Food Data is Failing Us: A 3-Part How and Why Video Series

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Many of us don’t recognize the problems facing our food systems, even when they’re hiding in plain sight. And if we do? Our best efforts to find answers are insufficient. We aren’t even able to ask the right questions. Why? Because food data is fundamentally flawed.

This reality has fueled TeakOrigin and its Co-Founder and CEO Brent Overcash to find a meaningful solution. Even though these problems affect us all, they can be hard to understand, so Overcash created this three-video series to explain the problems and what has kept us from solving them.

In this video Overcash deals with food profile data (0:47) and its issues with small sample size (1:45), old data (2:23), and static data (3:00), as well as food metadata (4:14). To show how pervasive the issues are he also has a very real world example of the failures in our food data, and specifically how these failures impact the quality of apples (5:10).

We wanted to hear a bit more about our food systems, and this series in general, so we asked a few questions about this first video that goes into detail about the mess our current food data has created.

What’s the most important thing for viewers to walk away with?

When it comes to food, we are looking in the wrong direction. We are looking at the physical aspects of food and not the nutritional quality. You are being sold on the messaging of wholesome produce, not the facts or data.

How did we end up here?

Unintentionally. At the end of WWII the food system reacted to the end of the war with the goal of growing more food, but people didn’t realize the consequences of that singular goal. At the time, appearance was our only way to judge quality, but that’s still what’s happening.

We could get watermelons 12 months a year from all over the world, but no matter how great they looked, they’d lose vital nutrients in part due to shipping times and conditions.

How have we been misunderstanding our food?

It’s the Quasimodo syndrome, we’ve been trained that physical beauty is quality. If it looks great, it is high quality. But appearances have nothing to do with nutritional quality.

The world has more food than ever today, but we have the most malnutrition ever, the most obesity ever.

But what about USDA food data? That tells me what’s in watermelon, any produce, doesn’t it?

Those labels tell us what should be in food, but that data is so old, and comprised of so few samples, we don’t know if it represents reality or how food is being grown today. Even with fresh food you can have fundamentally different crops in the same season, even the same field. We all take it for granted that these labels are “accurate” because they’re literally all that we have. On top of that, food loses nutrition as it makes its way through our ever increasing supply chain. Produce no longer comes from around the corner, it comes from literally all over the world. That journey has a huge nutritional cost that almost no one recognizes. But every app and website continues to use the same static, antiquated data. They try to tell us what’s in our food, but they can’t. On average, we make something like 220 food decisions a day, what if the information fueling those decisions is all “off”? Well, it is.

How does this affect people who don’t usually dive into the “data” side of things?

We aren’t telling you about food data, we are telling you about food. Quality, price, value, they’re the things you care about with food, and they’re all data. No one likes to get screwed over, you want to get what you pay for. I paid a dollar for this apple, did I get a dollar’s worth of apple?

The right food data can answer that. We’ve never had the opportunity to answer these questions before, but we finally can.

What inspired you?

I was inspired to create this series because there is a universal misunderstanding — people have been fundamentally misled to believe something about their food that is not true and it needs to change.

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