For the most part, when people think of crunching numbers, they imagine charts and graphs. Today on the podcast, we’re exploring unusual ways to look at—or rather, listen to—data. Sound can sometimes present information with more urgency and clarity than a visualization. We decide to see what would happen if we applied the data sonification technique to some somewhat obscure data sets—including the Cheeseburger Index. Listen in as Matt Kenney describes the creation process and Nick Colas dissects the numbers.

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This podcast has been edited and condensed. A rush transcript is below. Music credit: / Podington Bear


ALLAWALA: I’m Katie Allawala, and this is Foreign Affairs Unedited.

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ALLAWALA: That’s the sound of the economy, or at least one part of it. Today on the podcast, we’re exploring unusual ways to look at—or rather, listen to—data.

For the most part, when people think of crunching numbers, they imagine charts and graphs. But according to Penn State professor Mark Ballora, visualizers need to "open their ears to data." In a 2011 Ted talk, he explained that "we tend to be visually oriented and to underappreciate the contributions other senses give us." But the ears are better at some things than the eyes, he says, particularly when it comes to detecting patterns and dynamic changes.

Data sonification, or non-speech audio to convey data, can be valuable for the visually impaired, but it has wider applications as well. Ballora, for his part, has contributed to a project by with George Smoot, the Nobel prize-winning physicist, and Mickey Hart, the drummer for the Grateful Dead, called Rhythms of the Universe—an exploration of the cosmos.

But there are also more routine examples of data sonification. The Geiger counter, for example, uses the rate of clicking to convey the level of radiation in the immediate vicinity of the device. And everyone is familiar with the sound of sonar, pings that are used to 'echo locate' underwater.

in all these cases, sound can perhaps present information with more urgency and clarity than a visualization. Since this is Foreign Affairs, and we’re not tracking u-boats underwater, we decided to apply the data sonifcation technique to the economy, which is where our first soundclip comes back in.

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ALLAWALA: What you’re hearing there was created by Matt Kenney, who works with Ballora at Penn State. We talked with Kenney to learn more about his process and what that particular sonifcation describes. 

KENNEY: Data sonification is essentially the process of taking data points, and instead of visualizing them on a graph, it's turning them into sound. So if you can imagine a line path going upwards, and you try to imagine it as a sound, it would be a kind of sound like the notes were going up, right? And similarly that's how data sonifications are made.

So, my process is essentially taking data points or taking CSV files or large data sets, designing instruments, and then reading those data sets, and kind of seeing what sounds come out of them or what pitches.

ALLAWALA: In this case, Kenney is using sound to tell us about silver and gold coin sales. Traditionally, interest in coin sales perks up at times of economic and geopolitical malaise. Here, higher pitched rings

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signal monthly silver states and slower pitched rings

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indicate monthly gold sales.

KENNEY: So for the coin data set, originally I wanted to make a sound of maybe like coins dropping on the floor or something along those lines, but that kind of got a little bit harsh as you listen to it over and over again. So I kind of backtracked and went for, kind of... Maybe like taking a gold bar and hitting it; less chaotic, maybe easier to map and understand. So as you listen to the sound, the pitch of the coins goes up with the data, and the speed and intensity also increases; so as the data increases, the speed, pitch, and intensity increases.

ALLAWALA: In fact, in years 2011 and 2013, the sales data sounds almost frantic, which should tell you something about the state of the economy in those years.

We also had Kenney look car inventory. Since Americans prefer to buy their cars from dealers—new and ready to drive off the lot—car dealerships often keep an average of two months of inventory, and stock up or down, based on the state of sales. Car supply is represented by the "wooshing" noise of passing automobiles

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and truck supply takes the form of lower pitched rumbles of truck engines.

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Again, each variable changes based on pitch and frequency. As the inventory for cars and trucks increases, the speed, pitch, and intensity of each instrument increases.

KENNEY: I looked up as vehicle inventory, and for this sonification I wanted to kind of make... Kind of like a fun noise as automobiles pass, and again I matched the speed and pitch and intensity to that, so as more cars are being sold, you'll hear the whooshing sound get faster and louder,

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ALLAWALA: In 2014, truck and car inventories were up. Our last data sonification has to do with inflation. Whatever the reported numbers say, consumer attitudes regarding inflation are anchored in their shopping cart. So it is worth watching the prices of basic foods to determine how far a dollar goes. And that basic food—cheeseburgers.

KENNEY: Oh, yeah, the bacon cheeseburger was a lot of fun. Yeah, I decided to kinda go out on a limb and... So there were three different variables; there was ground beef, the cheese and the bacon. And again, I wanted to make a couple of relatively different sounds for each one.

ALLAWALA: The ground beef, he says, kind of sounds like a spatula slapping the grill.

