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<\/p>\nwordpress-seo domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home3/retailp1/public_html/wp-includes/functions.php on line 6114mfn-opts domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home3/retailp1/public_html/wp-includes/functions.php on line 6114By Doug Stephens<\/p>\n
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I defy you to find a marketing conference today that doesn\u2019t have at least one track focused on big data analytics. Big data is a very big deal. Yet, despite all the talk and attention, a 2014 study<\/a><\/strong> suggests that almost half of retail executives across categories still don\u2019t fully understand how big data can help them solve business problems.<\/p>\n This understanding-gap is a huge problem if you happen to be the one in the organization attempting to garner consensus on a big data strategy. After all, it\u2019s difficult to build a case for investment and trial when such a high percentage of leadership may not even be able to see the potential payoff.<\/p>\n By the same token, there’s also little sense in spending more time and energy selling your executives on the technical aspects of big data analytics. Does anyone really<\/i> care about the technicalities of petabytes, distributed processing and\u00a0Hadoop\u00a0databases<\/i>? \u00a0Probably not.<\/p>\n However, I do think there’s a way to present the big data opportunity to your business leaders that cuts through the jargon and technicality and brings big data to a level every executive can appreciate and connect to in a very clear and intuitive sense.<\/p>\n It involves sharing two very simple stories.<\/p>\n <\/p>\n <\/p>\n I came across this article by Fast Company contributor\u00a0Farhad Manjoo<\/a><\/strong> and thought it was brilliant. \u00a0Manjoo wrote:<\/p>\n A few years ago, at the Washington Hospital Center, a sprawling urban health-care facility near D.C., the emergency-room doctors noticed a troubling medical mystery common to many hospitals: A large number of patients were returning to the ER, sick again, within just a few weeks of being discharged. Doctors believed that many of these readmissions could have been prevented with better follow-up care, but they had no way to predict which patients were most likely to become ill again. The issue became even more pressing when Medicare announced that it would start penalizing hospitals for patients readmitted in less than 30 days after discharge.<\/i><\/p>\n <\/i>At a loss for answers, the hospital began working with Eric Horvitz a computer scientist (and physician) who works at Microsoft Research. Instead of a team of slavish residents, Horvitz’s main investigative tool is data. He and his colleagues built a system to analyze more than 300,000 ER visits. They looked for correlations among 25,000 variables, including the patients’ medications, vital signs, and doctors.<\/i><\/p>\n In the thicket of information, Horvitz stumbled upon a few intriguing surprises. One was the length of a patient’s stay in the hospital. Horvitz’s data showed a tipping point of 14 hours–if you’re in the ER for longer than that, there’s a good chance you’ll be back. Another red flag was\u00a0fluid. The data showed that any mention of that word on a patient’s medical chart significantly increased the likelihood of readmission. “You look at that and you say, ‘Wow,’ ” Horvitz says. “We don’t know why fluid is so important, but it seems to matter–and it can help doctors take necessary preventative action.”<\/i><\/p>\n <\/i>Horvitz built his findings into a program called the Readmissions Manager, which Microsoft sells as part of its health-care IT suite. It analyzes hospital data to produce a readmissions forecast for each patient, and doctors can tailor follow-up appointments based on the forecast. How much will this reduce costs? Horvitz is formulating clinical trials now to assess the savings. Studies show that 20% of patients released from American hospitals need to be readmitted within 30 days, an inefficiency that costs Medicare $17 billion a year. “There’s just so much data dropped on the floor in health care that we can learn from,” Horvitz says.<\/i><\/p>\n <\/p>\n <\/p>\n Without even knowing your business, I guarantee it\u2019s awash in questions that are every bit as mysterious and inexplicable as Washington Hospital’s readmission problem. \u00a0Questions like; why some of your customers are more profitable than others? \u00a0Why certain products cause a disproportionate percentage of returns? \u00a0Which external factors have the greatest impact on demand for your products? \u00a0And which skills and traits your best employees have in common \u2013 to name just a few.<\/p>\n What would the value be to your business of understanding the root causes, and deep correlations lying behind these sorts of questions? I suspect it could be enormous!<\/p>\n <\/p>\n <\/p>\n You may be surprised to learn that each year in the United States there are 1,638,910 new cases of cancer diagnosed. In turn, 577,190 Americans succumb to cancer-related illnesses\u00a0<\/em>each year\u00a0<\/em>. \u00a0<\/em><\/p>\n So, with those statistics in mind, would it not follow that if we could eradicate all forms of cancer, life expectancy in America would dramatically increase?\u00a0 It seems logical to think so, doesn\u2019t it?<\/em><\/p>\nThe first story<\/b><\/h2>\n
Discovering Invisible Truths<\/b><\/h2>\n
The second story<\/b><\/h2>\n
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