{"id":33145,"date":"2018-11-13T18:58:17","date_gmt":"2018-11-13T23:58:17","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/"},"modified":"2018-11-13T18:58:17","modified_gmt":"2018-11-13T23:58:17","slug":"walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/","title":{"rendered":"Walmart takes on Amazon: The Journey from Brick &amp; Mortar to Click &amp; Mortar"},"content":{"rendered":"<p><u>Artificial Intelligence in Retail<\/u><\/p>\n<p>The retail industry is facing a critical inflection point. Gone are the days where big box retailers could claim to be digital by creating an e-commerce business unit. As consumers shift a larger portion of their wallet to online platforms and grow increasingly demanding amid more options on\/offline, traditional retailers have been trying to keep up in building analytical competency: they must move beyond finding indicators of success in historical performance, instead identifying future areas of opportunity. To complicate matters, Amazon is bolstering its presence as it reaches ~$1 trillion in market capitalization<sup>1<\/sup>, posing an insurmountable threat to competition.<\/p>\n<p>Fortunately, the future looks promising for retailers that are proactively addressing the shifting dynamics. A recent report shows that the retail industry could be the biggest beneficiary of artificial intelligence (AI) and machine learning (ML)<sup>2<\/sup>.<\/p>\n<figure id=\"attachment_34976\" aria-describedby=\"caption-attachment-34976\" style=\"width: 640px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/AI-x-Retail-impact.png\"><img loading=\"lazy\" decoding=\"async\" class=\"size-large wp-image-34976\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/AI-x-Retail-impact-1024x823.png\" alt=\"\" width=\"640\" height=\"514\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/AI-x-Retail-impact-1024x823.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/AI-x-Retail-impact-300x241.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/AI-x-Retail-impact-768x617.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/AI-x-Retail-impact-600x482.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/AI-x-Retail-impact.png 1043w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><figcaption id=\"caption-attachment-34976\" class=\"wp-caption-text\">Retail is the top industry for value creation through AI<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>The granularity and depth of customer- and SKU-level data in the industry create a wealth of opportunity for the retailer that can recognize patterns and draw forward-looking insights from this repository. Conventionally, the more common applications of AI and ML in retail so far have been grounded in Marketing &amp; Sales: personalized recommendations (Next Product to Buy), targeted marketing campaigns, and assortment optimization. Increasingly, retailers are beginning to use the same technology in supply chain management, e.g., predictive maintenance or inventory control, as well as using analytics to make more critical M&amp;S decisions, such as pricing and promotions<sup>3<\/sup>. In his recent letter to shareholders, Bezos states how ML can permeate all integral aspects of retail operations:<\/p>\n<p style=\"text-align: center\">\u201c<em>Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more<\/em>.<sup>4<\/sup>\u201d<\/p>\n<p>&nbsp;<\/p>\n<p><u>Case Study: Walmart <\/u><\/p>\n<p>As one of the largest big box retailers in the world and a significant competitor to Amazon in the digital space, Walmart has exhibited a track record of taking AI seriously. Since appointing its current e-commerce unit CEO Lore, Walmart has taken strides in leveraging ML across major facets of its business, with both shorter and medium-to-long time horizons:<\/p>\n<ul>\n<li><em>Customer Service \u2013 faster shopping<\/em>:\n<ol start=\"5\">\n<li>Patents issues for Scan &amp; Go technology where customers can ring up purchases on their smartphones and avoid checkout lines altogether<sup>5<\/sup>.<\/li>\n<li>Pick up towers that retrieve customers\u2019 online orders from receipt barcodes within 45 seconds to speed up checkout<sup>6<\/sup>.<\/li>\n<\/ol>\n<\/li>\n<li><em>Store operations<\/em>: Autonomous robots used to scan shelves and monitor inventory using machine vision and learning<sup>7<\/sup>.