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Cognitive Computing and the Digital Supply Chain

March 13, 2017


The term “supply chain” emerged because historically every step of the process that saw raw material converted into a product for consumer use was seen as a link. According to Deloitte analysts Adam Mussomeli, Doug Gish, and Stephen Laaper, that linear view of things is out of date. “Supply chains are traditionally linear,” they write, “but today supply chains are transforming into dynamic, interconnected systems. These digital supply networks integrate information from many different sources to drive production and distribution, potentially altering manufacturing’s competitive landscape.” Although they are correct that “digital supply network” (DSN) is a better description than “digital supply chain,” the term “supply chain” has deep roots in the business landscape and it will be hard to dislodge in short term. Whatever term you want to use for next iteration of the supply chain, Mussomeli and his colleagues believe committing to transform could be a life or death decision for companies. “This shift from linear, sequential supply chain operations to an interconnected, open system of supply operations,” they explain, “could lay the foundation for how companies compete in the future.”


The Digital Economy requires a Digital Supply Chain


“Today’s digital economy, where customers want tailored products delivered immediately via their preferred channel, is putting enormous pressure on companies to modernize their traditional supply chains,” writes Don Hnatyshin (@hnatyshd1), Senior Vice President and Chief Supply Chain & Procurement Officer for Jabil. “In addition to meeting the needs of the now generation, these new, digital supply chains must support macro trends such as globalization of manufacturing, new models such as the sharing economy, and the rise of Big Data and the Internet of Things (IoT).”[2] To his list of macro trends, I would add regionalization of supply lines and reshoring of manufacturing. New technologies are bringing the manufacture of personalized products closer to the ultimate consumer and shortening supply lines.


Frauke Heistermann, a Member of the Management Board at AXIT, told Adrian Gonzalez (@talkinlogistics), “IT is no longer just a tool where I type in data and a process is automated; IT in the age of digitalization becomes a major part of a company’s strategy, an enabler of success, which helps companies to differentiate themselves from the competition.”[3] Like Mussomeli and his colleagues, Heistermann believes a digital supply chain embraces the notion of a large supply ecosystem. “The next step,” she told Gonzalez, “is for companies to look [beyond their four walls] and find opportunities to improve the processes across their trading partner network. Therefore, it’s really important to take a broad look at your supply chain, not just have [an internal perspective].” The Deloitte analysts explain that companies must “focus more holistically on how the full supply chain can better achieve business objectives, while informing corporate, business unit, and portfolio strategies. Indeed, DSNs increasingly allow supply chains to become an integral part of strategic planning and decision making. To this end, organizations can develop and leverage multiple DSNs to complement different facets of their strategy and more effectively target specific needs.”


Cognitive Computing and the Digital Supply Chain


What Mussomeli and his colleagues are describing is a complex system needing orchestration. Fortunately, today’s cognitive computing systems offer a platform on which digital supply chains (and digital enterprises) can be built. As noted above, the Deloitte analysts insist digital supply networks must “integrate information from many different sources to drive production and distribution.” Cognitive computing platforms are excellent data integrators because they can handle both structured and unstructured data. Data integration is important because decision makers across an enterprise need to be working from a single version of the facts. Heistermann stressed the need to improve processes across the trading partner network. Cognitive computing systems can help automate data gathering processes across the network and leverage advanced analytics to both monitor and improve those processes. Cognitive computing platforms can also provide alerts to decision makers when anomalies occur and serve up actionable insights in a number of areas to help improve both efficiency and effectiveness.


Nicklas Brändström (@nicklasbrandst1), CEO of IBX Business Network, asserts cognitive procurement is one example of how smart technologies can help the digital supply chain. “Mobile, big data, and cognitive computing are trends that frequently overlap and will create the foundation for virtual assistants that are always available to help, no matter where we are,” he writes. “Cognitive procurement represents a future built upon efficiency and convenience.”[4] He elaborates:

“Thanks to new technologies, cognitive functions allow computers to perceive the world, analyze and understand the information gathered in a certain way, and then behave in an informed manner. When working in combination with business expertise, these IT solutions lead to a variety of valuable options, including machine learning applications, natural language question answering, and intelligent virtual assistants. When cognitive computing is applied to procurement solutions, the result is cognitive procurement, a process in which computers use data mining, pattern recognition, and natural language process (NLP) to mimic human activity concerning procurement processes. This cuts down on a great deal of manual work that would otherwise be required, cutting costs for your procurement team while also making it more efficient.”

Luca Urciuoli, an associate research professor at the Zaragoza Logistics Center, believes smart technologies can also help improve supply chain resilience. Urciuoli writes, “The digitization of supply chains is introducing new demands on company operations that require a different approach to building supply chain resilience. With the benefit of digital technologies, companies are using Big Data to identify supply chain risks and create early warning systems with much greater speed and precision.”[5] Unfortunately, Urciuoli insists the ability to respond to these signals has not advanced at the same pace. “Moreover,” Urciuoli writes, “the gap between risk identification and risk response promises to become more severe as the rate of digitization accelerates. … To keep pace with the changing landscape, companies need to develop ways to automate resiliency.” Cognitive computing platforms can help achieve automated resilience. He concludes, “The need to increase cyber resilience to speed response time must rely on improved automation and intelligent software.”




Hnatyshin concludes, “In the area of logistics, the benefits of a connected ecosystem are staggering. Data in isolation may not be particularly informative, but with connected information flowing from suppliers, manufacturers, retailers and other partners, companies can piece disparate facts and metrics together to tell a story or pinpoint a trend. … Reaping the benefits of structured and unstructured data need not wait for some distant future. … The convergence of Big Data, the IoT, analytics and digitization gives companies the opportunity to make significant changes in supply chain performance, efficiency and capabilities. Instead of incremental improvements, companies should be concentrating their efforts on achieving substantial change with improvement impacts of 20 percent and greater. This calls for radical alterations to business processes. Once a company starts on its journey, developing a digital supply chain platform and analytical capability is clearly paramount.” Mussomeli and his colleagues add, “Advancing to an ‘always-on’ DSN is not about a single technology implementation; it is more about developing an agile supply culture and promoting a more strategic approach to meeting customers’ needs. Investments in DSN technology and tactics can become key differentiators in not only supporting but also advancing business strategy.” I agree that digital supply chain transformation is about more than technology; but, without technologies, like cognitive computing, any transformation effort will be futile.


[1] Adam Mussomeli, Doug Gish, and Stephen Laaper, “The rise of the digital supply network,” Deloitte University Press, 1 December 2016.
[2] Don Hnatyshin, “Transforming the Supply Chain for Today’s Digital Economy,” Electronic Products and Technology, 27 December 2016.
[3] Adrian Gonzalez, “What’s New and Different About The Digital Supply Chain?” Talking Logistics, 4 January 2017.
[4] Nicklas Brändström, “Taking advantage of cognitive procurement,” Capgemini, 10 January 2017.
[5] Luca Urciuoli, “Automating Supply Chain Resilience Should Be High on Your Digital Agenda,” MIT Sloan Management Review, 20 January 2017.

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