{"id":17095,"date":"2015-09-07T14:19:53","date_gmt":"2015-09-07T14:19:53","guid":{"rendered":"http:\/\/www.cloudcomputing-news.net\/news\/2015\/sep\/07\/10-ways-big-data-is-revolutionizing-supply-chain-management\/"},"modified":"2015-09-07T14:19:53","modified_gmt":"2015-09-07T14:19:53","slug":"10-ways-big-data-is-revolutionising-supply-chain-management","status":"publish","type":"post","link":"https:\/\/icloud.pe\/blog\/10-ways-big-data-is-revolutionising-supply-chain-management\/","title":{"rendered":"10 ways big data is revolutionising supply chain management"},"content":{"rendered":"<p><em>(c)iStock.com\/\u0421\u0435\u0440\u0433\u0435\u0439 \u0425\u0430\u043a\u0438\u043c\u0443\u043b\u043b\u0438\u043d<\/em><\/p>\n<p>Big data is providing supplier networks with greater data accuracy, clarity, and insights, leading to more contextual intelligence shared across supply chains.<\/p>\n<p>Forward-thinking manufacturers are orchestrating 80% or more of their supplier network activity outside their four walls, using big data and cloud-based technologies to get beyond the constraints of legacy e<span class=\"forbes_entity\">nterprise<\/span> resource planning (ERP) and supply chain m<span class=\"forbes_entity\">anagement<\/span> (SCM) systems. For manufacturers whose <span class=\"forbes_entity\">business<\/span> models are based on rapid product lifecycles and speed, legacy ERP systems are a bottleneck.&nbsp; Designed for delivering order, shipment and transactional data, these systems aren&rsquo;t capable of scaling to meet the challenges supply chains face today.<\/p>\n<p>Choosing to compete on accuracy, speed and quality forces supplier networks to get to a level of contextual intelligence not possible with legacy ERP and SCM systems. While many companies today haven&rsquo;t yet adopted big data into their supply chain operations, these ten factors taken together will be the catalyst that get many moving on their journey.<\/p>\n<p>The ten ways big data is revolutionising supply chain <span class=\"forbes_entity\">management<\/span> include:<\/p>\n<ul>\n<li><strong>The scale, scope and depth of data supply chains are generating today is accelerating, providing ample data sets to drive contextual intelligence.<\/strong> The following graphic provides an overview of 52 different sources of big data that are generated in supply chains Plotting the data sources by variety, volume and velocity by the relative level of structured\/unstructured data, it&rsquo;s clear that the majority of supply chain data is generated outside an <span class=\"forbes_entity\">enterprise<\/span>. Forward-thinking manufacturers are looking at big data as a catalyst for greater collaboration. Source: <a href=\"https:\/\/www.researchgate.net\/profile\/Benny_Tjahjono\/publication\/270506965_BIG_DATA_ANALYTICS_IN_SUPPLY_CHAIN_MANAGEMENT_TRENDS_AND_RELATED_RESEARCH\/links\/54abe07b0cf25c4c472fb56b.pdf\">Big Data Analytics in Supply Chain Management: Trends and Related Research. Presented at 6th International Conference on Operations and Supply Chain Management, Bali, 2014<\/a><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-8820 size-full aligncenter\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/Figure-1-SCM-Data-Volume-Velocity-Variety.jpg\" alt=\"Figure 1 SCM Data Volume Velocity Variety\" width=\"730\" height=\"401\" \/><\/p>\n<ul>\n<li><strong>Enabling more complex supplier networks that focus on knowledge sharing and collaboration as the value-add over just completing transactions.<\/strong>&nbsp; Big data is revolutionising how supplier networks form, grow, proliferate into new markets and mature over time. Transactions aren&rsquo;t the only goal, creating knowledge-sharing networks is, based on the insights gained from big data analytics. The following graphic from <a href=\"http:\/\/d2mtr37y39tpbu.cloudfront.net\/wp-content\/uploads\/2015\/04\/DUP_1048-Business-ecosystems-come-of-age_MASTER_FINAL.pdf\">Business Ecosystems Come Of Age<\/a> (<span class=\"forbes_entity\">Deloitte<\/span> University Press) (free, no opt-in) illustrates the progression of supply chains from networks or webs, where knowledge sharing becomes a priority.