{"id":30360,"date":"2018-11-12T23:16:17","date_gmt":"2018-11-13T04:16:17","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/"},"modified":"2018-11-12T23:16:17","modified_gmt":"2018-11-13T04:16:17","slug":"machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/","title":{"rendered":"Machine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure"},"content":{"rendered":"

Digitization.<\/em><\/p>\n

This buzzword is boasted by many industrial manufacturing companies today, being showcased in headlines of company webpages and included in company goals for the future. \u00a0An industry survey by Strategy& found that 72% of manufacturing companies said they are dramatically increasing their level of digitization and expect to be able to be ranked as digitally advanced by 2020.[1]<\/a> This demand to offer customized digital capabilities has created a market opportunity. One company that has positioned itself to fill this market void is Schneider Electric.<\/p>\n

Schneider Electric (SU.PA) is a French company headquartered in Rueil-Malmaison, France with over 140,000 employees in 100 countries. Founded in 1836, Schneider Electric was originally focused on steel, heavy industry and transportation equipment, but has evolved to focus on the electrical industry and, more recently, digitization.[2]<\/a> After undertaking a series of strategic acquisitions in the electrical and digital space (including 17 since 2011), Schneider Electric is vertically integrated in the market to provide the software and hardware needed to improve manufacturing operations using machine automation.<\/p>\n

Digitizing manufacturing companies is no easy feat, as there is not an obvious one-size-fits-all approach for the industry. Per Schneider Electric\u2019s 2017 financial statement, it targets four industry segments: Low Voltage, Industrial Automation, Medium Voltage and Secure Power. Table 1<\/strong> provides information from their 2017 finance statements. Each industry segment poses its own set of challenges to break into the market and supply meaningful innovation to its customers.<\/p>\n

Table 1: 2017 Schneider Electric Financial Statement[3]<\/strong><\/a> (revenues in EURm)<\/em><\/p>\n\n\n\n\n\n\n\n\n
Industry Segment<\/em><\/strong><\/td>\n2017 Revenue<\/strong><\/td>\n% 2017 Revenue<\/strong><\/td>\n% 2017 Organic Growth<\/strong><\/td>\n% 2018 Projected Growth<\/strong><\/td>\n2017 EBITA Adjusted Margin<\/strong><\/td>\n<\/tr>\n
Low Voltage (Building)<\/em><\/td>\n10,812<\/td>\n43.7%<\/td>\n4.4%<\/td>\n4.5%<\/td>\n20.6%<\/td>\n<\/tr>\n
Industrial Automation (Industry)<\/em><\/td>\n5,816<\/td>\n23.5%<\/td>\n5.9%<\/td>\n5.1%<\/td>\n17.6%<\/td>\n<\/tr>\n
Medium Voltage (Infrastructure)<\/em><\/td>\n4,500<\/td>\n18.2%<\/td>\n-2.2%<\/td>\n2.9%<\/td>\n10.0%<\/td>\n<\/tr>\n
Secure Power (IT)<\/em><\/td>\n3,615<\/td>\n14.6%<\/td>\n2.1%<\/td>\n3.0%<\/td>\n16.6%<\/td>\n<\/tr>\n
GROUP<\/em><\/td>\n24,743<\/td>\n100%<\/td>\n3.2%<\/td>\n4.1%<\/td>\n4.1%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n

Arguably one of Schneider Electric\u2019s most prominent industries for early trail in digitization is the chemical sector. As part of the Schneider Electric\u2019s industrial automation industry segment, the chemicals sector offers a large capital budget and high R&D intensity (See Figure 1<\/strong>). Given that Schneider Electric has a lasting relationship with chemical companies in providing electrical and hardware components, Schneider Electric has started offering these companies more automation services and capabilities to meet their safety and energy efficiency needs. One example project in Schneider Electric’s portfolio is an upgrade of manual compressors and turbines to an automated control system, while meeting applicable industry safety standards. Revenue from these types of project can be earned through software programs, hardware for installation, and training modular for new equipment.<\/p>\n

Although the chemicals industry serves as a relatively easy market for Schneider Electric to break into, current projects are highly customer-based and difficult to scale. However, performing small customer-based projects has been an essential for Schneider Electric\u2019s ability to trial and refine its technology. The types of projects that Schneider Electric will want to transition to in the chemical market are new capital infrastructure projects. The benefit of these projects is that they are much larger in size and Schneider Electric can design equipment with digitization in mind before the infrastructure is even built. Additionally, designing for digitization pre-build could allow Schneider Electric to more easily scale its services. It is essential to chemical companies that the digital technology has been proven before risking downtime or project deadlines on a \u20ac1+ billion project. Given Schneider Electric\u2019s current portfolio of products and services, they are well set up to lead the digital transformation for chemical companies and hopefully can transition that knowledge to other industrial markets.<\/p>\n

Figure 1: Manufacturing Diversity[4]<\/strong><\/a><\/em><\/p>\n

\"\"<\/a><\/p>\n

As Schneider Electric continues to expand its automation services for its customers it will be important for the company to invest in cloud infrastructure or partner with an existing company. Schneider Electric goals in digital transformation significantly increases the data quantity and therefore data storage requirements. Additionally, given the demand for digitization projects across diverse industries, Schneider Electric will need to continue to join forces with companies that provide complementary services. Currently, Schneider Electric has formed alliances with Microsoft, AWS, Salesforce, Accenture, Cisco, and Intel[5]<\/a> in efforts to meet customer needs and expand their project capabilities.<\/p>\n