<\/li>\n<\/ul>\n<p>Its newly opened Sam\u2019s Club Now (Dallas) is a pilot store that will test all new technologies, including plans for augmented reality, voice navigation, and auto-filled shopping lists in the future<sup>8<\/sup><\/p>\n<figure id=\"attachment_35257\" aria-describedby=\"caption-attachment-35257\" style=\"width: 640px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Sams-club.jpeg\"><img loading=\"lazy\" decoding=\"async\" class=\"size-large wp-image-35257\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Sams-club-1024x683.jpeg\" alt=\"\" width=\"640\" height=\"427\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Sams-club-1024x683.jpeg 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Sams-club-300x200.jpeg 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Sams-club-768x512.jpeg 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Sams-club-600x400.jpeg 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Sams-club.jpeg 1200w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><figcaption id=\"caption-attachment-35257\" class=\"wp-caption-text\">Sam&#8217;s Club Now (Dallas)<\/figcaption><\/figure>\n<ul>\n<li><em>Acquisitions<\/em>: Acquired prominent e-commerce players such as Bonobos, Jet.com and Flipkart<sup>9<\/sup> (India) to build relevancy and talent, and explore further synergies. Also recently invested in Team8 to better understand the cybersecurity landscape and protecting itself (and customers) from fraud<sup>10<\/sup>.<\/li>\n<li><em>Talent<\/em>: Outside of acquisitions, also actively recruiting experts in ML\/AI. Recently it opened its Emerging Technologies office in Dallas to capture value from the vast amount of data held by the retailer. Walmart plans to build up a ~50-person team of ML, IOT, and computer vision experts by year-end<sup>11<\/sup>.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><u>Where next?<\/u><\/p>\n<p>While the retailer has garnered the accolade of \u201cout-innovating every retailer under the sun, with the exception of Amazon<sup>12<\/sup>\u201d, there are further opportunities to consider to fully leverage its omnichannel presence in competing against Amazon. One idea to entertain is personalized marketing campaigns that utilize customer information form both in-store and online purchases. Walmart is already investing in ways to track better quality input from in-store shopping; marrying this with Walmart.com data can create as comparable of a dataset to Amazon as any retailer can, and allow Walmart to better predict its customers\u2019 demands despite significantly lower online traffic<sup>13<\/sup>.<\/p>\n<p>Research<sup>14<\/sup> shows that customers that shop both online and in-store are 2-3x more valuable, and that Walmart shoppers who shop in-store that have been converted to shop online actually purchase more in-store afterwards. I would argue that the biggest asset Walmart has against Amazon is its physical store business: Walmart should continuously look at ways to generate value through synergies across channels.<\/p>\n<p>&nbsp;<\/p>\n<p><u>Further areas for discussion<\/u><\/p>\n<p>Considering developments discussed so far, I would love to hear from peers on the following topics:<\/p>\n<ul>\n<li>Walmart has recently struck a multi-year contract with Microsoft to use their cloud servers and team up to compete against Amazon using combined AI and ML capabilities. What kind of synergies could we expect from this combination?<\/li>\n<li>Recently several retailers have stopped using ML-enabled service chatbots due to customer backlash. Is there room for ML in customer-facing services?<\/li>\n<li>What other types of companies could make sense for Walmart to invest in \/ acquire in light of establishing presence as an analytics\/ML-driven digital company?<\/li>\n<\/ul>\n<p>(Word Count: 795)<\/p>\n<p>&nbsp;<\/p>\n<p>1 Franck, Thomas. \u201cAmazon closes in bear market a little more than two months after hitting $1 trillion market cap.\u201d CNBC, November 12, 2018. <a href=\"https:\/\/www.cnbc.com\/2018\/11\/12\/amazon-falls-into-bear-market-2-months-after-hitting-1-trillion.html\">https:\/\/www.cnbc.com\/2018\/11\/12\/amazon-falls-into-bear-market-2-months-after-hitting-1-trillion.html<\/a><\/p>\n<p>2 Chui, Michael et al. \u2018Notes from the AI Frontier: Insights from Hundreds of Use Cases.\u2019 McKinsey Global Institute, April 2018. <a href=\"https:\/\/www.mckinsey.com\/~\/media\/mckinsey\/featured%20insights\/artificial%20intelligence\/notes%20from%20the%20ai%20frontier%20applications%20and%20value%20of%20deep%20learning\/mgi_notes-from-ai-frontier_discussion-paper.ashx\">https:\/\/www.mckinsey.com\/~\/media\/mckinsey\/featured%20insights\/artificial%20intelligence\/notes%20from%20the%20ai%20frontier%20applications%20and%20value%20of%20deep%20learning\/mgi_notes-from-ai-frontier_discussion-paper.ashx<\/a><\/p>\n<p>3 Begley, Steven et al. \u201cHow analytics and digital will drive next generation retail merchandising.