  {"id":22305,"date":"2017-11-14T15:09:51","date_gmt":"2017-11-14T20:09:51","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/drugs-digitized-merck-leads-pharmas-belated-adoption-of-supply-chain-4-0\/"},"modified":"2017-11-14T15:12:36","modified_gmt":"2017-11-14T20:12:36","slug":"drugs-digitized-merck-leads-pharmas-delayed-adoption-of-supply-chain-4-0","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/drugs-digitized-merck-leads-pharmas-delayed-adoption-of-supply-chain-4-0\/","title":{"rendered":"Drugs, Digitized: Merck Leads Pharma\u2019s Delayed Adoption of Supply Chain 4.0"},"content":{"rendered":"<p><strong>S<\/strong>uppose Nike rolls out a digital innovation in its warehouse or tests a new predictive demand algorithm: if manufacturing disruptions or algorithm errors mean a few Air Zoom Pegasus sneakers are late or poor quality, the company risks some disgruntled customers. When pharmaceutical companies underestimate demand or adopt unproven new technologies, they risk lives, potentially providing consumers faulty products or disrupting treatment regimens. Given these stringent performance requirements, pharma companies have been slower to adopt supply chain digitalization than their counterparts in consumer goods, less willing to risk the performance lapses that altering information systems and trialing innovations often cause.<a href=\"#_edn1\" name=\"_ednref1\">[1]<\/a><\/p>\n<p><strong>I<\/strong>ncreasing financial and competitive pressures, however, mean supply chain digitalization is rapidly becoming an imperative for pharma as well. The market shift toward generics is eroding top lines, while increasing development costs erodes margins, pushing companies to look to the supply chain for cost savings.<a href=\"#_edn2\" name=\"_ednref2\">[2]<\/a> Second, expansion into developing markets in search of higher growth threatens longer supply chains with higher complexity, lead times, and operational expense.<a href=\"#_edn3\" name=\"_ednref3\">[3]<\/a> Third, increased demand for products derived from biologics (requiring constant cold storage) promises dramatically higher inventory costs unless process changes mitigate the increase.<a href=\"#_edn4\" name=\"_ednref4\">[4]<\/a> For Merck KGaA, a global pharmaceutical and biotechnology company, to remain a leading player, the company will have to digitalize its supply chain \u2013 and quickly.<\/p>\n<p><strong>Exhibit 1<\/strong>: Development costs per drug are rising dramatically<a href=\"#_edn5\" name=\"_ednref5\">[5]<\/a><\/p>\n<p><strong><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/sci-american-drug-costs.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-medium wp-image-22309\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/sci-american-drug-costs-300x275.png\" alt=\"\" width=\"300\" height=\"275\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/sci-american-drug-costs-300x275.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/sci-american-drug-costs-600x551.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/sci-american-drug-costs.png 608w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><\/strong><\/p>\n<p><strong>I<\/strong>n fact, Merck KGaA, is \u201cat the forefront of digitizing its pharma supply chain.\u201d<a href=\"#_edn6\" name=\"_ednref6\">[6]<\/a> In 2015, Merck partnered with supply chain analytics firm Aera<a href=\"#_edn7\" name=\"_ednref7\">[7]<\/a> to create digestible and actionable data visualizations, providing Merck more real-time visibility into supply chain performance but also the ability to grasp more quickly the <em>implications<\/em> of metrics and to react more effectively.<a href=\"#_edn8\" name=\"_ednref8\">[8]<\/a> Building on these capabilities, in March 2017 Merck launched a multi-year supply chain automation effort to enhance its ability to predict and satisfy demand as a \u201cfirst step toward full digitization\u201d<a href=\"#_edn9\" name=\"_ednref9\">[9]<\/a>: the vision is to move from highly manual, human-driven control to artificial intelligence \u201cthat analyzes data continuously and makes decisions on its own about speed and resources.