Fast Four: A Lingua Franca for Business Data

Non-fungible tokens (NFTs) set the world abuzz in 2021. People bought virtual furniture, images of apes in garish headgear, and digital albums by Kings of Leon.

These one-of-a-kind digital art pieces sparked a collectibles craze, driving some NFT prices into the millions. But like most investment schemes built on hype, the market imploded, leaving many buyers with little more than glorified clip art.

After the dust settled, some observers came to see that despite the uniqueness of non-fungible assets, the more valuable data—especially in the business world—is the fungible kind. While NFTs set their owners apart, giving them claim to an asset no one else in the world had, fungible data brings people together.

One example is a little-known data format called the hexbin. In this Fast Four interview, Esri’s Helen Thompson explains how the hexbin is uniting data scientists and location analysts, and why that could give companies a serious competitive edge.

Watch the video interview or read the transcript below.

Chris Chiappinelli: We’re back with a fascinating WhereNext Fast Four. Glad you could join us. We’re talking today about data. It’s the new oil. It’s the key to all kinds of business value—but only if you know how to make sense of it. Helen Thompson is always making sense of data, and she joins us with a new twist on how to get the most of it. Helen, let’s start with some basics. What’s the situation we’re looking at here?

Helen Thompson: Well, I think, Chris, companies are investing billions in data and analytics because, for them, it’s a real, tangible competitive edge. Now I’ve seen a few challenges with maximizing the value of those investments. And specifically, part of the problem that we’ve noticed is the gap between the data scientists and location analysts. Data scientists have their set of data analysis tools and methods, and the spatial analysts have their own.

Business executives are eager to use AI and certainly apply advanced analytics. But to maximize the value of all of that investment, the first thing they need to do is to solve the data gap.

Chiappinelli: Is that situation starting to change? What’s new here?

Thompson: There’s emerging consensus about how to organize location data. It’s like a lingua franca for data scientists to communicate with those location analysts I’ve just discussed. And it’s a thing called the hexbin.

A hexbin is a fancy name for a global hexagonal grid, a bit like you see on a honeycomb in a beehive. They’re all the same size, so the only thing that changes is the data within them. It’s usually customers, their demographics, consumer trends, things like sales, engagement with their physical locations or their digital assets, like websites, emails, social media.

You might see the consumer spending in one hexagon is 20 percent higher than in all of those that surround it. And we can figure out what’s driving the differences.

Chiappinelli: So you’re starting to talk a little bit about location intelligence here. But how does that all fit in?

Thompson: Much of the data that companies gather and the way they analyze is based on geography. Hexbins are becoming popular with data scientists because it helps them see the trends—things like market attractiveness, site accessibility, how easy is it to get to here from there.

So let me give a practical example. Recently, I was working with an international energy company on their expansion strategy. They have data at different geographic scales and in different systems. And the beauty of hexbins is that it provides consistent mathematical relationships between all of those geographies and all the ways that they collect data.

What they’ve been able to do is finally connect their national sales to their local network of dealers to see how local interactions and sales roll up into a regional and national level. How are things changing over time? And then what’s the real reason why certain regions have different behaviors from others?

Things like market attractiveness, site accessibility, how easy is it to get to here from there, all become much more connected through geography.

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Chiappinelli: So you can start to see the intelligence that’s coming out of this. But what are some of the benefits of that, and that new kind of data?

Thompson: Another example is some work that we’ve done with a major retailer here in the U.S. And the data science team were really mining the CRM data, and they were using ZIP codes. We helped the whole organization invest in a new strategy that basically said, “Let’s break away from these counties, ZIP codes, block groups, and build all of the analysis in this common hexagon framework.”

Working together, they’ve realized a whole new model for the organization that allows them to understand market potential and sales. They can run simulations, look at competitive influence, and see how store location or relocations, new openings, might affect it.

So it’s been transformative for the data scientists who’ve been working with the GIS analysts. They’re talking in that lingua franca. And the hexbin is this common currency, this fungible currency that allows both of them to use it.

Chiappinelli: That’s interesting. We’re going to have to keep an eye on this new data currency, this essentially new business language you’re talking about. Really interesting. Thank you for your time, Helen. Thanks for walking us through that.

Thompson: No problem. Thanks, Chris.

Chiappinelli: If you want to learn a little bit more about hexbins or data strategy, check out the link on the screen or in our article. For the WhereNext Fast Four, I’m Chris Chiappinelli. We’ll see you next time.