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Wafflecast: What Waffles Can Tell You about the Weather

By David Ratz

I enjoy learning how organizations, and even journalists, are using data to resolve challenges, reach their customers/audiences and answer complex questions. That’s why a recent article in Popular Science about how the Federal Emergency Management Agency (FEMA) is using Waffle House closures to assess the severity of storm damage caught my attention. But what I found more interesting is the story’s focus on small data.

We hear and talk about Big Data every day that it’s easy to forget small data sets have value too. FEMA Administrator W. Craig Fugate found this to be true while he was working as Florida’s emergency management chief. He discovered that an open or closed Waffle House was a good indication if “an area had electricity, gas, and passable roads.1

The article’s author, Clay Dillow, explained Waffle House is a good indicator of this type of information because its restaurants are located in some of the most natural disaster prone areas of the U.S. “…the chain has 500…locations throughout hurricane zones on the Gulf Coast and Eastern Seaboard as well as hundreds more across the flood-and tornado-prone Midwest.”

On top of that, Waffle House is very serious about keeping its doors open and its waffle irons hot. Dillow writes that the Waffle House “maintains its own fleet of portable generators, operates a mobile command center to assist in disaster recovery, and trains employees in crisis management to ensure that it can resume operations as quickly as possible – often within hours.”

This is a pretty remarkable feat given the type of natural disasters Waffle House restaurants go up against. It’s this commitment to reopen restaurants after a natural disaster that makes its operational status valuable to FEMA. It’s providing the agency with a real-time indicator of severity of storm damage, and how quickly services are being restored.

While the data set being sent to FEMA is small, it provides a clear picture of the type of emergency assistance an area might need. This simplifies the equation for FEMA and reduces the amount of information they have to sort through to make an emergency response decision.

Is it going to be right all the time? It’s not, and Dillow talks about this in the article. However, it’s a great example of how small data sets can be used to help inform decisions. Like its big brother, Big Data, the quality of the data is still king.

How is your organization using small data sets to make decisions?

1Dillow, C. (2013, Nov. 11). How Waffle House Became A Disaster Indicator For FEMA. Retrieved from:   

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