The Chicago Tribune investigation, “Judges don’t slow 100 mph speeders,” is a great example of how good journalism can make a difference. (http://bit.ly/aUpLqF) Through their effective data analysis, the Secretary of State Jesse White pledged to ban supervision for extreme speeders. The goal of any reporter is to write stories that lead to positive change, and this reporter’s story does exactly that.

The reporter also combed through the data and picked out the best examples to illustrate the need for reform. Like specifically looking for the fastest citations in the data (Ajay Lodhari and Jaime Villarreal raced along I-94 in Lake County last summer at 150) and showing that they got supervision too. And looking at cases where a driver was cited for going 100 mph more than once. (“Chalum Sangsuvan, who hit 131 mph in his BMW near the I-294/ I-88 interchange on a Saturday afternoon in 2008. He got supervision, despite getting supervision a year earlier for going 94 mph on I-294.”) It was also effective to compare Cook County data to surrounding counties (In Logan County only two people got supervision, in Cook County 66% of triple-digit speeders got supervision).

It was also effective to put faces and stories to the data, which is another good way to illustrate the need for reform. Straight numbers sometimes don’t jump out to readers unless they have a story behind it, someone who was affected by it — such as Mike Donovan, the man whose grandson and daughter were killed by a motorist with a history of supervisions.

I also like how the reporter mentioned parts of the data analysis that were missing or incomplete (“the analysis didn’t include cases where data were incomplete, still pending or that involved tickets issued by other departments”). I believe being up front with the reader is a good thing and makes the case stronger because people cannot question it.

The story layout was also strong. I liked the lead a lot because it made you want to keep reading and find out why these traffic violations were not on their record. However, I did not like that the reporter just randomly placed three stats in the middle of the story instead of weaving them through the story. (“Of the cases of triple-digit speeders with known court outcomes: –Those who drove 100 mph or faster while drunk got their records cleansed 40 percent of the time, with no conviction even for DUI, –Others driving recklessly or erratically at those speeds got supervision more than 60 percent of the time, –For those cited just for speeding that fast, more than 70 percent received supervision.”) I think the reporter should have either given these numbers context and weaved them into the story or put them in a sidebar.

I also think the accompanying graphics could have been stronger. The graphic “High speeds, low conviction rates” could have better illustrated the huge difference between supervisions in Chicagoland and downstate if it was in a pie chart as opposed to a bar chart. Showing 63% of a pie and 23% of a pie I think would be stronger visually than a bar. And in the graphic “Chicagoland’s Top Tickets,” I didn’t like the map. I thought it was unnecessary to show where these incidents occurred on a map, they could have just listed that information with the other information. Yet, I like how it’s laid out with the Supervision stamps because visually it shows shockingly how many supervisions were given.

Overall, I think this article is a strong example of good data analysis and, even more importantly, a great example of how data analysis can make a difference.