One point Howard makes in the intro is that we already have tentative evidence to think that people like data-driven stories, infographics, and exploratory visualizations quite a lot: "Original data and reporting presented with context and a strong narrative remains a powerful, popular combination."
Howard mentions that one of the pieces published in The Upshot yesterday was the most popular story of the day at The New York Times website (see screenshot at the bottom of this post.) This may not be that surprising if you knew about this or this already. Perhaps investing in data analysis, visualization, graphics, and in-depth reporting will pay off, after all.
My favorite quotes from the interview with Scott (bolds are mine):
I think there are some myths about what “programming” means. It doesn’t have to mean a computer science degree and it doesn’t have to mean what Google does. I know journalists who make incredibly complex scrapers for their reporting work who will tell you they don’t know how to program. Really, making tools to automate tasks is what a programmer does. There’s no magic threshold you have to pass between programmer and not-programmer.
I suspect that some newsrooms say they can’t afford to hire newsroom developers when they really mean that their budget priorities lie elsewhere – priorities that are set by a senior leadership whose definition of journalism is pretty traditional and often excludes digital-native forms.
What the Internet added is that it gave us the ability to show to people the actual data and let them look through it for themselves. It’s now possible, through interaction design, to help people navigate their way through a data set just as, through good narrative writing, we’ve always been able to guide people through a complex story.
The change we’re experiencing thanks to the web increases the role of presentation of the data itself, both in great data visualization and in great exploratory graphics like news applications. We can show people “the back of the baseball card” on a large scale.
Look how many people understand — and love — incredibly sophisticated and arcane sports statistics. We ought to be able to trust our readers to understand data in other contexts too.