“Manufacturing supply chains are experiencing levels of change heretofore unprecedented in their history,” writes Richard Howells (@howellsrichard), a Vice President at SAP.[1] He draws that conclusion from a white paper published by IDC Manufacturing Insights entitled “The Extended Supply Chain.” Howells explains, “In the paper, author Simon Ellis posits that the future of the supply chain is ‘one of an outwardly networked and collaborative organization that fully integrates supply chain with design, manufacturing, and asset management into an “extended” supply chain that is able to respond quickly and accurately.’” In other words, Ellis concludes that supply chains are going to get smarter. That improved “smartness” will come from collaboration between humans and cognitive computing systems. Jeff Bodenstab, Vice President of Marketing at ToolsGroup writes, “In today’s complex demand and replenishment environment, the need to consume and leverage increasing amounts of data clearly favors the use of more machine intelligence — to better sense and shape demand, and to adapt supply to shifting consumption and replenishment needs.”[2] Nicole Snyder, brand and marketing manager for JW Aluminum, agrees that “manufacturers need to shake off the traditional commodities mindset and embrace the idea of an intelligent supply chain.”[3] And Dave Blanchard (@SupplyChainDave) asserts, “AI has subtly but forcefully become a part of everyday, real-world life.”[4]

Although manufacturing is one area where cognitive computing is taking hold, Nathalie Fekete (@Nath_Fekete), an IBM logistics and supply chain expert, asserts that cognitive computing has much broader application in the business world. “Artificial Intelligence (AI) technologies are no longer the realm of science fiction,” she writes, “nor the sole domain of computer scientists and techies. AI is increasingly being applied by forward-looking companies across almost every industry — from healthcare and finance to consumer products and technology. AI, also known as cognitive computing, is being applied to solve a range of problems and manage tasks.”[5] Fekete describes a few ways that cognitive computing can help organizations. They include:

• Quickly sorting through very large amounts of structured or unstructured data
• Providing very detailed supplier assessments of a single supplier, a group of suppliers or your supply base
• Providing in-depth risk assessments, identify hidden risks, and calculate rate risks
• Elevating procurement professionals and extend their experience
• Supporting and validating decision-making
• Innovating, finding new ways of operating, providing new insights, uncovering new opportunities

One thing Fekete failed to mention is that cognitive computing systems can help integrate data across an enterprise helping it achieve alignment and breaking down information silos that have characterized industrial age organizations for decades. Lora Cecere (@lcecere), founder and CEO of Supply Chain Insights, insists, “The siloed organization is insular. It cannot sense, and is slow to adapt.”[6] By breaking down silos, companies can think more horizontally. Cecere explains, “Horizontal processes within the supply chain organization help to align and orchestrate demand and supply to deliver on the business strategy. Effective design of horizontal processes reduces silo friction and improves organizational cross-functional alignment. It enables growth.” She also recommends that organizations transform their planning from inside out to outside in. “An outside-in process design,” she explains, “starts at the market and uses channel data to sense and then shape demand opportunities while mitigating risks through cross-functional, horizontal processes. It is designed using optimization and simulation tools, and the network design processes are iterative on a monthly basis to improve the end-to-end set of horizontal processes.”

To achieve the objectives Cecere has in mind, an enterprise needs something like the Enterra Enterprise Cognitive System™ (ECS) — a system that can Sense, Think, Act, and Learn®. Cognitive computing combines artificial intelligence, advanced mathematics, and natural language processing. It can be applied to an almost unlimited number of business use cases. The pundits cited above note that modern supply chains must be able to respond quickly and accurately and be adaptable. Martin Christopher, an Emeritus Professor of Marketing and Logistics at Cranfield University, calls such supply chains “agile.” He insists that supply chains must be agile because they constantly confront changing conditions. “Companies operating in every industrial sector and in every market around the world,” he writes, “are facing significant challenges, ranging from economic recession to demographic shifts and geo-political upheavals, to name but a few.”[7] Like Cecere, Christopher believes that horizontal thinking can help make companies more agile. He calls it “looking past functions.” He explains, “For centuries, organizations have followed an organizational logic based upon a division of labor where activities take place within functions or departments. While this functionally-based organizational concept may ensure the efficient use of resources, it creates a silo-type mentality. As a result, companies are slow to respond to changes in the market or business environment. Companies that respond rapidly to changing customer requirements tend to focus more on managing processes. Processes are the horizontal, market-facing sequences of activities that create value for customers. They are cross-functional by definition and are usually best managed through inter-disciplinary teams.”

In addition to helping break down silos, cognitive computing systems can help improve processes. In fact, cognitive computing systems can be used to automate many of the processes that are prone to errors because human workers find them tedious and boring. Cognitive Process Automation™ goes beyond robotic process automation in that it can actually help improve processes not just carry them out in the same way they have always been accomplished. As Bill Gates once noted, “The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.” Cognitive computing systems can also provide predictive analytics. Blanchard explains:

“Predictive analytics refers to the ability of computers to crunch through enormous amounts of data (Big Data) and make sense of it all. As a Deloitte/MHI report explains, when applied to supply chain problems, predictive analytics ‘allows managers to manage inventory better, plan more reliable transportation networks and reduce variability in lead times. This can enhance service levels, lower costs and improve the bottom line.'”

Bodenstab concludes, “I see this technology evolving not unlike others that preceded it — into a combination of human and machine skills, leveraging what each does best, to increase productivity and free planners from the daily crunch to manage exceptions, think forward, and focus on value-added activities. Both companies and planners are much better off.”

Footnotes
[1] Richard Howells, “Top 3 Drivers Of Supply Chain Transformation,” D!gitalist Magazine by SAP, 20 January 2016.
[2] Jeff Bodenstab, “Ex Machina: AI and the Future of Supply Chain Planning,” ToolsGroup, 12 January 2016.
[3] Nicole Snyder, “Improving Competitive Advantage with an Intelligent Supply Chain,” IndustryWeek, 24 March 2016.
[4] Dave Blanchard, “A Smarter Way to Run a Supply Chain,” IndustryWeek, 26 June 2016.
[5] Nathalie Fekete, “What Can Artificial Intelligence Do for You?” Procurement Leaders, 20 June 2016.
[6] Lora Cecere, “Go Horizontal!” Supply Chain Shaman, 21 June 2016.
[7] Martin Christopher, “Want to Thrive in Disruptive Times? Start With an Agile Supply Chain.” Longitudes, 28 February 2016.