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Turning Politics Into Political Science With Big Data

Turning Politics Into Political Science With Big Data

"The most important realization that we made was that it wasn't going to be a huge technology effort that was going to make this happen," said Chris Wegrzyn, director of data architecture at the DNC. "It was going to be about analysts. It's about people who were going to understand the political challenges, understand something about the data, and go in and find answers."

By Dana Gardner E-Commerce Times ECT News Network
10/21/13 5:00 AM PT

It's no secret that Big Data is changing the face of customer analytics, giving organizations new insight into customers' wants and preferences.

A similar phenomenon is going on in the realm of politics.

In the 2012 U.S. national elections, in fact, the Democratic National Committee leveraged Big Data analytics to better understand and predict voter behavior and alliances. Here to shed more light on that effort in this podcast is Chris Wegrzyn, director of data architecture at the DNC.

The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions.


Listen to the podcast (18:30 minutes).

Here are some excerpts.

Dana Gardner: Like a lot of organizations, you had different silos of data and information, and you weren't able to do the analysis properly because of the distributed nature of the data and information. What did you do that allowed you to bring all that data together, and then also get the data assembled to bring out better analysis?

Chris Wegrzyn: In 2008, we received a lot of recognition for being a data-driven campaign and making some great leaps in how we improved efficiency by understanding our organization.

Coming out of that, those of us on the inside were saying this was great, but we have only really skimmed the surface of what we can do. We focused on some sets of data, but they're not connected to what people were doing on our website, what people were doing on social media or what our donors were doing. There were all of these different things, and we werenít looking at them.

Really, we couldn't look at them. We didn't have the staff structure, but we also didn't have the technology platform. It's hard to integrate data and do it in a way that is going to give people reasonable performance. That wasn't available to us in 2008.

So, fast forward to where we were preparing for 2012. We knew that we wanted to be able to look across the organization, rather than at individual isolated things, because we knew that we could be smarter. It's pretty obvious to anybody. It isn't a competitive secret that, if somebody donates to the campaign, they're probably a good supporter. But unless you have those things brought together, you're not necessarily pushing that information out to people so that they can understand.

Gardner: Until the fairly recent past, it wasn't practical, both from a cost and technology perspective, to try to get at all the data. But it has gotten to that point now. So when you are looking at all of the different data that you can bring to bear on a national election, in a big country of hundreds of millions of people, what were some of the issues you faced?

Wegrzyn: We hadn't done it before. We had to figure it out as we were going along. The most important realization that we made was that it wasn't going to be a huge technology effort that was going to make this happen. It was going to be about analysts. That's a really generic term. Maybe it's data scientists or something, but it's about people who were going to understand the political challenges, understand something about the data, and go in and find answers.

We structured our organization around being analyst-centric. We needed to build those tools and platforms, so that they could start working immediately and not wait on us on the technology side to build the best system. It wasn't about building the best system, but it was about getting something where we could prototype rapidly.

Nothing that we did was worth doing if we couldn't get something into somebody's hands in a week and then start refining it. But we had to be able to move very, very quickly, because we were just under a constant time-crunch.

Gardner: The results of your Big Data activities are apparent. As I recall, Governor Romney's campaign, at one point, had a larger budget for media and spent a lot of that. You had a more effective budget with media, and it showed.

Another indication was that on election night, right up until the exit polls were announced, the Republican side didn't seem to know very clearly or accurately what the outcome was going to be. You seemed to have a better sense. So the stakes here are extremely high. Whatís going to be the next chapter for the coming elections, in two, and then four years along the cycle?

Wegrzyn: Thatís a really interesting question, and obviously it's one that I have had to spend a lot of time thinking about. The way that I think about the campaign in 2012 was one giant fancy office tower. We call it the Obama Campaign. When you have problems or decisions that have to be made, that goes up to the top and then back down. Itís all a very controlled process.

We are tipping that tower on its side now for 2014. Instead of having one big organization, we have to try to do this to 50, 100, maybe hundreds of smaller organizations that are going to have conflicting priorities. But the one thing that they have in common now is they saw what we did on the last campaign and they know that that's the future.


Dana Gardner is president and principal analyst at Interarbor Solutions, which tracks trends, delivers forecasts and interprets the competitive landscape of enterprise applications and software infrastructure markets for clients. He also produces BriefingsDirect sponsored podcasts. Follow Dana Gardner on Twitter. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]


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