You’ve no doubt heard the joke. It’s a staple of t-shirts sold all over the Internet:
“I’m an English major.
You do the math.”
And it’s true: Many of us “lit” types look a bit down our noses (when they’re not stuck in books, anyway) at what we perceive as widespread illiteracy. And rightly so: The ability to string together sentences that are coherent, grammatical — dare I say even sonorous? — is arguably more important now than a few decades ago thanks to email and social media and the steady stream of textual content they demand.
Yet the irony of our bias toward words is that we run the risk of overlooking another failing that is often right under our own noses: innumeracy. Or (lest that sound a bit harsh): the state of being somewhat numerically challenged.
Journalists can fall prey to this affliction as surely as English majors. Sure, plenty of j-schools offer stats classes, but many also don’t, as the Columbia Journalism Review pointed out a few years ago (in a commentary that also observed that “statistically untrained journalists are watchdogs without olfactory cells”).
My own experience is that most journalists “get” basic math but become goggle-eyed when presented with reams of data, and undergird a story with a few good data points but choose text reflexively rather than infographics or even bulleted stats to the tell a numerical tale.
Our lukewarm relationship with data could prove a little nettlesome in the years ahead if we don’t catch up.
Consider “big data” and the creeping realization that the era is closing of passive, even innocent, data collection ushered in first by widespread use of computers in the 1980s and then of the Internet in the 1990s and 2000s. Enter sophisticated data application, which examines what data means but also extrapolates it to what it could mean and seeks to predict outcomes.
No journalist better encapsulates big-data reporting than Nate Silver and his FiveThirtyEight blog which synthesized long-standing polls, the power of Internet crowdsourcing and sophisticated statistical modeling to accurately predict two straight presidential elections. Silver’s success prompted the Neiman Journalism Lab to predict a “surge in evidence-based journalism” in 2013 (while also quoting an Obama campaign official’s salty advice to journalists to “f***ing do math.”)
We’ve got to get better at understanding, interpreting and effectively presenting data — for the long-term durability and relevance of media, yes, but also for the general benefit of an informed society as observed by Book Business’ Brian Howard:
“[…] IBM estimates that there are 2.5 quintillion bytes of new information created per day and, without smart approaches to parsing and interpreting that data, we’re prone to focus on the information that tells us what we want to hear and ignore the rest.”
And telling people what they want to hear is anathema to the very mission of journalism, isn’t it?
But is journalism up to the data challenge?
A few thoughts on what we’ve got to do:
Foster a heightened data mentality in our organizations. Hire more data-savvy writers and editors. Develop more data-oriented expert sources. Ask for the data angle at every story that gets filed — what numbers, not just words, spoken and written, support the story? Question and cross-check data sets; strive to rely on multiple data sources.
Get better at how we present data to our audiences. Continue breaking data down until we so thoroughly understand it that our audiences will too. Match with related data, draw inferences, bounce possible conclusions off reputable sources, and weave it all together in a narrative that has as much meaning as text-based reports.
Do this and we may just weather the dawning age of evidence-based journalism.