Data is a good thing. The more we know about our customers, our website visitors, our business processes, the better off we should be.

But there are problems that come with analytics. If you are working in a data-driven company or are in the process of changing over to a data-driven culture, be sure to avoid these common missteps.

1. The data is wrong.

The first problem that many companies encounter is that the data they are collecting and analyzing is incorrect or incomplete. Often you’ll find that there are gaps in your data, or things don’t match from one system to the next. Then you have to go back and try to piece your data together manually to get a more accurate look at your business.

Sometimes, it is not immediately obvious that the data is wrong. So you start using it to make important business decisions. And you don’t find out until it’s too late that those decisions were made looking at incorrect information.

You need to be very confident that your data is correct and complete before relying on it to make important decisions that will impact the future of your business.

2. You’re using the wrong metrics.

Know what problem you want to solve or what question you want to answer before you start getting too involved with data analysis. It is far too easy to spend a lot of time and energy analyzing one metric or set of metrics when it’s something else entirely that should be commanding your attention.

Just because you are able to see something, doesn’t mean it’s important. Be sure to prioritize your data analysis based on the impact it can have on your business.

3. You’re missing the big picture.

Analysis paralysis is real, people. It’s when you get too bogged down in a vast world of analytics and are unable to pull yourself out and look at your business as a whole.

Sure, it’s easy to think that data will solve all your problems. If we improve this metric and that metric, the business will naturally improve with it. But if you start thinking on a smaller scale, focusing too intently on the numbers, you may find yourself unable to see the forest for the trees.