\u201d McKinsey &amp; Company, August 2018. <a href=\"https:\/\/www.mckinsey.com\/industries\/retail\/our-insights\/how-analytics-and-digital-will-drive-next-generation-retail-merchandising\">https:\/\/www.mckinsey.com\/industries\/retail\/our-insights\/how-analytics-and-digital-will-drive-next-generation-retail-merchandising<\/a><\/p>\n<p>4 Bezos, Jeff. Letter to Shareholders. April 12, 2017. <a href=\"https:\/\/www.sec.gov\/Archives\/edgar\/data\/1018724\/000119312517120198\/d373368dex991.htm\">https:\/\/www.sec.gov\/Archives\/edgar\/data\/1018724\/000119312517120198\/d373368dex991.htm<\/a><\/p>\n<p>5 Halzack, Sarah. \u201cWalmart\u2019s plan to get you in and out of stores faster.\u201d The Washington Post, February 28, 2017. <a href=\"https:\/\/www.washingtonpost.com\/news\/business\/wp\/2017\/02\/28\/walmarts-plan-to-get-you-in-and-out-of-stores-faster\/?noredirect=on&amp;utm_term=.4472e712e711\">https:\/\/www.washingtonpost.com\/news\/business\/wp\/2017\/02\/28\/walmarts-plan-to-get-you-in-and-out-of-stores-faster\/?noredirect=on&amp;utm_term=.4472e712e711<\/a><\/p>\n<p>6 Peterson, Hayley. \u201cWalmart is building giant towers to solve the most annoying thing about online ordering.\u201d Business Insider, July 5, 2017. <a href=\"https:\/\/www.businessinsider.com\/walmart-builds-pickup-towers-for-online-orders-2017-6\">https:\/\/www.businessinsider.com\/walmart-builds-pickup-towers-for-online-orders-2017-6<\/a><\/p>\n<p>7 \u2018The Smarter Store: How AI is powering the future of retail.\u2019 CB Insights, November 2017. <a href=\"https:\/\/www.cbinsights.com\/reports\/CB_Insights_AI-Retail-Briefing.pdf?utm_campaign=ai-in-retail_2017-11&amp;utm_source=hs_automation&amp;utm_medium=email&amp;utm_content=58295005&amp;_hsenc=p2ANqtz-_jdv6RwKCZjOApRQcGUYjwsg-8VPpc0pOYsZVsBqeGOoz3w_iMLgNj-hswdMHW1-YDW_PoJ0FmkzrgyxVaMzH7rNK1Xg&amp;_hsmi=58295005\">https:\/\/www.cbinsights.com\/reports\/CB_Insights_AI-Retail-Briefing.pdf?utm_campaign=ai-in-retail_2017-11&amp;utm_source=hs_automation&amp;utm_medium=email&amp;utm_content=58295005&amp;_hsenc=p2ANqtz-_jdv6RwKCZjOApRQcGUYjwsg-8VPpc0pOYsZVsBqeGOoz3w_iMLgNj-hswdMHW1-YDW_PoJ0FmkzrgyxVaMzH7rNK1Xg&amp;_hsmi=58295005<\/a><\/p>\n<p>8 Iannone, Jamie. \u201cSam\u2019s Club Now \u2013 Reimagining the Future of Retail.\u201d Sam\u2019s Club, October 29, 2018. <a href=\"https:\/\/corporate.samsclub.com\/blog\/2018\/10\/29\/sams-club-now-reimagining-the-future-of-retail\">https:\/\/corporate.samsclub.com\/blog\/2018\/10\/29\/sams-club-now-reimagining-the-future-of-retail<\/a><\/p>\n<p>9 O\u2019Shea, Dan. \u201cWalmart CFO Biggs touts retailer\u2019s e-commerce build-up.\u201d Retail Dive, June 19, 2017. <a href=\"https:\/\/www.retaildive.com\/news\/walmart-cfo-biggs-touts-retailers-e-commerce-build-up\/445266\/\">https:\/\/www.retaildive.com\/news\/walmart-cfo-biggs-touts-retailers-e-commerce-build-up\/445266\/<\/a><\/p>\n<p>10 Cheng, Andria. \u201cWhy Walmart is Investing in a Startup Founded by Former Leaders of Israel\u2019s Top Intelligence Unit.\u201d Forbes, October 23, 2018. <a href=\"https:\/\/www.forbes.com\/sites\/andriacheng\/2018\/10\/23\/why-walmart-is-investing-in-a-startup-founded-by-former-leaders-of-israelis-top-intelligence-unit\/#45041c0c6d73\">https:\/\/www.forbes.com\/sites\/andriacheng\/2018\/10\/23\/why-walmart-is-investing-in-a-startup-founded-by-former-leaders-of-israelis-top-intelligence-unit\/#45041c0c6d73<\/a><\/p>\n<p>11 Hensel, Anna. \u201cWalmart plans to open a computer vision and machine learning office in Dallas on April 5.\u201d VentureBeat, March 6, 2018. <a href=\"https:\/\/venturebeat.com\/2018\/03\/06\/walmart-plans-to-open-a-computer-vision-and-machine-learning-office-in-dallas-on-april-5\/\">https:\/\/venturebeat.com\/2018\/03\/06\/walmart-plans-to-open-a-computer-vision-and-machine-learning-office-in-dallas-on-april-5\/<\/a><\/p>\n<p>12 Ruff, Corinne. \u201cThe retail winners and losers of 2017.\u201d Retail Dive, December 20, 2017. <a href=\"https:\/\/www.retaildive.com\/news\/the-retail-winners-and-losers-of-2017\/513576\/\">https:\/\/www.retaildive.com\/news\/the-retail-winners-and-losers-of-2017\/513576\/<\/a><\/p>\n<p>13 Sevitt, Daniel. \u201cAmazon vs Walmart \u2013 The Battleground for Online Retail \u2013 Part I.\u201d The Market Intelligence Blog, April 25, 2018. \u00a0<a href=\"https:\/\/www.similarweb.com\/blog\/amazon-vs-walmart\">https:\/\/www.similarweb.com\/blog\/amazon-vs-walmart<\/a><\/p>\n<p>14 Safian, Robert. \u201cAs Amazon and Walmart Duke It Out, Niche Retail Can Thrive.