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In the mid-2000s, Companies spent large sums of money compiling fans and friends on Social Media, at the end of which they asked, “Now what do we do with all of these followers?” The Content Marketing boom was born. Similarly, the big data buzz has lead to the collection of massive amounts of data. Now with servers filled with numbers, companies are asking, “Now what do we do with all of this data?” The Predictive Analytics boom has started.


To date, Companies have had limited capabilities to leverage their data due to a lack of internal knowledge, limited tools, and prohibitive costs, but corporate capabilities are finally catching up. The Cloud has provided Companies assess to large databases backed by powerful computers at a fraction of what it once cost. The Cloud also means that employees are no longer tied to corporate servers to access their data, they can access it on any device from virtually anywhere in the world.


Now, with better Technology and growing corporate capabilities, the next step for big data is to turn data into knowledge. Data for the sake of data, at best, only produces pretty charts. The reality is that unless we’re using data to make better decisions or take faster action, it is purely an expense. When we can use big data for prediction and automation, big data can become a valuable investment.


Big DataUSE #s, NOT %s


Research has shown that using absolute numbers has a greater impact than using percentages.


In one study done at the University of Oregon, Psychiatrists were consulted on whether or not to release a patient. They were given one of two data points: “Patients similar to Mr. Jones are estimated to have a 20% chance of committing an act of violence,” or “20 out of every 100 patients similar to Mr.Jones are estimated to commit an act of violence.” Only 21% of the psychiatrists who read the first statement refused to discharge the patient, compared with 41% who read the second statement.


Researchers believe that the ease in visualizing 20 patients, versus 20% of patients, which is quite abstract, has a major impact on why people tend to have a greater response to numbers versus percentages. So next time, say “9 out of 10 people…,” instead of “90% of people….”


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