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-8824 size-full aligncenter\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/figure-1-big-data-scm1.jpg\" alt=\"figure 1 big data scm\" width=\"730\" height=\"480\" \/><\/p>\n<ul>\n<li><strong>Big data and advanced analytics are being integrated into optimisation tools, demand forecasting, integrated <span class=\"forbes_entity\">business<\/span> planning and supplier collaboration &amp; risk analytics at a quickening pace.<\/strong> These are the top four supply chain capabilities that Delotte found are currently in use form their recent study, <a href=\"http:\/\/www2.deloitte.com\/content\/dam\/Deloitte\/global\/Documents\/Process-and-Operations\/gx-operations-supply-chain-talent-of-the-future-042815.pdf\">Supply Chain Talent of the Future Findings from the 3rd Annual Supply Chain Survey<\/a> (free, no opt-in). Control tower analytics and visualization are also on the roadmaps of supply chain teams currently running big data pilots.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-8823 size-full aligncenter\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/Figure-2-use-of-supply-chain-capabilities.jpg\" alt=\"Figure 2 use of supply chain capabilities\" width=\"730\" height=\"522\" \/><\/p>\n<ul>\n<li><strong>64% of supply chain executives consider big data analytics a disruptive and important technology, setting the foundation for long-term change <span class=\"forbes_entity\">management<\/span> in their organizations.<\/strong>&nbsp; <a href=\"http:\/\/www.scmworld.com\/home\/\">SCM World&rsquo;s<\/a> latest Chief Supply Chain Officer Report provides a prioritisation of the most disruptive technologies for supply chains as defined by the organisations&rsquo; members.&nbsp; The following graphic from the report provides insights into how senior supply chain executives are prioritizing big data analytics over other technologies.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-8826 size-full aligncenter\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/disruptive-tech.jpg\" alt=\"disruptive tech\" width=\"730\" height=\"484\" \/><\/p>\n<ul>\n<li><strong>Using geoanalytics based on big data to merge and optimise delivery networks.<\/strong>&nbsp; The <span class=\"forbes_entity\">Boston Consulting Group<\/span> provides insights into how big data is being put to use in supply chain <span class=\"forbes_entity\">management<\/span> in the article <a href=\"https:\/\/www.bcgperspectives.com\/content\/articles\/technology_making_big_data_work_supply_chain_management\/\">Making Big Data Work: Supply Chain Management<\/a> (free, opt-in). One of the examples provided is how the merger of two delivery networks was orchestrated and optimized using geoanalytics. The following graphic is from the article. Combining geoanalytics and big data sets could drastically reduce cable TV tech wait times and driving up service accuracy, fixing one of the most well-known service challenges of companies in that <span class=\"forbes_entity\">business<\/span>.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-8821 size-full aligncenter\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/Figure-4-geoanalytics.jpg\" alt=\"Figure 4 geoanalytics\" width=\"730\" height=\"494\" \/><\/p>\n<ul>\n<li><strong>Big data is having an impact on organizations&rsquo; reaction time to supply chain issues (41%), increased supply chain efficiency of 10% or greater (36%), and greater integration across the supply chain (36%).<\/strong> The <a href=\"https:\/\/acnprod.accenture.com\/_acnmedia\/Accenture\/Conversion-Assets\/DotCom\/Documents\/Global\/PDF\/Dualpub_2\/Accenture-Global-Operations-Megatrends-Study-Big-Data-Analytics.pdf#zoom=50\">Big Data Analytics in Supply Chain: Hype or Here to Stay? Accenture Global Operations Megatrends Study<\/a> found that companies are achieving significant results using big data analytics to improve supply chain performance and gain greater contextual intelligence.