\u201d<a href=\"#_edn10\" name=\"_ednref10\">[10]<\/a> The effort involves installing sensors throughout Merck\u2019s sourcing, manufacturing, and distribution facilities and implementing predictive demand algorithms that use the data collected to make decisions about production schedules, raw material allocation, and distribution, independent of human operators.<a href=\"#_edn11\" name=\"_ednref11\">[11]<\/a> The project is intended to help Merck to \u201cprocess orders in the shortest time possible\u201d and build the company\u2019s ability to react to demand spikes or manufacturing disruptions (e.g., natural disasters).<\/p>\n<p><strong>Exhibit 2: <\/strong>Examples of Aera\u2019s visualization products<a href=\"#_edn12\" name=\"_ednref12\">[12]<\/a><\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/AERA.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-22311 size-large\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/AERA-1024x541.png\" alt=\"\" width=\"640\" height=\"338\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/AERA-1024x541.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/AERA-300x159.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/AERA-768x406.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/AERA-600x317.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/AERA.png 1025w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/Supply-chain-cloud-fig1.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-large wp-image-22327\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/Supply-chain-cloud-fig1-1024x647.jpg\" alt=\"\" width=\"640\" height=\"404\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/Supply-chain-cloud-fig1-1024x647.jpg 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/Supply-chain-cloud-fig1-300x190.jpg 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/Supply-chain-cloud-fig1-768x485.jpg 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/Supply-chain-cloud-fig1-600x379.jpg 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/Supply-chain-cloud-fig1.jpg 1496w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><\/p>\n<p>&nbsp;<\/p>\n<p><strong>M<\/strong>erck has also recently partnered with big data firm Palantir to bolster its ability to leverage predictive data in its supply chain. In the short term, Merck intends the partnership to accelerate the R&amp;D phase of its go-to-market process and reduce drug development costs \u2013 critical competitive differentiators \u2013 by \u201cus[ing] Palantir\u2019s analytics software to\u2026predict which patients will respond best to certain drugs,\u201d first for cancer treatments and then across Merck\u2019s portfolio.<a href=\"#_edn13\" name=\"_ednref13\">[13]<\/a> Over the longer term, Merck hopes Palantir\u2019s big data capabilities will bolster its global \u201cforecasting and agility\u201d<a href=\"#_edn14\" name=\"_ednref14\">[14]<\/a> and further its ultimate aim of building a fully automated, \u201cself-driving supply chain \u2018without [human] pilots.\u2019\u201d<a href=\"#_edn15\" name=\"_ednref15\">[15]<\/a><\/p>\n<p><strong>T<\/strong>o complement these plans, Merck should consider incorporating additional digitalization efforts. In the short term, Merck could use sensors not only to predict demand and optimize production schedules, but also to anticipate and automatically prevent manufacturing failures.