Risk Management in Global Supply Chains


Managing day-to-day operations in a global supply chain is no easy task. That’s certainly not news for supply chain professionals. In fact, a survey conducted by Barloworld Supply Chain Software found “four out of five supply chain executives say the performance of their supply chains is average or poor owing to the effects of globalisation.”[1] A large majority (63%) of survey participants indicated that the number of partners involved in the supply chain was a major reason for performance and risk challenges. Bart Kelly and Mike M. Varney (@Mike_VarneyCPA), from Crowe Horwath LLP, write, “The growing webs of suppliers and their subsuppliers have created greater complexity and risk in manufacturer-supplier relationships, which can result in a manufacturer having little to no notice that it is not able to meet a customer’s needs.”[2] Will Green reports that survey results released by Xchanging Procurement concludes, “Supply chain risk was seen as a challenge by 77 per cent of firms, and as an ‘extreme’ challenge by almost one in five.”[3] The worst risks, of course, are those resulting in supply chain disruptions. Bruce Gain asserts, “Disruptions in the supply chain have always been a source of major concern. … However, the level of worry will only rise as today’s worldwide supply networks become more geographically diverse, riskier, and ultimately, more prone to outages.”[4]

[blockquote style=”3″]Steven Minsky (@SteveMinsky), CEO and Founder of LogicManager, insists that the best place to start a risk assessment is by tapping employee knowledge. He writes, “Risks are known far in advance by at least one employee and typically by several on the front lines of every business.”[5] He continues:[/blockquote]

[blockquote style=”1″]Problems arise when managers lack mechanisms to escalate and connect their risks with the concerns shared by colleagues in other parts of the organization. When critical business interdependencies are not formally recognized, they remain invisible, and the cumulative impact of these concerns is rarely addressed. Without the ability to identify connections between risks across business silos, high impact risks remain ‘unknown’ to senior management. As a result, the individuals capable of allocating resources to mitigate these risks sit idly as their risk exposure grows. This is literally a preventable disaster waiting to happen.[/blockquote]

Minsky’s observation highlights the importance of understanding connections (or the lack thereof) for any business especially in the digital age. Kelly and Varney add, “Ever-expanding supply chains make it difficult to maintain consistent and timely visibility with suppliers, which ultimately affect the close relationships manufacturers historically have had with their suppliers.… Today’s supply chains, though, find companies further removed from their suppliers and a personal level of contact. Relationships increasingly are transaction-based and often focused primarily on cost, leaving relationship-based premiums severely diminished. As a result, companies might have lower costs, but they also have much less insight into the business of their suppliers, leaving them with little advance notice of signs of trouble that could affect them.” One way to deal with complexity is to employ a cognitive computing system that is able to apply the latest analytic tools to help increase supply chain visibility and predict perturbative effects resulting from disruptions or delays. Provided with the right data, a cognitive computing system can help identify relationships and potential areas of risk as well as ensure that day-to-day operations run more efficiently. Kelly and Varney assert there are four essential components of supply chain resiliency: visibility, responsiveness, integration, and control. A good cognitive computing solution can help in each of these areas.


The better the visibility and understanding of the supply chain the better able companies are to identify and deal with potential risks. Cognitive computing systems can help provide insights into the four areas that BSI identifies as important for improved resilience: Identifying critical business functions; Remembering seven operational “P’s” (i.e., providers, performance, processes, people, premises, profile, and preparation); Understanding and tracking past supplier incidents; and assessing and understanding vulnerabilities and weak points. Kelly and Varney add, “Too frequently… companies concentrate primarily on cost and on-time delivery. Instead, companies would be far better off considering a wider set of ongoing metrics and monitoring those metrics through methods as varied as regular interaction with suppliers and multifaceted supplier scorecards.”


Obviously, companies need to be responsive to challenges that threaten smooth operations. Responsiveness is particularly critical, however, whenever a disruption in supply chain operations occurs. Potential risks that could result in supply chain disruption abound. James Allt-Graham, a Partner at GRA Supply Chain Consultants, insists, “Business interruption… is around every corner for most global supply chains.”[6] Kelly and Varney add, “A company must be able to identify the areas where potentially damaging issues could arise, such as a supplier’s inability to provide the requisite supplies for the short or long term, and move those parts of its chain based on the company’s or market’s demands.” Cognitive computing systems can keep track of and provide alerts concerning many more variables than traditional monitoring systems.


Kelly and Varney write, “Integration consists of two vital elements. The first element relates to integration within the organization. Departments that play crucial roles in successful planning and production should communicate clearly and frequently…. To serve the supply chain needs more optimally, structured, recurring input from sales, production and other functions is required. The second element of integration relates to the various suppliers a manufacturer uses. Companies must find ways to create a genuine connection with their suppliers and form relationships based on more than just cost. Technology, for example, can facilitate real-time integration with and feedback for suppliers.” Cognitive computing systems are particularly adept at doing just that.


“Control in the context of supply chain resiliency comes in several forms,” Kelly and Varney write. “To begin with, a company needs to put in place activities and processes that allow it to identify, monitor and mitigate risks. The company must strike the proper balance between imposing sufficient controls to reduce risk to the organization and imposing so many controls that the company can’t operate efficiently.” Managing supply risk is an around-the-clock activity ideal for monitoring by a cognitive computing system. A cognitive computing system can handle many more variables than either a human or a traditional computer system; making it better equipped to identify anomalies and alert decision makers when there is a problem.


[1] “Supply chains struggle under pressures from globalisation,” Supply Chain Standard, 21 July 2015.
[2] Bart Kelly and Mike M. Varney,“Maintaining Resiliency in the Face of Expanding Supply Chains,” IndustryWeek, 17 June 2015.
[3] Will Green, “Supply chain risk ‘a challenge’ for nearly eight in 10 firms – survey,Supply Management, 13 July 2015.
[4] Bruce Gain, “10 Business Continuity Tips for the Global Supply Chain Era,EBN, 18 May 2015.
[5] Steven Minsky, “Managing Uncertainty: Escalating Unknown Knowns (Part 1 of 2),” ebizQ, 9 July 2015.
[6] James Allt-Graham, “Understanding Risk in your Supply Chain,Global Logistics Media, 28 May 2015.


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Stephen DeAngelis is a technology and supply chain entrepreneur and patent holder with over 25 years of experience helping to pioneer the application of advanced cognitive computing technologies and applied mathematics to commercial industries and governmental agencies. He is a former Visiting Scientist at the Mathematical and Computational Sciences Directorate and the Center for Advanced Technology at the Oak Ridge National Laboratory and at the Software Engineering Institute (SEI) at Carnegie Mellon University. He was recognized in December 2006, as one of Esquire magazine’s “Best and Brightest” honorees as “The Innovator.” In 2012, Forbes magazine recognized him as one of the “Top Influencers in Big Data.”