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-8819 size-full aligncenter\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/figure-6-big-data.jpg\" alt=\"figure 6 big data\" width=\"730\" height=\"466\" \/><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><strong>Embedding big data analytics in operations leads to a 4.25x improvement in order-to-cycle delivery times, and a 2.6x improvement in supply chain efficiency of 10% or greater. <\/strong><span class=\"forbes_entity\">Accenture<\/span> found that embedding big data into supply chain operations accelerates supply chain processes a minimum of 1.3x over using big data on an ad hoc basis. Source: &nbsp;&nbsp;<a href=\"https:\/\/acnprod.accenture.com\/_acnmedia\/Accenture\/Conversion-Assets\/DotCom\/Documents\/Global\/PDF\/Dualpub_2\/Accenture-Global-Operations-Megatrends-Study-Big-Data-Analytics.pdf#zoom=50\">Big Data Analytics in Supply Chain: Hype or Here to Stay? Accenture Global Operations Megatrends Study<\/a><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-8818 size-full aligncenter\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/figure-7-big-data.jpg\" alt=\"figure 7 big data\" width=\"730\" height=\"544\" \/><\/p>\n<ul>\n<li><strong>Greater contextual intelligence of how supply chain tactics, strategies and operations are influencing financial objectives.<\/strong>&nbsp; Supply chain visibility often refers to being able to see multiple supplier layers deep into a supply network.&nbsp; It&rsquo;s been my experience that being able to track financial outcomes of supply chain decisions back to financial objectives is attainable, and with big data app integration to financial systems, very effective in industries with rapid inventory turns. Source: <a href=\"http:\/\/go.onenetwork.com\/l\/20522\/2014-04-23\/7wbh1\/20522\/28482\/big_visibility_wp_2014.1.pdf\">Turn Big Data Into Big Visibility.<\/a><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-8817 size-full aligncenter\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/figure-8-traceability.jpg\" alt=\"figure 8 traceability\" width=\"730\" height=\"413\" \/><\/p>\n<ul>\n<li><strong>Traceability and recalls are by nature data-intensive, making big data&rsquo;s contribution potentially significant.<\/strong> Big data has the potential to provide improved traceability performance and reduce the thousands of hours lost just trying to access, integrate and manage product databases that provide data on where products are in the field needing to be recalled or retrofitted.\n<\/li>\n<li><strong>Increasing supplier quality from supplier audit to inbound inspection and final assembly with big data.<\/strong> <span class=\"forbes_entity\">IBM<\/span> has developed a quality early-warning system that detects and then defines a prioritisation framework that isolates quality problem faster than more traditional methods, including Statistical Process Control (SPC). The early-warning system is deployed upstream of suppliers and extends out to products in the field.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p><em>(c)iStock.com\/&#1057;&#1077;&#1088;&#1075;&#1077;&#1081; &#1061;&#1072;&#1082;&#1080;&#1084;&#1091;&#1083;&#1083;&#1080;&#1085;<\/em><\/p>\n<p>Big data is providing supplier networks with greater data accuracy, clarity, and insights, leading to more contextual intelligence shared across supply chains.<\/p>\n<p>Forward-thinking manufacturers are orchestrating 80% or more of their supplier network activity outside their four walls, using big data and cloud-based technologies to get beyond the constraints of legacy e<span>nterprise<\/span> resource planning (ERP) and supply chain m<span>anagement<\/span> (SCM) systems. For manufacturers whose <span>business<\/span> models are based on rapid product lifecycles and speed, legacy ERP systems are a bottleneck.&nbsp; Designed for delivering order, shipment and transactional data, these systems aren&rsquo;t capable of scaling to meet the challenges supply chains face today.<\/p>\n<p>Choosing to compete on accuracy, speed and quality forces supplier networks to get to a level of contextual intelligence not possible with legacy ERP and SCM systems. While many companies today haven&rsquo;t yet adopted big data into their supply chain operations, these ten factors taken together will be the catalyst that get many moving on their journey.<\/p>\n<p>The ten ways big data is revolutionising supply chain <span>management<\/span> include:<\/p>\n<ul>\n<li><strong>The scale, scope and depth of data supply chains are generating today is accelerating, providing ample data sets to drive contextual intelligence.