The Emergence of the Cognitive Supply Chain

Stephen DeAngelis

August 16, 2016

Nearly a year ago I laid out my vision of what supply chains might look like in the future.[1] With the Supply Chain Insights Global Summit nearly upon us, a conference Enterra Solutions® is helping to sponsor, I thought it would be a good time to revisit the subject since the theme of the conference is “Imagine: The Supply Chain in 2030.” As I noted in my previous article, the word “imagine” is powerful. It releases us from daily constraints. It stretches our thinking. It sparks our creative juices. Imagination can help us envision a situation in which we would like to find ourselves; it just doesn’t tell us how to get from here to there. A year ago it took some imagination to envision a cognitive supply chain because discussions about cognitive computing, digital transformation, robotic process automation, and the Internet of Things (IoT) were still fairly new. During this past year, many of those subjects have received a lot more attention. At the beginning of this year, IBM CEO Ginni Rometty (@GinniRometty) asserted, “It is the dawn of a new era, the cognitive era.”[2] She defined the cognitive era as one in which “digital business” will be enhanced by “digital intelligence.” Vinodh Swaminathan, KPMG’s Managing Director of Innovation and Enterprise Solutions, agrees. “The cognitive systems era, which is the most exciting phase of enterprise transformation in more than a century, is upon us,” he writes. “Cognitive software mimics human activities such as perceiving, inferring, gathering evidence, hypothesizing, and reasoning. And when combined with advanced automation, these systems can be trained to execute judgment-intensive tasks.”[3] It doesn’t take much imagination to realize cognitive supply chains might look different than today’s supply chains. They will still be involved with movements of goods from raw material to final products, but the processes used will much more automated and efficient.

Digital Transformation

As I noted a year ago, the discussion about “what a supply chain could be” needs to start at the enterprise level. As Lora Cecere (@lcecere), founder of Supply Chain Insights, has written, “The supply chain IS Business, not a department within a business.”[4] Ken Corless (@kfcwork), a principal at Deloitte Consulting LLP, briefly explains the objective of becoming a digital enterprise. He writes, “‘Digital.’ ‘Digitization.’ ‘Digitizing the business.’ These terms are a popular rallying cry inside IT organizations these days. Deloitte Consulting LLP describes a digital enterprise as one that integrates people, processes, and capabilities to deliver an omnichannel experience, enabling organizations to reimagine how profits are made and to reshape how work gets done.”[5] He adds, “For CIOs, enabling digital business is less about selecting and implementing particular new technologies than about applying those technologies in new ways to align with business objectives. Digital is shaping up to be the next great wave of business transformation.” Although most companies recognize they need to transform into digital enterprises, many of them are struggling with where to start. My recommendation is that they start with the supply chain. I’m not alone in that assessment. Patrick Burnson reports, “According to a study by Capgemini Consulting and GT Nexus, an Infor company, 70% of [surveyed] executives have started a digital supply chain transformation.”[6] Burnson adds, “The expected benefits of Digital Supply Chain Transformation include, but go well beyond cost reductions for logistics, inventory and maintenance, improvements in customer service and higher overall equipment effectiveness. Perhaps more importantly, Digital Supply Chain Transformation is expected to dramatically improve an organization’s agility.”

The Internet of Things

It is no coincidence that the emergence of the Internet of Things and the maturation of cognitive computing is happening simultaneously. Artificial intelligence involving machine learning requires a lot of data and the IoT is going to provide more than enough of that. General Electric believes that the IoT will have such a significant impact on the business landscape that it calls it the Industrial Internet. The amount of data that will be generated by the IoT in the years to come will dwarf what we today call “Big” Data. What appears to be oceans of data today will seem like small ponds in the years ahead (see my article entitled “The Internet of Things and Really, Really Big Data“). Mark Morley (@MarkMorley), Marketing Technologist for OpenText, suggests there are “three areas where IoT will add value to supply chain operations.”[7] He calls these areas “the ‘Three Ps’ of supply chain focused IoT, namely Pervasive Visibility, Proactive Replenishment and Predictive Maintenance.” Puneet Pandit, founder and CEO of Glassbeam, believes that advanced analytics are the key to IoT success and to supply chain transformation. “Innovative supply chain managers,” he writes, “are leveraging real time analysis to improve customer service, reduce the cost of that service, improve inventory control, and even identify new services with a potential to increase revenue.”[8]

