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Business Models for the Data Economy by Ken Gleason, Q. Ethan McCallum

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Business Models for the Data Economy

Whether you call it Big Data, data science, or simply analytics, modern businesses see data as a gold mine. Sometimes they already have this data in hand and understand that it is central to their activities. Other times, they uncover new data that fills a perceived gap, or seemingly “useless” data generated by other processes. Whatever the case, there is certainly value in using data to advance your business.

Few businesses would pass up an opportunity to predict future events, better understand their clients, or otherwise improve their standing. Still, many of these same companies fail to realize they even have rich sources of data, much less how to capitalize on them. Unaware of the opportunities, they unwittingly leave money on the table.

Other businesses may fall into an explore/exploit imbalance in their attempts to monetize their data: they invest lots of energy looking for a profitable idea and become very risk averse once they stumble onto the first one one that works. They use only that one idea (exploit) and fail to look for others that may be equally if not more profitable (explore).[1]

We hope this paper will inspire ideas if you’re in the first camp or encourage more exploration if you’re part of the second so you can build a broad and balanced portfolio of techniques. While there are myriad ways to make data profitable, they are all rooted in the core strategies we present in the following list.

Collect/Supply
Gather and sell raw ...

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