On paper, serving the growing demand for machine learning seemed like an easy pivot to Schneider Electric\u2019s existing capabilities. Although a large organization, Schneider Electric has kept its capabilities innovative through acquisitions and continuing to utilize its size and scale. However, if we are approaching a digital transformation, why are Schneider Electric\u2019s growth projections only averaging 3.4% the next three years[6]<\/a>? Maybe the transition period to a digital world is farther than we think.<\/p>\n

As Schneider Electric\u2019s leadership team reviews successes and failures of past digitization projects, they will have to predict whether digitization transformation will continue to be customer-based for Schneider Electric or if they can provide a scalable automation service. Is there a future where we design capital infrastructure for digitization? Or will each digitization project need to include a local customer-based approach?<\/p>\n

(760 words)<\/p>\n

[1]<\/a> https:\/\/www.strategyand.pwc.com\/media\/file\/Industrial-Manufacturing-Trends-2018-19.pdf<\/p>\n

[2]<\/a> https:\/\/en.wikipedia.org\/wiki\/Schneider_Electric<\/p>\n

[3]<\/a> https:\/\/www.schneider-electric.com\/ww\/en\/documents\/finance\/2018\/03\/20-release-annual-results-post-consensus-tcm50-370945.pdf<\/p>\n

[4]<\/a> https:\/\/www.mckinsey.com\/business-functions\/operations\/our-insights\/the-future-of-manufacturing<\/p>\n

[5]<\/a> https:\/\/blog.schneider-electric.com\/energy-management-energy-efficiency\/2018\/07\/13\/the-rise-of-the-extended-enterprise-in-todays-digital-economy\/<\/p>\n

[6]<\/a> https:\/\/www.schneider-electric.com\/ww\/en\/documents\/finance\/2018\/03\/20-release-annual-results-post-consensus-tcm50-370945.pdf<\/p>\n","protected":false},"excerpt":{"rendered":"

Demand for applying digitization and machine learning to current operations has increased significantly for manufacturing companies today. Can one company expand its reach to help all industries reach their goal of digital transformation?<\/p>\n","protected":false},"author":11433,"featured_media":30527,"comment_status":"open","ping_status":"closed","template":"","categories":[1346,788,2086,1479,161],"class_list":["post-30360","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-chemicals","category-digital","category-digital-transformation","category-industrials","category-manufacturing","hck-taxonomy-organization-schneider-electric","hck-taxonomy-industry-industrial-products","hck-taxonomy-country-france"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2018\/","yoast_head":"\nMachine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure - Technology and Operations Management<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Machine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure - Technology and Operations Management\" \/>\n<meta property=\"og:description\" content=\"Demand for applying digitization and machine learning to current operations has increased significantly for manufacturing companies today. Can one company expand its reach to help all industries reach their goal of digital transformation?\" \/>\n<meta property=\"og:url\" content=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/\" \/>\n<meta property=\"og:site_name\" content=\"Technology and Operations Management\" \/>\n<meta property=\"og:image\" content=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Capture-6.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1017\" \/>\n\t<meta property=\"og:image:height\" content=\"524\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\\\/\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\\\/\",\"name\":\"Machine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure - Technology and Operations Management\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Capture-6.png\",\"datePublished\":\"2018-11-13T04:16:17+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\\\/#primaryimage\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Capture-6.png\",\"contentUrl\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Capture-6.png\",\"width\":1017,\"height\":524},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Submissions\",\"item\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Machine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/#website\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/\",\"name\":\"Technology and Operations Management\",\"description\":\"MBA Student Perspectives\",\"potentialAction\":[{\"@type\":\"性视界Action\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Machine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure - Technology and Operations Management","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/","og_locale":"en_US","og_type":"article","og_title":"Machine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure - Technology and Operations Management","og_description":"Demand for applying digitization and machine learning to current operations has increased significantly for manufacturing companies today. Can one company expand its reach to help all industries reach their goal of digital transformation?","og_url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/","og_site_name":"Technology and Operations Management","og_image":[{"width":1017,"height":524,"url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Capture-6.png","type":"image\/png"}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"4 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/","url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/","name":"Machine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure - Technology and Operations Management","isPartOf":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website"},"primaryImageOfPage":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/#primaryimage"},"image":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/#primaryimage"},"thumbnailUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Capture-6.png","datePublished":"2018-11-13T04:16:17+00:00","breadcrumb":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/#primaryimage","url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Capture-6.png","contentUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Capture-6.png","width":1017,"height":524},{"@type":"BreadcrumbList","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-schneider-electric-positions-itself-to-lead-digital-transformation-of-infrastructure\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/d3.harvard.edu\/platform-rctom\/"},{"@type":"ListItem","position":2,"name":"Submissions","item":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/"},{"@type":"ListItem","position":3,"name":"Machine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure"}]},{"@type":"WebSite","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website","url":"https:\/\/d3.harvard.edu\/platform-rctom\/","name":"Technology and Operations Management","description":"MBA Student Perspectives","potentialAction":[{"@type":"性视界Action","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/d3.harvard.edu\/platform-rctom\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"}]}},"_links":{"self":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/30360","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission"}],"about":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/types\/hck-submission"}],"author":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/users\/11433"}],"replies":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/comments?post=30360"}],"version-history":[{"count":0,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/30360\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media\/30527"}],"wp:attachment":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media?parent=30360"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/categories?post=30360"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}