Cognitive Computing

Diego Lo Giudice (@dlogiudice), an analyst with Forrester, believes that a quarter of a century from now cognitive computing will have replaced artificial intelligence as the term most used to describe smart machines.[9] Lo Giudice and his colleagues at Forrester conclude, “Cognitive systems are creeping into commercial relevance beginning with high-end customer engagement applications in financial services, healthcare, and retail and will become ubiquitous in mainstream scenarios and the Internet of Things within five years.” In Accenture’s latest technology vision entitled “From Digitally Disrupted to Digital Disrupter,” Accenture analysts state that cognitive computing will provide the “ultimate long-term solution” for many business challenges. Nathalie Fekete (@Nath_Fekete), an IBM logistics and supply chain expert, explains, “Artificial Intelligence (AI) technologies are no longer the realm of science fiction, 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.”[10] 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. Breaking down these silos is important. Cecere insists, “The siloed organization is insular. It cannot sense, and is slow to adapt.”[11] By breaking down silos, companies can think more horizontally.

The Cognitive Supply Chain

As Burnson noted above, one of the characteristics of a digital enterprise and its supply chain will be agility. Martin Christopher, an Emeritus Professor of Marketing and Logistics at Cranfield University, agrees with Burnson that corporate agility is important and he believes cognitive supply chains will be 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.”[12] 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.” Two other important areas where cognitive computing is poised to make a difference are supply chain risk management and predictive analytics. Perhaps no area requires more variables to be analyzed than supply chain risk. All of the data involved in normal supply chain visibility must be monitored along with current events, environmental conditions, political unrest, natural disasters, and so forth. Emerging and long-term patterns must be considered. Cognitive computing can help make connections between variables and provide better alerting than manual processes. Monitoring is essential because companies can’t influence or control many of the potential sources of disruption.

Concerning predictive analytics, most analysts see this as a game-changer. Cognitive computing can analyze many more variables than current systems and are, therefore, able to make predictions with greater accuracy than the forecasts many businesses now use. Better predictions can help eliminate things like the dreaded Bullwhip Effect. Predictions generated from data will help improve decision-making in every department of an enterprise. Lo Giudice concludes, “What’s surfacing from Cognitive computing these days is only the tip of the iceberg, much more will be coming. Cognitive computing has long-term goals, spanning over a decade or more. It will solve a class of new problems we have not even yet thought of. … If you get involved in cognitive computing, you should get in for the long run. Yes you can get some spot business solutions going, but the big reward is going to take more investment and time.” As I noted a year ago, the big reward will be a cognitive supply chain.

Footnotes
[1] Stephen DeAngelis, “Imagine: A Cognitive Supply Chain,” Enterra Insights, 19 August 2015.
[2] Mike Snider, “IBM’s Rometty heralds dawn of ‘cognitive era’, inks new Watson deals,”USA Today, 7 January 2016.
[3] Vinodh Swaminathan, “Embracing the Cognitive Era,” KPMG, 22 January 2016.
[4] Lora Cecere, “Sage advice? Only for turkeys.” eft, 1 February 2013.
[5] Ken Corless, “The CIO’s Digital Mandate,” The Wall Street Journal, 28 April 2016.
[6] Patrick Burnson, “The Current State of Digital Transformation across Extended Global Supply Chains,” Supply Chain 24/7, 8 April 2016.
[7] Mark Morley, “How IoT Based Analytics Will Drive Future Supply Chain Operations,” OpenText Blogs, 1 September 2015.
[8] Puneet Pandit, “IoT Analytics Brings Unprecedented Triage to Supply Chain,” EBN, 17 November 2015.
[9] Diego Lo Giudice, “Three assumptions for why the next generation of software innovation will be cognitive,” Computerworld UK, 28 August 2014.
[10] Nathalie Fekete, “What Can Artificial Intelligence Do for You?Procurement Leaders, 20 June 2016.
[11] Lora Cecere, “Go Horizontal!Supply Chain Shaman, 21 June 2016.
[12] Martin Christopher, “Want to Thrive in Disruptive Times? Start With an Agile Supply Chain.Longitudes, 28 February 2016.