SIPAward Winner Shines Light on Role of Data-Driven Journalism

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"This data-driven story was the result of a five-month effort tracking the political contributions made by senior executives at 39 private equity (PE) firms. The goal was to create an interactive database that would allow our readers to analyze how candidates' voting records and public positions on issues such as financial industry regulation influence campaign contributions from PE professionals."

That paragraph came from the 2017 first-place SIPAward-winning entry in the category of Best Use of Data, by Sam Sutton, senior editor of PE Hub, published by Buyouts Insider, a Simplify Compliance company. The article shows how data is making an impact on the way B2B publishers tell stories today.

Sutton compiled a list of about 1,000 PE executives who hold top positions at firms that belong to the American Investment Council. He ran those names through the database maintained by the Center for Responsive Politics to find every contribution made to a candidate, PAC or Super PAC during the 2016 campaign. (Here's a link to the published story.)

Wrote Sutton: "Once I had a list of candidates and committees that received cash from the private equity industry, I dug through public records, voting records, speeches and public appearances to determine the candidates' stances on three key areas... The end result was a Google Fusion database that allows readers to 'map' candidates by position, and see how the industry contributed to those candidates based on their position."

This seems pretty advanced—and quite worthy of its SIPAward. An article on the site Online Journalism Blog takes a couple steps back in the data journalism world for those just getting started. Asked for his three top tips for journalists who want to begin working on data-driven news stories, Paul Bradshaw, an English journalist and expert in this area, responds:

"Don't start by learning a technique for the sake of it – there are 101 different things you could learn. Instead pick a problem that you face regularly, or a story idea that you have, and let that dictate the sorts of data journalism skills that you learn first."

"Start simple. Learning how to work out the biggest risers or fallers is simple, but really useful, for example. Or learning how to calculate a percentage change. Or learning how to turn granular data into aggregate totals using pivot tables. I cover these skills in my introductory ebook Data Journalism Heist because they're easy to start with and are involved in probably more than half of data journalism stories."

"Remember the story is still about people. Sometimes the data journalism part only takes up 10 minutes and the rest of your time is tracking down case studies or experts. Know when to put the numbers down and pick up the phone. A good chart is useful, but a photo or video of a person affected is equally valuable."

As for the skills that a data journalist needs, Bradshaw recommends:

  • learning how to properly read a spreadsheet
  • working on data visualization and
  • mastering computational thinking—breaking down a problem and taking on each segment logically.

In addition to bolstering your presentation, Bradshaw suggests that data visualization  "can help you find patterns that you won't see in a spreadsheet, and demonstrate them to colleagues succinctly." For assistance, he recommends the tools, and

"Don't focus on what you haven't got – instead focus on what you can do, and build from there," Bradshaw advises.

Sutton agrees on the building part. He writes that, "Going forward, we plan to use this template to track political contributions in future coverage."  

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Ronn Levine began his career as a reporter for The Washington Post and has won numerous writing and publications awards since. Most recently, he spent 12 years at the Newspaper Association of America covering a variety of topics before joining SIPA in 2009 and SIIA in 2013 as editorial director…