The new Data Era has arrived! And like any new shiny thing, with it comes with acclaimed hope and slick promises. Finally, all these new training datapoints will point us and our learners in the best direction, right?

Truth is always less glossy than the sales brochure.

No matter how we parse or present all our learning data, it can't tell us where we should go. That part is still up to us—for better or worse. If used well, the new bounty of information can help us better describe where we are and where we want to go.

Is this important?

Well, it is if you say it is.

Data can show us what happened in the past. Though it can't say why anything happened. We must overlay our values to give our data any value. We say what matters and why.

When we tell stories with data, we're curating it. We are selecting certain elements that we believe are relevant highlight, and glossing over other things that we feel don't count as much. The data itself is agnostic. Because data doesn't tell us what to do, it can't tell us which stories are worth telling—and it won’t relieve us of responsibility for making hard decisions.

We can use data to better express what matters to us, and our vision of the future

There is plenty of activity these days around machine learning, artificial intelligence, algorithms, decision engines, etc., and I for one am very happy to see it! Let us use all the tools at our disposal to better guide our success. Let us use data to differentiate what we said we wanted to do from what we actually did do. Let us better predict some of the familiar behavioral pitfalls ahead based on the ones behind us.

There is much to learn, many illusions to shatter. As much as we let it, our data supports us on this upending adventure.

So do you need more data?

That depends on the decision being made, and who is making it.

If you already know there are some seriously flawed actions in progress right now under your watch, and you're confident you know what needs to happen next to address this, then you clearly already know where to go. Don't distract yourself with quantifying anything. Roll up your sleeves and fix it! You'll learn plenty of real-world lessons on this journey that will teach you much more than formalized datasets ever could.

If you work with people who will go with their gut—people for whom no amount of evidence will change their approach—then they will tell you that they already know where to go. Data can help power a path in that direction, but data is definitely the wrong tool to influence choices about the destination they’ve set. Gut-based decision makers won't care about your data; they'll blindly insist that they know better. Data that supports their decision may be welcomed but anything else is merely a nuisance to them. If we present it, we run the risk of being seen as an obstacle to their impending progress.

Data is simply a map

If we aren't clear on what the goal state is or where we are in relationship to it, then having more data is kind of like saying:

“Here’s a map. Now I know you don’t know where you are or where your destination is or which end is up on this thing. But hey, you have a map,’re good, right?”

Would you feel ready to chart your path? Of course not, you wouldn't even know to stop if you happened to reach the goal! No amount of optimization or efficiency or mounds of additional datapoints make up for the fact that you’re still missing the key pieces of information that matter the most.

Data is like that. Good data gives us better ways to see ourselves and orient to our surroundings. Great data shows us things we would never be able to observe otherwise, and helps us make more informed choices. Yet they are still very much our choices. There will always be risk in every decision we make; data provides no insurance and no guarantees.

Fortunately, we don’t need certainty. We just need to power better decisions for less than the cost of the outcomes, and that means knowing what is most important to the unique needs of your organization.

When we have an important business decision to make and decision makers who seek data to help them decide, then by all means, it is time to gather more data! At that point the question becomes how little data is needed to get the decider to a decision. This is far easier to capture and parse than all the things we might maybe someday want to know.

First decide what matters, then choose what counts and how best to count it

And those people who trusted their gut? They could be stubborn or ignorant—or they might just be on to something.

Do you really need more data to come to a decision?

Well, you do if you say you do.

...After all, it's your call to make.

From the editor: Want more?

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