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Too often companies complete a large data collection project, then when nothing happens wonder what all the fuss was about. 

Here are three concrete actions your business can take to avoid this fate.

Wait

Yes, wait. 

A good mental model for the data is the encyclopedia. Encyclopedias have millions of entries. Generally, you only care about one or two at a time. So it goes with your new data set. It has millions of entries, which track everything your team could think of. At some point in the future you will need some of that data. The catch is you don’t know which part. 

John Wanamaker said: “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” In today’s economy, the quote may well become: “Half the money I spend on data is wasted; the trouble is I don’t know which half.”

Related Article: It's Time to Get Practical About Your Data Management

Reimagine How to Share Data About X

X can be anything from how you display customer journeys to product lifecycles. Is there an area in your operations where decisions are haphazard or ill-informed? Hopefully the new data set provides you the opportunity to dig deeper.

An inventive example of this I observed occurred in a call center. The center transformed the customer data from the multiple screens agents had to wade through to understand the customer’s needs to a single graphical display that instantly provided a picture of the customer’s behaviors and likely wants.

Explore

Have a pet theory about how to improve your business? Now is the time to explore. New data sets are wonderful because they provide opportunities for discovery ahead of the competition. 

A fresh data set is far more exciting for data scientists than an existing one. Chances are the existing data set has been picked over already and the most impactful insights have already been gleaned.

Related Article: Is Your Voice of the Customer Program All Talk and No Action?

Data at Rest Stays at Rest

Collecting data provides a foundation for more informed decisions. However, it is just the foundation. Once collected, the data still needs to be converted to information that can be understood and acted upon.