<a href=\"#_edn16\" name=\"_ednref16\">[16]<\/a> Machine sensors can signal when proactive maintenance would enhance output, avoiding costly downtime and reducing lifetime maintenance costs, while testing sensors can signal when manufacturing processes should be adjusted <em>before <\/em>products begin to fail standards, reducing downtime and waste. Second, Merck could move toward a leaner supply chain while maintaining high service levels by increasing inventory and demand transparency with its procurement partners and direct customers, potentially sharing real-time output from its predictive demand algorithms to give all its partners superior visibility into coming needs. In the longer term, Merck could bolster its feedback loop with end-consumers by tracking individual usage or introducing voluntary internal monitoring devices<a href=\"#_edn17\" name=\"_ednref17\">[17]<\/a> \u2013 real-time data on adherence and efficacy could help anticipate demand and also surface potential product improvements on an on-going basis. Around all these digitalization efforts, however, Merck should prioritize security to ensure its production and monitoring processes are not vulnerable to cyberattacks.<\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/DigitalPillResize.jpeg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-medium wp-image-22313\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/DigitalPillResize-300x200.jpeg\" alt=\"\" width=\"300\" height=\"200\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/DigitalPillResize-300x200.jpeg 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2017\/11\/DigitalPillResize.jpeg 600w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><\/p>\n<p><strong>A<\/strong>s pharma continues to digitalize, are there technologies CPG has successfully adopted that pharma will have to avoid given the risks to the consumer? Will supply chain digitalization in pharma be fundamentally different somehow than in other industries?<\/p>\n<p>(Word count: 796)<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Endnotes<\/strong><\/p>\n<p><a href=\"#_ednref1\" name=\"_edn1\"><\/a>1 Peter Behner and Dr. Marcus Ehrhardt. \u201cDigitization in pharma: Gaining an edge in operations,\u201d <em>Strategy&amp;<\/em>, October 19, 2016, <a href=\"https:\/\/www.strategyand.pwc.com\/reports\/digitization-in-pharma\">https:\/\/www.strategyand.pwc.com\/reports\/digitization-in-pharma<\/a>, accessed November 2017.<\/p>\n<p>Julian Upton, \u201cSetting Sights on the Smart Supply Chain,\u201d <em>Pharmaceutical Executive<\/em> vol. 37, no. 3 (2017), accessed November 2017.<\/p>\n<p><a href=\"#_ednref2\" name=\"_edn2\"><\/a>2 Rick Mullin. \u201cCost to Develop New Pharmaceutical Drug Now Exceeds $2.5B,\u201d <em>Scientific American<\/em>, November 24, 2014, <a href=\"https:\/\/www.scientificamerican.com\/article\/cost-to-develop-new-pharmaceutical-drug-now-exceeds-2-5b\/\">https:\/\/www.scientificamerican.com\/article\/cost-to-develop-new-pharmaceutical-drug-now-exceeds-2-5b\/<\/a>, accessed November 2017.<\/p>\n<p>Allen Jacques. \u201c2017 Trends &amp; Transformations in the Pharma Supply Chain,\u201d <em>Pharmaceutical Processing<\/em>, December 29, 2016, <a href=\"https:\/\/www.pharmpro.com\/article\/2016\/12\/2017-trends-transformations-pharma-supply-chain\">https:\/\/www.pharmpro.com\/article\/2016\/12\/2017-trends-transformations-pharma-supply-chain<\/a>, accessed November 2017.<\/p>\n<p><a href=\"#_ednref3\" name=\"_edn3\"><\/a>3 Behner and Ehrhardt, \u201cDigitization in pharma: Gaining an edge in operations.\u201d Jacques, \u201c2017 Trends &amp; Transformations in the Pharma Supply Chain.\u201d<\/p>\n<p><a href=\"#_ednref4\" name=\"_edn4\"><\/a>4 Jacques, \u201c2017 Trends &amp; Transformations in the Pharma Supply Chain.\u201d<\/p>\n<p><a href=\"#_ednref5\" name=\"_edn5\"><\/a>5 Mullin, \u201cCost to Develop New Pharmaceutical Drug Now Exceeds $2.5B.\u201d<\/p>\n<p><a href=\"#_ednref6\" name=\"_edn6\"><\/a>6 Upton, \u201cSetting Sights on the Smart Supply Chain.\u201d<\/p>\n<p><a href=\"#_ednref7\" name=\"_edn7\"><\/a>7 Aera was known at the time as FusionOps.