<\/strong> The following graphic provides an overview of 52 different sources of big data that are generated in supply chains Plotting the data sources by variety, volume and velocity by the relative level of structured\/unstructured data, it&rsquo;s clear that the majority of supply chain data is generated outside an <span>enterprise<\/span>. Forward-thinking manufacturers are looking at big data as a catalyst for greater collaboration. Source: <a href=\"https:\/\/www.researchgate.net\/profile\/Benny_Tjahjono\/publication\/270506965_BIG_DATA_ANALYTICS_IN_SUPPLY_CHAIN_MANAGEMENT_TRENDS_AND_RELATED_RESEARCH\/links\/54abe07b0cf25c4c472fb56b.pdf\">Big Data Analytics in Supply Chain Management: Trends and Related Research. Presented at 6th International Conference on Operations and Supply Chain Management, Bali, 2014<\/a><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/Figure-1-SCM-Data-Volume-Velocity-Variety.jpg\" alt=\"Figure 1 SCM Data Volume Velocity Variety\" width=\"730\" height=\"401\"><\/p>\n<ul>\n<li><strong>Enabling more complex supplier networks that focus on knowledge sharing and collaboration as the value-add over just completing transactions.<\/strong>&nbsp; Big data is revolutionising how supplier networks form, grow, proliferate into new markets and mature over time. Transactions aren&rsquo;t the only goal, creating knowledge-sharing networks is, based on the insights gained from big data analytics. The following graphic from <a href=\"http:\/\/d2mtr37y39tpbu.cloudfront.net\/wp-content\/uploads\/2015\/04\/DUP_1048-Business-ecosystems-come-of-age_MASTER_FINAL.pdf\">Business Ecosystems Come Of Age<\/a> (<span>Deloitte<\/span> University Press) (free, no opt-in) illustrates the progression of supply chains from networks or webs, where knowledge sharing becomes a priority.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/figure-1-big-data-scm1.jpg\" alt=\"figure 1 big data scm\" width=\"730\" height=\"480\"><\/p>\n<ul>\n<li><strong>Big data and advanced analytics are being integrated into optimisation tools, demand forecasting, integrated <span>business<\/span> planning and supplier collaboration &amp; risk analytics at a quickening pace.<\/strong> These are the top four supply chain capabilities that Delotte found are currently in use form their recent study, <a href=\"http:\/\/www2.deloitte.com\/content\/dam\/Deloitte\/global\/Documents\/Process-and-Operations\/gx-operations-supply-chain-talent-of-the-future-042815.pdf\">Supply Chain Talent of the Future Findings from the 3rd Annual Supply Chain Survey<\/a> (free, no opt-in). Control tower analytics and visualization are also on the roadmaps of supply chain teams currently running big data pilots.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/Figure-2-use-of-supply-chain-capabilities.jpg\" alt=\"Figure 2 use of supply chain capabilities\" width=\"730\" height=\"522\"><\/p>\n<ul>\n<li><strong>64% of supply chain executives consider big data analytics a disruptive and important technology, setting the foundation for long-term change <span>management<\/span> in their organizations.<\/strong>&nbsp; <a href=\"http:\/\/www.scmworld.com\/home\/\">SCM World&rsquo;s<\/a> latest Chief Supply Chain Officer Report provides a prioritisation of the most disruptive technologies for supply chains as defined by the organisations&rsquo; members.&nbsp; The following graphic from the report provides insights into how senior supply chain executives are prioritizing big data analytics over other technologies.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/disruptive-tech.jpg\" alt=\"disruptive tech\" width=\"730\" height=\"484\"><\/p>\n<ul>\n<li><strong>Using geoanalytics based on big data to merge and optimise delivery networks.<\/strong>&nbsp; The <span>Boston Consulting Group<\/span> provides insights into how big data is being put to use in supply chain <span>management<\/span> in the article <a href=\"https:\/\/www.bcgperspectives.com\/content\/articles\/technology_making_big_data_work_supply_chain_management\/\">Making Big Data Work: Supply Chain Management<\/a> (free, opt-in). One of the examples provided is how the merger of two delivery networks was orchestrated and optimized using geoanalytics. The following graphic is from the article. Combining geoanalytics and big data sets could drastically reduce cable TV tech wait times and driving up service accuracy, fixing one of the most well-known service challenges of companies in that <span>business<\/span>.