\u201d Fast Company, January 9, 2018. <a href=\"https:\/\/www.fastcompany.com\/40509026\/as-amazon-and-walmart-duke-it-out-niche-retail-can-thrive\">https:\/\/www.fastcompany.com\/40509026\/as-amazon-and-walmart-duke-it-out-niche-retail-can-thrive<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The retail industry is facing a digital revolution at a pace never seen before. With the digital behemoth that is Amazon, traditional brick &amp;amp; mortar retailers are challenged to find ways to integrate analytics to remain competitive. This article looks at how Walmart is taking large bets in artificial intelligence and machine learning (ML) to support its long-term growth and their vision of a &#039;newly imagined future of retail.&#039;<\/p>\n","protected":false},"author":11644,"featured_media":35309,"comment_status":"open","ping_status":"closed","template":"","categories":[1869,826,346,16],"class_list":["post-33145","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-ai","category-big-box-retailers","category-machine-learning","category-retail","hck-taxonomy-organization-walmart","hck-taxonomy-industry-retail","hck-taxonomy-country-united-states"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2018\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Walmart takes on Amazon: The Journey from Brick &amp; Mortar to Click &amp; Mortar - 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\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Walmart takes on Amazon: The Journey from Brick &amp; Mortar to Click &amp; Mortar - Technology and Operations Management\" \/>\n<meta property=\"og:description\" content=\"The retail industry is facing a digital revolution at a pace never seen before. With the digital behemoth that is Amazon, traditional brick &amp;amp; mortar retailers are challenged to find ways to integrate analytics to remain competitive. 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With the digital behemoth that is Amazon, traditional brick &amp;amp; mortar retailers are challenged to find ways to integrate analytics to remain competitive. This article looks at how Walmart is taking large bets in artificial intelligence and machine learning (ML) to support its long-term growth and their vision of a &#039;newly imagined future of retail.&#039;","og_url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/","og_site_name":"Technology and Operations Management","og_image":[{"width":3048,"height":871,"url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Walmart-logo.png","type":"image\/png"}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"6 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/","url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/","name":"Walmart takes on Amazon: The Journey from Brick &amp; Mortar to Click &amp; Mortar - Technology and Operations Management","isPartOf":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website"},"primaryImageOfPage":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/#primaryimage"},"image":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/#primaryimage"},"thumbnailUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Walmart-logo.png","datePublished":"2018-11-13T23:58:17+00:00","breadcrumb":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/d3.harvard.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/#primaryimage","url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Walmart-logo.png","contentUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Walmart-logo.png","width":3048,"height":871},{"@type":"BreadcrumbList","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/walmart-takes-on-amazon-the-journey-from-brick-mortar-to-click-mortar\/#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":"Walmart takes on Amazon: The Journey from Brick &amp; Mortar to Click &amp; Mortar"}]},{"@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":"SearchAction","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\/33145","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\/11644"}],"replies":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/comments?post=33145"}],"version-history":[{"count":0,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/33145\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media\/35309"}],"wp:attachment":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media?parent=33145"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/categories?post=33145"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}