"Data and visual stories are pretty consistently among our most saved and forwarded content," Emily Laermer, managing editor for Ignites at Money-Media, told us at SIPA 2019 in June in a session titled Numbers Drive Engagement: Telling Compelling Stories Using Data.
"In the most basic sense, data stories are ones that just have a ton of information. So they can be generated from a huge spreadsheet or Excel file. But they don't necessarily have to be numbers driven. They can be stories that have a lot of facts. So for example, new rules and regulations are great data stories. The first story I worked on at Ignites required that I read a 400-page rule on mutual fund regulation and how the funds were going to have to change their reporting. That's a data story."
The spreadsheets caught my eye. In telling about his reporting using data for The New York Times, Reed Abelson, a health and science reporter, wrote this:
"In a recent article, I used data from researchers at the University of California, Berkeley, to show how hospital mergers had helped lead to higher prices in various communities. And I created my own spreadsheet to look closely at the experience in a single state. Being comfortable with data and spreadsheets allows me to ask better questions about researchers' studies. Spreadsheets also provide a way of organizing sources, articles and research, as well as creating a timeline of events. By putting information in a spreadsheet, you can quickly access it, and share it with other reporters.
Here are more tips on building a data culture:
Make sure the proper tools are acquired.
Unsilo—open the conversation up with other relevant departments (graphics, tech, etc.).
Make sure that data people are involved as early in the content process as possible.
Encourage your reporters to use data — The team needs to clearly see the value of using data clear and have no barriers to access it.
Support experimentation — Management needs to insist that reporters bring data into their everyday decision making freely and from internal and external sources.
Educate in the use of data — The team needs to receive training on how to use the tools at hand to access data, to make it informative, and to interpret results. (See NYT link below.)
Foster critical thinking — The organization needs to create an environment that would promote questioning biases, distrusting intuition, and displaying a healthy degree of skepticism but would celebrate critical thinking, curiosity, and the deeper desire to question things.
Build data literacy. In a data-driven organization with broad data access, staff will frequently encounter reports, dashboards and analyses, and they may have a chance to analyze data themselves. To do so effectively, they must be sufficiently data literate.
Compile a data dictionary. This is an aspect that trips up many organizations. When you don't have a clear list of metrics and their definitions, people make assumptions — ones that may differ from colleagues. Then the arguments ensue. A business needs to generate a glossary with clear, unambiguous and agreed-upon definitions.
Create broad data access. Having clean, high-quality data, from a central source, and with clear metadata, is ineffective if staff can't access it. Data-driven organizations tend to be very inclusive and provide access wherever the data can help. [This] means assessing the needs of individuals, not just the analysts and key decision makers, but across the whole organization, out to the front-line of operations."
To listen to Laermer's session, click on the SIPA 2019 Presentations page.
Sciforce's blog post is here.
The New York Times extensive data materials are here.
TechCrunch's 5 building blocks of a data-driven culture are here.