‘Datafication’ Has Limits

I love analyzing data as much as the next guy, but in today's world of over-datafication, even data has its limits.

This is a point I think is worth remembering in this day and age, where seemingly everything needs and should be measured. This is also a conversation among talent management practitioners, especially those in the learning and development space.

Learning leaders want to show their value, and business leaders want to see it. For people used to counting dollars and cents, measurement is a fairly easy concept —  show me how much something costs along with the dollar value of what we got in return as a result. For learning leaders, this is a bit more tricky. And by a bit more tricky, I mean that it's sort of kind of definitely become a huge white unicorn.

Leaders in the learning and development field are absolutely pulling their hair out over how to truly capture the exact, most precise value that their programs are driving toward the business. 

A lot of learning leaders will say they've "got it figured out," and they have some really fancy charts and buzz terms to prove it. These people should be listened to, no doubt. But most talent practitioners still seem befuddled at how to capture talent metrics in a world consumed with big data.

I was reminded of this at an event this week put on by Talent Management's sister publication, Chief Learning Officer. During a panel session during the event, a question was posed: How do you measure learning? The room was abuzz with conversation.

Listening to the talk around me, I noticed many folks seemed equal parts concerned and obsessed with how to translate even the smallest potential learning transaction — one employee sharing an article over social media with another employee — into a data point to be shared with senior leaders. Practitioners want to know not only how to capture and translate that transaction into a data point to be shared later, but also how to capture the exact level of learning gleaned from reading that article and how that learning improved that person's performance to eventually boost the business.

That's definitely ambitious. And also kind of a waste of time and energy. Even if someone were to invent some kind of system to track and measure such a random and obscure event — and, in today's environment, I'm sure there is someone who says they can — it's worth remembering that data isn't perfect. It's just a tool that should be considered among many other, more qualitative (even subjective and opinionated) perspectives that should be thrown into the decision-making pot. 

Do not get me wrong: Data is valuable, and technology has improved our ability to find it, track it and give it value. Data should continue to be a factor in how we explain the world, but using data in most cases is really just a best-guess scenario, with a whole lot of emphasis placed on past events.

Keep that in mind as you obsess over ways to collect data to show your value to the business. Should you try to track the exact level of learning that comes from an article shared on social media? Or should you keep a skeptical eye on the correlation between hot sales streaks and social sharing among your sales team, with the realization that correlation doesn't mean causation?

Sometimes not everything should or can be measured. And that's OK.