{"id":2716,"date":"2013-11-26T14:47:00","date_gmt":"2013-11-26T14:47:00","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=2716"},"modified":"2021-01-13T08:39:18","modified_gmt":"2021-01-13T13:39:18","slug":"the-privacy-pickle-hewlett-packards-prediction-of-employee-behavior","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/the-privacy-pickle-hewlett-packards-prediction-of-employee-behavior\/2716\/","title":{"rendered":"The Privacy Pickle: Hewlett-Packard\u2019s Prediction of Employee Behavior"},"content":{"rendered":"Hewlett-Packard (HP) knows there are two sides to every coin. The company has achieved new power by predicting employee behavior, a profitable practice that may raise eyebrows among some of its staff. HP tags its more than 330,000 workers with a so-called Flight Risk score. This simple number foretells whether each individual is likely to leave his or her job. With the advent of predictive analytics, organizations gain power by predicting potent yet \u2013 in some cases \u2013 sensitive insights about individuals. These predictions are derived from existing data, almost as if creating new information out of thin <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/the-privacy-pickle-hewlett-packards-prediction-of-employee-behavior\/2716\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>Hewlett-Packard (HP) knows there are two sides to every coin. The company has achieved new power by predicting employee behavior, a profitable practice that may raise eyebrows among some of its staff. HP tags its more than 330,000 workers with a so-called Flight Risk score. This simple number foretells whether each individual is likely to [&hellip;]<\/p>\n","protected":false},"author":83,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11],"tags":[228,8],"class_list":["post-2716","post","type-post","status-publish","format-standard","hentry","category-industry-news","tag-hewlett-packard","tag-predictive-analytics"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2716","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/83"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=2716"}],"version-history":[{"count":7,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2716\/revisions"}],"predecessor-version":[{"id":11919,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2716\/revisions\/11919"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=2716"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=2716"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=2716"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}