<\/p>\n<p><a href=\"#_ednref8\" name=\"_edn8\"><\/a>8 \u201cFusionOps brings enhanced supply chain visibility to pharma with new analytics capabilities,\u201d July 13, 2015, Pharmaceutical Commerce, <a href=\"http:\/\/pharmaceuticalcommerce.com\/latest-news\/fusionops-brings-enhanced-supply-chain-visibility-to-pharma-with-new-analytics-capabilities\/\">http:\/\/pharmaceuticalcommerce.com\/latest-news\/fusionops-brings-enhanced-supply-chain-visibility-to-pharma-with-new-analytics-capabilities\/<\/a>, accessed November 2017.<\/p>\n<p><a href=\"#_ednref9\" name=\"_edn9\"><\/a>9 Upton, \u201cSetting Sights on the Smart Supply Chain.\u201d<\/p>\n<p><a href=\"#_ednref10\" name=\"_edn10\"><\/a>10 Kim S. Nash. \u201cMerck Deploys AI For \u2018Self-Driving\u2019 Supply Chain,\u201d <em>Wall Street Journal<\/em>, December 20, 2016, <a href=\"https:\/\/blogs.wsj.com\/cio\/2016\/12\/20\/merck-deploys-ai-for-self-driving-supply-chain\/\">https:\/\/blogs.wsj.com\/cio\/2016\/12\/20\/merck-deploys-ai-for-self-driving-supply-chain\/<\/a>, accessed November 2017.<\/p>\n<p><a href=\"#_ednref11\" name=\"_edn11\"><\/a>11 <em>Ibid.<br \/>\n<\/em><\/p>\n<p><a href=\"#_ednref12\" name=\"_edn12\"><\/a>12 Aera company website (<a href=\"https:\/\/www.aeratechnology.com\/technology\">https:\/\/www.aeratechnology.com\/technology<\/a>).<\/p>\n<p><a href=\"#_ednref13\" name=\"_edn13\"><\/a>13 Michal Lev-Ram. \u201cPalantir\u2019s Bet on Big Pharma,\u201d Fortune, January 12, 2017, <a href=\"http:\/\/fortune.com\/2017\/01\/12\/palantir-merck-pharma\/\">http:\/\/fortune.com\/2017\/01\/12\/palantir-merck-pharma\/<\/a>, accessed November 2017.<\/p>\n<p>\u201cMerck seals collaborations in Silicon Valley,\u201d ENP Newswire, March 1, 2017, via Factiva, accessed November 2017.<\/p>\n<p>\u201cMerck KGaA, Darmstadt, Germany, and Palantir Launch New Healthcare Acceleration Partnership,\u201d PR Newswire, January 12, 2017, <a href=\"https:\/\/www.prnewswire.com\/news-releases\/merck-kgaa-darmstadt-germany-and-palantir-launch-new-healthcare-acceleration-partnership-300390579.html\">https:\/\/www.prnewswire.com\/news-releases\/merck-kgaa-darmstadt-germany-and-palantir-launch-new-healthcare-acceleration-partnership-300390579.html<\/a>, accessed November 2017.<\/p>\n<p><a href=\"#_ednref14\" name=\"_edn14\"><\/a>14 Upton, \u201cSetting Sights on the Smart Supply Chain.\u201d<\/p>\n<p><a href=\"#_ednref15\" name=\"_edn15\"><\/a>15 Upton, \u201cSetting Sights on the Smart Supply Chain.\u201d<\/p>\n<p><a href=\"#_ednref16\" name=\"_edn16\"><\/a>16 Upton, \u201cSetting Sights on the Smart Supply Chain.\u201d<\/p>\n<p>Knut Alicke, Daniel Rexhausen, and Andreas Seyfert. \u201cSupply Chain 4.0 in consumer goods,\u201d <em>McKinsey &amp; <\/em><em>Company<\/em>, April 2017.<\/p>\n<p><a href=\"#_ednref17\" name=\"_edn17\"><\/a>17 Pam Belluck. \u201cFirst Digital Pill Approved to Worries About Biomedical \u2018Big Brother,\u2019\u201d <em>New York Times<\/em>, November 13, 2017, <a href=\"https:\/\/www.nytimes.com\/2017\/11\/13\/health\/digital-pill-fda.html\">https:\/\/www.nytimes.com\/2017\/11\/13\/health\/digital-pill-fda.html<\/a>, accessed November 2017.<\/p>\n<p>Banner photo source: https:\/\/eyeforpharmadrupalfs.s3.amazonaws.com\/istock-615087156.jpg<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Forget self-driving cars &#8211; Merck looks to create a self-driving supply chain with artificial intelligence calling the shots<\/p>\n","protected":false},"author":9993,"featured_media":22357,"comment_status":"open","ping_status":"closed","template":"","categories":[1909,3235,2123,3475,770],"class_list":["post-22305","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-artificial-intelligence","category-digital-supply-chain","category-digitalization","category-merck","category-pharma","hck-taxonomy-industry-pharmaceutical"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2017\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - 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