk. A region that only grows one or two major crops is vulnerable. A bad-weather event could wipe out its entire supply. A region with high diversity is a safer, more stable partner because its economy doesn't depend on a single crop.

Uncovering Emerging Market Opportunities

Finally, to truly get ahead of the competition, you need to identify the "rising stars" of the food world—countries that are showing rapid growth in the production of specific commodities. For example, if you're looking to launch a new line of rice-based snacks, you could ask Terno AI :

Prompt: Which countries have shown the fastest growth in rice production?

This is how you find new opportunities. These "fast-growing" countries might be untapped, lower-cost suppliers. They could also be perfect new markets to sell your rice snacks to, since you know the local supply and interest are growing.

Future-Proofing Your Strategy with Predictive Analytics

The ultimate competitive advantage is the ability to see into the future. With a time series modeling prompt, you can forecast the production of key commodities, allowing you to make proactive decisions about sourcing, pricing, and product development. For example, you could ask:

Prompt: Predict maize production for the next 5 years using time series modeling.

This is a financial forecast for your ingredients. If the model predicts production will go up, you can expect stable or lower prices. If it predicts a drop, you should prepare for higher costs or start securing contracts now to lock in a good price.

From Insight to Action: Making Strategic Sourcing Decisions

After all the analysis, it's time to make a decision. This is where you can turn broad insights into a specific, actionable strategy. By combining your knowledge of trends, growth, and top producers, you can ask a direct business question to guide your supply chain strategy:

Prompt: Which countries should we target for sourcing raw materials for packaged grains?

This is the final, actionable answer. The AI takes all the previous data—who grows the most, who is stable, who is growing—and gives you a simple, ranked list. This helps you confidently decide where to build your supply chain and find your raw materials.

Summary

Here’s summary of the four key dimensions in global food production—trends and risks—based on our analyses:

1. Global Wheat Production (2000–2020) 

• Steady growth from about 594 million tonnes in 2000 to roughly 765 million tonnes in 2020 (+29%). 

• Annual increases averaged ~1.3% per year over the two decades.

2. Commodity Volatility (1961–2021) 

• Most susceptible to year-to-year swings (std dev of annual % change): 

– Palm oil: 14.17% 

– Soybeans: 12.05% 

– Yams: 10.96% 

– Sunflower seed: 10.66% 

– Coffee (green): 10.42% 

• Oil crops and root crops show the highest climate‐driven variability.

3. Rice Production Growth (2000–2020 CAGR) 

• Fastest‐growing nations by compound annual growth rate: 

1) Gabon – 52.2% 

2) Kuwait – 43.2% 

3) South Korea – 42.3% 

4) Turkey – 38.0% 

5) Denmark – 29.2% 

• Reflects both emerging producers and highly dynamic smaller markets.

4. Soybeans Production Map (Latest Year) 

• Top producers in 2021: 

1) Brazil (~140 Mt) 

2) United States (~96 Mt) 

3) Argentina (~63 Mt) 

4) China (~18 Mt) 

5) Paraguay (~9 Mt) 

• Concentration in the Americas underscores supply-chain concentration risks.

Key Takeaways & Risks 

– Staple grains (wheat, maize, rice) show robust long-term growth, but specialty crops (oil seeds, root crops, coffee) are far more volatile and therefore more climate‐vulnerable. 

– Diversification across crop types and regions is critical: heavy reliance on a few oil crops or root crops increases exposure to extreme weather swings. 

– Emerging high-growth rice producers (e.g. Gabon, South Korea) may offer new supply opportunities but with greater risk. 

– Major producers of staples (Brazil, U.S., Argentina) remain the backbone of global supply but face challenges around land use and climate change adaptation. 

– Sourcing strategies should balance scale (high-volume grains from established producers) with stability (lower-volatility supply from regions with more consistent yields).

Conclusion

In the food industry, data is your most valuable ingredient. By leveraging the power of Terno AI, you can move beyond guesswork and make data-driven decisions that fuel growth and innovation. 

The ability to quickly analyze global trends, identify top-producing regions, and spot emerging market opportunities is no longer a luxury reserved for large corporations with teams of data scientists. With the right tools, these insights are now at your fingertips.

Ready to find your next bestseller? Book a free demo of Terno.ai to see how you can turn global food production data into a roadmap for your next big product launch.

Useful Links

• Terno AI: https://terno.ai
• Dataset link: World Food Production
• Detailed analysis: https://nikita.app.terno.ai/chat/share/82e488fb-1756-4d42-95a0-421d7390a1d8