Why every municipal Chief Data Officer should be a journalist first
By: Sam Edelstein
Tags: Data Storytelling, Data Science, Data Journalism, Chief Data Officer

Photo by Roman Kraft on Unsplash

I don’t really mean that, but it makes for a catchy headline. One of the most powerful things about municipal Chief Data Officers is the breadth of experiences and backgrounds that exist. Some have data science backgrounds, other policy, or history, or public administration, or economics, or something else entirely. But, I originally wanted to be a newspaper journalist, and though that didn’t become my career, I’ve used the skills I learned during my time writing for a couple of newspapers constantly in my Chief Data Officer life.

To be clear, I was never close to being a Pulitzer Prize journalist, I wrote for both my college and hometown newspapers during my undergrad years.

Ask tough questions

As a journalist, you have to ask a lot of questions to truly understand the full story. Sometimes those questions can be uncomfortable to ask, and the way those questions are answered can be challenging to hear as well. At the same time, in order to get the interviews and the quotes needed to file a story, you have to approach the interviewee in a way that builds trust.

Similarly for a Chief Data Officer, the data that a municipality holds is often challenging to understand. You may need to spend hours looking at a dataset, then go to actually do the work with the department that generates the data (we’ve filled potholes, picked up trash, tagged along for code violation inspections, and more), and then ask a lot of questions just to accurately count how many things happened on one day. Once you have a sense for what the data say, you will likely uncover some strange results that potentially show a bottleneck or inefficiency. Then you have to ask why the data looks the way it does. The answer may complete the story, but it also might be threatening to uncover. These are people you’ll continue working with in the future and will likely need to ask more questions, so every step requires judgment and tact.

If you aren’t willing to be creative and ask lots of questions, even the tough ones, then you probably aren’t cut out for the job.

Big picture and focused view

A good newspaper story will generally highlight a specific example of a problem as well as the broader reason for why that specific problem matters. Oftentimes, an article will start out telling a story about one person who had a bad experience somewhere, and then by the end of the piece the reader will have learned about why that problem is important for more than just that specific person. Being able to write about the big picture and more specific focus area requires a grasp of the overall topic and a need to talk to a lot of different people, gathering data to inform the article.

As a Chief Data Officer, often times the most meaningful way to convince someone about a project’s findings isn’t done by sharing a bunch of statistics, but instead by targeting a very specific piece of information. Maybe one neighborhood is particularly impacted, or maybe you can relate the overall findings to how someone might see the impact on their street or on their commute to work. Then, once you’ve captured their attention, you can talk about the larger issues and the overall findings that encompass the city as a whole. Combining the two gets the attention that is needed to push for considerations around a policy change.

Put together a story

If a journalist can’t tell a good story, then people won’t read their articles. A catchy headline, a well-written lede, interesting interviews, and maybe a good picture all make for a quality article.

Similarly, a Chief Data Officer needs to tell a good story with high quality data visualizations. Even if an analysis requires complex statistical analyses, ultimately the presentation of the findings needs to be distilled in a way that is understandable. Generally, outside of the data office, no one will care if the analysis was done in Excel or Python or using a linear regression or deep learning. The assumptions, findings, and clear recommendations are what matters.

Understanding the limitations

Any journalist should attempt to report objectively and if a piece of information is not available, that should be reported, too. When a mistake is made in reporting, the journalist or newspaper should acknowledge that mistake and issue a correction.

One of the most common challenges in dealing with municipal data is that often times data is missing. Potholes may get reported to the City so they can be fixed, but they are not reported equitably. For a number of reasons, people in different neighborhoods call the City to complain at different rates. If a Chief Data Officer was asked to manage a project predicting where potholes would appear next year so the Department of Public Works could better budget for materials and staffing, it would be irresponsible to only build a model based on historical pothole complaints. Certain neighborhoods would be ignored. Just as a journalist should understand where information is unavailable, so should a Chief Data Officer. The final deliverable on the pothole project example would either include a large assumption about who calls in complaints, or maybe it would require some new data collection from neighborhoods that have historically under-reported potholes. Also, when a mistake happens, it needs to be acknowledged immediately and fixed, or the analysis should be retracted.

Push for transparency, with some limitations

Ultimately a journalist’s job is to report on the facts. They oftentimes will expose information that may uncover a troubling reality, but it is in an effort to hold people accountable and expose the truth. There can be limitations — sometimes information may be held back especially if the newsworthiness is questionable, particularly when compared to the harm it may bring.

For a municipal Chief Data Officer, making data more available in the public realm is a key tenet of the job. Open data is useful both for internal staff and for the public. It also can hold city staff and processes to account. But there are limitations. If a dataset is released that includes information about someone who paid a parking fine late once, and now that information is online and searchable forever, does that have enough value to balance against the harm it may bring to the person? It might depend on the person, but a Chief Data Officer will need to make a judgment on issues like this, with an eye toward transparency, but and understanding of appropriate limitations.

Conclusion

During my time as Chief Data Officer in Syracuse, I’ve always enjoyed watching the local government reporters do their work. I think back to my time as a newspaper reporter often in this job — I do think the two have a lot of similarities. I don’t know how many other Chief Data Officers, or others working in the data field have any background in journalism, but if you do, I’d be interested to hear if you agree with what I’ve written!