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/Figure-4-geoanalytics.jpg\" alt=\"Figure 4 geoanalytics\" width=\"730\" height=\"494\"><\/p>\n<ul>\n<li><strong>Big data is having an impact on organizations&rsquo; reaction time to supply chain issues (41%), increased supply chain efficiency of 10% or greater (36%), and greater integration across the supply chain (36%).<\/strong> The <a href=\"https:\/\/acnprod.accenture.com\/_acnmedia\/Accenture\/Conversion-Assets\/DotCom\/Documents\/Global\/PDF\/Dualpub_2\/Accenture-Global-Operations-Megatrends-Study-Big-Data-Analytics.pdf#zoom=50\">Big Data Analytics in Supply Chain: Hype or Here to Stay? Accenture Global Operations Megatrends Study<\/a> found that companies are achieving significant results using big data analytics to improve supply chain performance and gain greater contextual intelligence.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/figure-6-big-data.jpg\" alt=\"figure 6 big data\" width=\"730\" height=\"466\"><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><strong>Embedding big data analytics in operations leads to a 4.25x improvement in order-to-cycle delivery times, and a 2.6x improvement in supply chain efficiency of 10% or greater. <\/strong><span>Accenture<\/span> found that embedding big data into supply chain operations accelerates supply chain processes a minimum of 1.3x over using big data on an ad hoc basis. Source: &nbsp;&nbsp;<a href=\"https:\/\/acnprod.accenture.com\/_acnmedia\/Accenture\/Conversion-Assets\/DotCom\/Documents\/Global\/PDF\/Dualpub_2\/Accenture-Global-Operations-Megatrends-Study-Big-Data-Analytics.pdf#zoom=50\">Big Data Analytics in Supply Chain: Hype or Here to Stay? Accenture Global Operations Megatrends Study<\/a><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/figure-7-big-data.jpg\" alt=\"figure 7 big data\" width=\"730\" height=\"544\"><\/p>\n<ul>\n<li><strong>Greater contextual intelligence of how supply chain tactics, strategies and operations are influencing financial objectives.<\/strong>&nbsp; Supply chain visibility often refers to being able to see multiple supplier layers deep into a supply network.&nbsp; It&rsquo;s been my experience that being able to track financial outcomes of supply chain decisions back to financial objectives is attainable, and with big data app integration to financial systems, very effective in industries with rapid inventory turns. Source: <a href=\"http:\/\/go.onenetwork.com\/l\/20522\/2014-04-23\/7wbh1\/20522\/28482\/big_visibility_wp_2014.1.pdf\">Turn Big Data Into Big Visibility.<\/a><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2015\/07\/figure-8-traceability.jpg\" alt=\"figure 8 traceability\" width=\"730\" height=\"413\"><\/p>\n<ul>\n<li><strong>Traceability and recalls are by nature data-intensive, making big data&rsquo;s contribution potentially significant.<\/strong> Big data has the potential to provide improved traceability performance and reduce the thousands of hours lost just trying to access, integrate and manage product databases that provide data on where products are in the field needing to be recalled or retrofitted.\n<\/li>\n<li><strong>Increasing supplier quality from supplier audit to inbound inspection and final assembly with big data.<\/strong> <span>IBM<\/span> has developed a quality early-warning system that detects and then defines a prioritisation framework that isolates quality problem faster than more traditional methods, including Statistical Process Control (SPC). The early-warning system is deployed upstream of suppliers and extends out to products in the field.<\/li>\n<\/ul>\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-17095","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/17095","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=17095"}],"version-history":[{"count":1,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/17095\/revisions"}],"predecessor-version":[{"id":17096,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/17095\/revisions\/17096"}],"wp:attachment":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/media?parent=17095"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/categories?post=17095"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/tags?post=17095"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}