Anyone who has spent more than a few minutes with a three-year-old knows that most conversations inevitably return to one, simple question: why?
Why do dogs have tails?
Why don’t we have tails?
Why are bird tails made of feathers?
Why aren’t dog tails made of feathers?
And on and on and on and on and on…
There are a million different manifestations of the question, but the base instinct is the same — unraveling a chain of logic that isn’t immediately obvious to an outside observer. While the process can be vexing for adults who haven’t needed to think about dog tails and evolution for many years, it’s a vital pattern for sharing knowledge with someone who is new to the planet.
It’s also an invaluable lesson for those of us who work on data issues. Like the adult who just accepts dog tails as a part of life, many in the data world take it as a given that we need ‘more data’ or ‘better data’. The underlying logic of those needs is clear to anyone who works on data issues day in and day out, but it’s not always apparent to data newcomers.
Asking a few rounds of ‘why?’, however, yields important insights: we need better data to understand which children and families are being left behind. We need to know which children and families are being left behind so that we can reach them with the services and protection they deserve.
Digging just a few layers beyond the shorthand call for more or better data is valuable both for data practitioners and for those we hope to convert into data champions.
Inside the data world, it’s crucial for making sure we’re making the right investments. If we can’t provide compelling answers about why we need more, better, or different data — or about how we plan to use those data to change lives — we need to re-examine our investments and our assumptions about what’s really needed.
Outside the data world, explicitly laying out the unspoken chain of logic behind a call for more data is essential for winning over donors, private sector partners, government counterparts and more. Just as a toddler is rightly dissatisfied with ‘because that’s the way it is’ as an answer, all these potential data advocates are un-persuaded by ‘because the experts said so’ answers. They need to hear the more compelling arguments that underlie the call for greater investments in data.
Clearly linking data collection to use and, ultimately, to meaningful impact is the best way to win over new champions to the data cause. It’s also a remarkably effective way of motivating both new and veteran data practitioners.
As 1,600 of those data experts gather at the World Data Forum in Dubai this week, they’d all do well to take an investment lesson from the world’s toddlers: keep asking why, and don’t stop until you get an answer that satisfies you.