From the course: Data Visualization: A Lesson and Listen Series

Lesson: Data in public policy

From the course: Data Visualization: A Lesson and Listen Series

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Lesson: Data in public policy

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(lively music) - From the dawn of time, groups of people have had to make collective decisions. And for most of that time, those decisions were based on instinct or tradition. Now, we have endless amounts of data that's supposed to help us do this more effectively than ever. But for data to help drive public policy, it has to be collected, analyzed, and communicated to policy makers, and those policy makers have to listen to the evidence and make clear decisions based on that evidence, right? Most governments collect and analyze endless amounts of information about just about everything in society. The decision-making part that could be argued hasn't quite lived up yet to the ideal. So let's talk about data-driven decision-making. Human beings are generally speaking terrible at it. This might be difficult for you to hear, but we know from decades of psychological research that we aren't very good at reasoning. Right now you are struggling to make sense of this data-driven statement, but it's true. You and I are bad at this. Why? Well, as it turns out, rather than actually reasoning and making sound evidence-driven decisions, we tend to make decisions and then use our reasoning to justify why the decision we've made is the right one. So we use the data after the fact to convince ourselves that we did the right thing. In other words, we latch onto whatever data makes sense to back up the decision that we want to make. This isn't really a surprise. We see people in politics doing this all the time. Not us, right? Just the other guys on the other side of the table, right? No, no, no. You do it too. So what do we do about it? Well, when the decision is easy, you don't need to do much. If all the weather models show a hurricane is coming straight at your house, you evacuate, right? Simple, we're not usually idiots when faced with overwhelming evidence. The difficulty comes when it's subtler than that. All you can do as the decision maker, is to acknowledge that this isn't a strength of yours, and to do your best to be objective, to consider the evidence in full, and to be hyper conscious of your own decision-making process, asking yourself if you're simply justifying your own decisions after the fact, or if you're really making a data-driven decision. That awareness of the problem is half the battle. Now, if you're a data worker trying to help others make better decisions based on evidence, you need to work very hard at providing that evidence in as clear and concise a way as possible. The easier it is for your stakeholders to see the key information, the more time and energy they'll have to spend thinking about the point and making smart decisions rather than struggling to understand your evidence. So this brings us back to what I'm always advocating, tell flowing narratives, illustrate your data clearly, and align everything you're doing with decision-making in mind. Next, you don't want to miss my conversation with DJ Patil, the former U.S. Chief Data Scientist under President Obama. He knows a thing or two about data-driven policymaking, and so much more. Join us.

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