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KENNEY: The cheese is kinda like this gurgling dripping sound,

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and the bacon is, what hopefully sounds kind of like that static sizzling bacon that you would hear when you're cooking bacon.

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KENNEY: I think that sonification generally is a really fun way to look at data and kind of like explore different data sets. I think it's great to get people initially interested in the data set who may not be interested in these variables or the context and really dive into it. 

ALLAWALA: That was Matt Kenney talking about data sonification. You might have noticed that the economic indicators he was working with were unusual. The reason is that traditional methods for measuring the health of the U.S. economy—for example, new residential construction, manufacturing trade inventory and sales, and residential sales—do not provide a full picture of growth or decline. And so, a number of financial firms have turned to offbeat indicators to fill in the gaps. Convergex is one of them, and it provided Foreign Affairs with the numbers to produce Kenney’s presentations.

COLAS: We do a lot of work in behavioral finance. We do a lot of work in economic indicators, both the standard ones and less standard ones. And we do a lot of work on things like stock valuation, investor psychology.

ALLAWALA: That was Nick Colas from Convergex.

COLAS: So, we look at inflation through a number of different lenses. Of course, we look at the standard measures of inflation. That would be things like the consumer price index, the Producer Price Index, the personal consumption indicators that the Fed looks at very closely. But we try to get to a more existential point which is, "How do US consumers perceive inflation?" And we use indicators like the Bacon Cheeseburger Index, as a way to measure things that people buy on a very regular basis.

ALLAWALA: According to Colas, the data from the Bacon Cheeseburger Inflation Index was surprising.

COLAS: The biggest surprise for us using the Bacon Cheeseburger Inflation Index has been that levels of inflation are declining in that kind of core basket of things that people buy quite frequently at the supermarket. And that has actually informed how people think about inflation. They see inflation as less and less of an issue and, not only does the Bacon Cheeseburger Index show that, but more standard measures like the New York Feds Survey of Consumers, also shows declining inflationary expectations.

ALLAWALA: Convergex also likes to look at new car sales as an indicator of economic health.

COLAS: Well for example, everybody knows that car sales are a very important economic indicator. A car is the second most expensive purchase most households make, behind a house. And so people don't tend to buy a cars when they feel the economy is getting worse, or they're worried about their own job prospects. At the same time, when things are better they do. And we've had a run of very strong car sales over the past couple of years. It's really been one of the bright spots of the economy.

ALLAWALA: Another bright spot, at least for now, with used car prices.

We look at the Used Vehicle Index, put up by Manheim, which is one of the major car auction companies in the US, and it's shown remarkable resilience in used care prices. So not only are new car sales going quite well, but used car demand is quite strong. Now, the data more recently is worrisome because it shows that for the first time a decline of over 1% month to month in used car prices. And after a number of years of strong car demand, it could be that your car demand is about to tail off because used car values are gonna decline.

ALLAWALA: In other words, the auto industry could be a canary in a coal mine.

COLAS: If it does signal the US economy is slowing, and that's a major concern among investors and economists right now. Then obviously emerging markets like China, for example, that export a lot of goods to the US would feel a ripple effect as the US economy slowed, their economy would slow as well.

ALLAWALA: It is important to find the kind of offbeat measures that Convergex studies because the traditional ones seem less and less relevant by the year.

COLAS: Yeah, so for example in the US, we have a traditional measure in economics called productivity, which basically is how many units of GDP do you get for every person in the workforce. And those numbers have been declining and very soft for a number of years. And it's a real conundrum because in the middle of this huge wave of technological growth that we see in the US and all the eventual capital money being put to work in brand new ideas and technology, we're not seeing it in the official productivity data. And there's a huge conundrum and kind of argument between Silicon Valley and economists about how to measure services that are now free, like Google that didn't even exist 20 years ago.

ALLAWALA: Of course, it isn’t always easy to change the way things are measured.

COLAS: Yeah, it's right now the number one debate and it's a very hard one because the official data has a very long track record and economists like to have somebody to plug into a model and back test. And so they're really reluctant to look at things like Google searches as a way to measure some kind of productivity growth. We do use Google Trends, which is a wonderful tool developed by Google that allows you to see how many searches took place for a given search term over time. And so even in our work, we're more productive because Google exists, but as far as how to measure it, it's very tough.

ALLAWALA: You’ve got to cast a broad net, Colas says, because the way economies work is changing.

COLAS: We are in the middle of this transformation from an older traditional based economy which has things that are easy to measure, and you really gotta go further your field if you wanna get the nuances and all the interesting stuff happens in the nuances, that doesn't really happen in the base loads

ALLAWALA: That was Nick Colas from Convergence, and I hope we’ve been able to add a little nuance to the conversation today. We’ll be back in two weeks with another episode. Until then, leave a review, email us at [email protected], and subscribe your friends to the show.