You can use data to boost your career. Here’s how. | Neil Irwin | Big Think

So one of the most fundamental shifts which happened in technology and how big organizations work is that we have more and more data about what we do. Some of that is simple forms. I mentioned I work in the media industry; I know how many people read each of my stories and how long they spent on it and how they found it. But I think it applies in a much bigger way.

I found a fascinating example of how data can be used to make a team more effective and make an organization more effective at Microsoft. This is this big successful company, and there was a unit on it that makes devices, so surface tablets and Xboxes, things like that. There are 700 people in this unit, and they had a problem. The problem was this: the surveys showed that employees in this business unit were not happy. They had low scores on work-life balance, and the head of this unit, a guy named Brett Ostrom, was really worried because these were hard people to hire, hard people to replace if they were to quit. He was afraid all the success they had might go out the window if people were so unhappy they started to leave this team.

So he worked with a team at Microsoft that does data analytics and tries to understand people and how they're operating using big data sources. What they found was kind of a surprising result. The real reason these people were unhappy was not because they had to make a lot of late-night phone calls to Asia because of international supply chains. It wasn't because a few bosses were really mean or really demanding or hard-charging. The problem was across this team; they were spending way too much time in big meetings. They spent an average of 27 hours a week in large meetings, and that meant these workers had no time during the workday to get individual work done.

So you know, we all know how this works. You end up doing that and catching up on that work on the evenings and on the weekends. That's why they had low work-life balance. Because they had these analytical tools of crunching millions of emails, calendar entries, things like that, they were able to discern this information that has allowed this team to be more effective. Data was the reason essentially; you can use data to be your own career coach.

I think the key is understanding what are the real metrics that matter in your organization, your line of work, and being just an avid student of them. Understanding the moving pieces, understanding what correlates with what. You know, often beer companies will have people who can help you understand this within an organization, but I think being an avid consumer of the information available to you is the real key to taking advantage of the resources that larger organizations just have to offer.

There is a risk if you focus too much on data and analytics that you could get in your own head and be too focused on the numbers rather than the underlying performance of whatever you're trying to do, whether that's sales or product development or whatever it might be. But I think the key is when you use these tools over and over again, it's not so much about overthinking everything you do. It becomes about an underlying way of thinking; an underlying baseline for understanding the world around you and what's likely to create good results in your field.

Look, data alone isn't insight. You can't just look at numbers and decide everything you're gonna do based only on numbers. It's really—there's an art to interpreting those numbers, and you really have to apply the logic that you can understand from the world around you to make sure those numbers are not leading you in a bad direction.

So for example, in my own industry, in the media business, if everybody just tried to write the stories that would get the most traffic, we might get more traffic and more clicks, but we wouldn't necessarily be building a more successful organization. Because there'd be a lot of kind of trashy, silly, frivolous things that people don't want to pay for a subscription to.

And I think there's equivalents of that in a lot of fields where you don't want to just solve for whatever happens to be on your dashboard.