{"id":5548,"date":"2015-06-17T09:00:06","date_gmt":"2015-06-17T09:00:06","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=5548"},"modified":"2015-06-15T14:37:15","modified_gmt":"2015-06-15T14:37:15","slug":"mitigating-risk-with-predictive-modeling-061715","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/mitigating-risk-with-predictive-modeling-061715\/5548\/","title":{"rendered":"Mitigating Risk with Predictive Modeling"},"content":{"rendered":"One of most effective risk management philosophies is to work smarter, not harder, implementing holistic tools, such as predictive analytics to ensure it is minimized. More often than not, companies implement blanketed management programs, applying the same strategies to all employees regardless of performance. With this approach, employers waste time and effort focusing on employees who are not at risk, leaving room for at-risk employees to go unnoticed. On an opposing front, many companies use the \u201csqueaky wheel\u201d approach, diverting all of their attention to employees that actively demonstrate troublesome behaviors. While this approach targets a greater amount <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/mitigating-risk-with-predictive-modeling-061715\/5548\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>One of most effective risk management philosophies is to work smarter, not harder, implementing holistic tools, such as predictive analytics to ensure it is minimized. More often than not, companies implement blanketed management programs, applying the same strategies to all employees regardless of performance. With this approach, employers waste time and effort focusing on employees [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11],"tags":[],"class_list":["post-5548","post","type-post","status-publish","format-standard","hentry","category-industry-news"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/5548","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\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=5548"}],"version-history":[{"count":2,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/5548\/revisions"}],"predecessor-version":[{"id":5550,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/5548\/revisions\/5550"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=5548"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=5548"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=5548"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}