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Big Data Analytics Can Help Supply Chain Risk Management

July 21, 2016


Supply chain risks that result in disruptions continue to cost businesses billions of dollars a year. Gavin van Marle (@LoadstarGav) reports, “New research from the British Standards Institute (BSI) has found that global supply chains gained a combined $56bn in extra costs last year, incurred by crime, extreme weather, terrorist threats and the migrant crisis that swept across Europe.”[1] To remain profitable, companies pass those added costs along to customers. In the end, no one is happy with the results. Natural disasters remain the primary cause of disruptions according to the BSI report and the more extended your supply chain the greater that risk becomes. Van Marle notes, “The El Nino phenomenon, collectively caused $33bn damage to businesses — forest fires in Indonesia cost $16bn; the Nepal earthquake cost $4-5bn; the typhoon that destroyed swathes of China and the Philippines also had a $4bn bill with it; while floods in the US and India cost $4-5bn and $1.3-3bn respectively.” Supply chain disruptions are like trains on London’s Circle Line — if you missed the last one another one is on the way. Judith M. Myerson asserts, “Any OEM and or supplier that takes a reactive approach rather than [a] proactive [one] to dealing with natural disaster disruptions [is] taking a big gamble.”[2] Myerson adds, “A risk management plan consists of four key elements: assets, vulnerabilities, risks and safeguards/remediation.” A company must have a proactive supply chain risk management plan that addresses each of those areas if it is going to be resilient.


Kaitlyn McAvoy (@KMcAvoySM) argues that one of the best ways to be proactive with your supply chain risk management process is to take advantage of big data analytics — but, she argues, not enough companies are taking advantage of them. “Big data analytics has a number of applications within the supply chain,” she writes. “Yet there is still some lag in adoption of solutions that help mine through the wealth of information that can lead to an increase supply chain visibility, reduce business risks and other benefits. Recent research has shown while the majority of companies understand the opportunities big data presents, fewer are actually implementing analytic capabilities and integrating these tools into supply chain functions.”[3] Although so-called “acts of God” can’t be predicted accurately, big data can help companies understand patterns and risks. Hurricanes, for example, are so regular that meteorologists have established an annual season for them (basically June through November). Armed with insights about risk patterns, companies are better able to establish mitigation plans. Rick Schreiber, partner and leader of the Manufacturing & Distribution practice and partner of the Consumer Business practice at BDO USA, LLP, rhetorically asks, “Why do you need a contingency plan for Mother Nature? For starters, weather- and climate-related disasters have caused $2.4 trillion in economic losses and nearly 2 million deaths globally since 1971, according to the World Meteorological Organization. And more recently, you may recall the transportation and logistics shutdowns during the winter of 2014 that took a $15 billion bite out of U.S. businesses. These numbers alone should be reason enough to develop a contingency plan to help your business stay afloat during a significant business interruption, like a hurricane.”[4]


Analysts from the Wharton School of Business write, “In the highly complex world of risk management, mistakes, shortcuts and a lack of planning or regulation can lead to grave consequences if and when disaster strikes. But the digital revolution of the past several decades has contributed a number of innovations to help risk managers craft more effective and airtight strategies for facing such situations.”[5] At a conference on supply chain risk management held at Wharton, University of Pennsylvania Provost Vincent Price stated, “A poor decision can turn a natural disaster into what in retrospect looks very much like a man-made catastrophe. Such a level of complexity demands input not only from numerous and varied academic experts, but also from experts both in the government and the private sector.” I would argue that complexity requires more than expert inputs if a supply chain risk management process is going to be effective. Even the best experts can’t tell you how all the variables that must be considered might interact to create a crisis. Fortunately, cognitive computing systems are capable of dealing with a large number of variables and can help make sense of complex situations. Another speaker at the Wharton conference made that point. Holly Bamford, former acting assistant secretary for conservation and management for the National Oceanic and Atmospheric Administration (NOAA), told conference participants that over the past couple of decades computerized modeling has “really advanced our understanding of the intensity of storms and [storm] tracks.” As cognitive computing systems mature, they will be able to provide similar insights into other complex situations affecting supply chain risk management.


That point was driven home by another speaker, Robin Gregory, associate director of the Eco-Risk Research Unit at the University of British Columbia. Gregory “noted that much of the innovation in long-term risk management is coming from the public. ‘Experts are surprised by that wealth of knowledge’ emerging in public discussion groups and on social media, he noted.” Clearly, humans can’t track and analyze social media data without the aid of artificial intelligence. The same holds true in many areas that could have direct or indirect impacts on supply chain risk management efforts. A press release from DHL concerning release of a study noted, “Building resilience to ‘expect the unexpected’ isn’t only the best defense against supply chain disruption, global companies who get it right could avoid million dollar losses and enjoy organization-wide competitive advantage. This is one of the central findings presented in DHL’s new InsightOn report on risk management and supply chain resilience.”[6] In the release, Bill Meahl, Chief Commercial Officer at DHL, states, “The modern economy runs on interconnected global supply chains, but with distance and complexity come new types of risk from natural and manmade disasters, climate change, and socio-political and economic factors from war to strikes and crime. Any company relying on complex supply chains needs to improve its risk management.”


[1] Gavin van Marle, “Supply chain disruption cost $56bn last year – and there’s more risk to come,” The Loadstar, 23 March 2016.
[2] Judith M. Myerson, “Avoid Disaster through Supply Chain Risk Management,” EBN, 9 June 2016.
[3] Kaitlyn McAvoy, “Big Data Presents Opportunities for the Supply Chain, but are Organizations Taking Advantage of It?Spend Matters, 1 June 2016.
[4] Rick Schreiber, “How to Not Lose Your Shirt When Disaster Strikes Your Supply Chain,” Apparel, 23 May 2016.
[5] Staff, “How Innovative Tech Is Changing the Way We Respond to Risk,” Knowledge@Wharton, 22 March 2016.
[6] DHL, “Supply chain resilience best defense against growing global risks,” Freightnet, 29 February 2016.

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