{"id":28629,"date":"2017-04-03T10:16:06","date_gmt":"2017-04-03T10:16:06","guid":{"rendered":"https:\/\/www.cloudcomputing-news.net\/news\/2017\/apr\/03\/machine-learning-is-the-new-proving-ground-for-competitive-advantage\/"},"modified":"2017-04-03T10:16:06","modified_gmt":"2017-04-03T10:16:06","slug":"why-machine-learning-is-the-new-proving-ground-for-competitive-advantage","status":"publish","type":"post","link":"https:\/\/icloud.pe\/blog\/why-machine-learning-is-the-new-proving-ground-for-competitive-advantage\/","title":{"rendered":"Why machine learning is the new proving ground for competitive advantage"},"content":{"rendered":"<p><img decoding=\"async\" src=\"http:\/\/www.cloudcomputing-news.net\/media\/iStock-175169608_1.jpg\"><\/p>\n<ul>\n<li>50% of organisations are planning to use machine learning to better understand customers in 2017.<\/li>\n<li>48% are planning to use machine learning to gain greater competitive advantage.<\/li>\n<li>Top future applications of machine learning include automated agents\/bots (42%), predictive planning (41%), sales &amp; marketing targeting (37%), and smart assistants (37%).<\/li>\n<\/ul>\n<p>These and many other insights are from a recent survey completed by <a href=\"https:\/\/www.technologyreview.com\/profile\/mit-technology-review-custom\/\" >MIT Technology Review Custom<\/a> and <a href=\"https:\/\/cloud.google.com\/\" >Google Cloud<\/a>, <a href=\"https:\/\/s3.amazonaws.com\/files.technologyreview.com\/whitepapers\/MITTR_GoogleforWork_Survey.pdf\" >Machine Learning: The New Proving Ground for Competitive Advantage<\/a> (PDF, no opt-in, 10 pp.). 375 qualified respondents participated in the study, representing a variety of industries, with the majority being from technology-related organisations (43%). Business services (13%) and financial services (10%) respondents are also included in the study.&nbsp; <a href=\"https:\/\/s3.amazonaws.com\/files.technologyreview.com\/whitepapers\/MITTR_GoogleforWork_Survey.pdf\" >Please see page 2 of the study<\/a> for additional details on the methodology.<\/p>\n<p>Key insights include the following:<\/p>\n<ul>\n<li><strong>50% of those adopting machine learning are seeking more extensive data analysis and insights into how they can improve their core businesses.<\/strong>&nbsp;46% are seeking greater competitive advantage, and 45% are looking for faster data analysis and speed of insight. 44% are looking at how they can use machine learning to gain enhanced R&amp;D capabilities leading to next-generation products.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-12142 size-full\" src=\"https:\/\/i2.wp.com\/blogs.forbes.com\/louiscolumbus\/files\/2017\/03\/Seeking-to-gain-from-ML.jpg\" alt=\"If your organization is currently using ML, what are you seeking to gain?*\" width=\"954\" height=\"477\" \/><\/p>\n<h3 class=\"wp-caption-text\">If your organisation is currently using ML, what are you seeking to gain?<\/h3>\n<ul>\n<li><strong>In organisations now using machine learning, 45% have gained more extensive data analysis and insights. <\/strong>Just over a third (35%) have attained faster data analysis and increased the speed of insight, in addition to enhancing R&amp;D capabilities for next-generation products. The following graphic compares the benefits organizations who have adopted machine learning have gained. One of the primary factors enabling machine learning&rsquo;s full potential is service oriented frameworks that are synchronous by design, consuming data in real-time without having to move data.&nbsp;<a href=\"https:\/\/enosix.com\/\" >enosiX<\/a> is quickly emerging as a leader in this area, specializing in synchronous real-time Salesforce and SAP integration that enables companies to gain greater insights, intelligence, and deliver measurable results.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-12145\" src=\"https:\/\/i0.wp.com\/blogs.forbes.com\/louiscolumbus\/files\/2017\/03\/gained-from-ML.jpg\" alt=\"your organization is currently using machine learning, what have you actually gained?\" width=\"1018\" height=\"479\" \/><\/p>\n<h3 class=\"wp-caption-text\">If your organisation is currently using machine learning, what have you actually gained?<\/h3>\n<ul>\n<li><strong>26% of organisations adopting machine learning are committing more than 15% of their budgets to initiatives in this area.<\/strong>&nbsp;79% of all organisations interviewed are investing in machine learning initiatives today. The following graphic shows the distribution of IT budgets allocated to machine learning during the study&rsquo;s timeframe of late 2016 and 2017 planning.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-12147\" src=\"https:\/\/i0.wp.com\/blogs.forbes.com\/louiscolumbus\/files\/2017\/03\/IT-Budget-dedicated-to-ML.jpg\" alt=\"What part of your IT budget for 2017 is earmarked for machine learning?\" width=\"953\" height=\"360\" \/><\/p>\n<h3 class=\"wp-caption-text\">What part of your IT budget for 2017 is earmarked for machine learning?<strong>&nbsp;<\/strong><\/h3>\n<ul>\n<li><strong>Half of the organisations (50%) planning to use machine learning to better understand customers in 2017.<\/strong>&nbsp;48% are adopting machine learning to gain a greater competitive advantage, and 45% are looking to gain more extensive data analysis and data insights. The following graphic compares the benefits organisations adopting machine learning are seeking now.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-12148\" src=\"https:\/\/i2.wp.com\/blogs.forbes.com\/louiscolumbus\/files\/2017\/03\/customers-machine-learning.jpg\" alt=\"If your organization is planning to use machine learning, what benefits are you seeking?\" width=\"1039\" height=\"519\" \/><\/p>\n<h3 class=\"wp-caption-text\">If your organisation is planning to use machine learning, what benefits are you seeking?<\/h3>\n<ul>\n<li><strong>Natural language processing (NLP) (49%), text classification and mining<\/strong><strong>(47%), emotion\/behaviour analysis (47%) and image recognition, classification, and tagging (43%) are the top four projects where machine learning is in use today.<\/strong>&nbsp; Additional projects now underway include recommendations (42%), personalisation (41%), data security (40%), risk analysis (41%), online search (41%) and localisation and mapping (39%). Top future uses of machine learning include automated agents\/bots (42%), predictive planning (41%), sales &amp; marketing targeting (37%), and smart assistants (37%).<\/li>\n<\/ul>\n<ul>\n<li><strong>60% of respondents have already implemented a machine learning strategy and committed to ongoing investment in initiatives.<\/strong>&nbsp;18% have planned to implement a machine learning strategy in the next 12 to 24 months. Of the 60% of respondent companies who have implemented machine learning initiatives, 33% are in the early stages of their strategies, testing use cases. 28% consider their machine learning strategies as mature with between one and five use cases or initiatives ongoing today.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>50% of organisations are planning to use machine learning to better understand customers in 2017.<br \/>\n48% are planning to use machine learning to gain greater competitive advantage.<br \/>\nTop future applications of machine learning include automated agents\/bots&#8230;<\/p>\n","protected":false},"author":56,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-28629","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/28629","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/users\/56"}],"replies":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/comments?post=28629"}],"version-history":[{"count":1,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/28629\/revisions"}],"predecessor-version":[{"id":28630,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/28629\/revisions\/28630"}],"wp:attachment":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/media?parent=28629"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/categories?post=28629"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/tags?post=28629"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}