Learning, Building on Experience: Enabling Cognitive Supply Chains

Article by Tom Serres

We live in a dynamic world with a global marketplace that reflects those ever-evolving qualities. Concepts that might seem like an absolute today could very well be an antiquated notion tomorrow. Customer affinities change on a whim, and traditional supply chains that are unable to keep up with such velocity and turbulence will ultimately prove to be inefficient and costly to all participants. Supply chains must be more cognitive in nature, building autonomous networks that learn as they go and grow in flexibility to keep up.

The critical component to a supply chain framework that not only adequately serves a volatile marketplace but can thrive under such conditions is agility. Logistical networks must be nimble to account for the unexpected – whether that’s adverse weather conditions that disrupt distribution channels, diminished production capacity to machine error, or merely changing interests and tastes from a customer base. Cognitive supply chains that can quickly and effectively absorb all such variables – learning as they go – are not only the best solution but likely the only one that can evolve in lockstep with modern commerce.

The Weakest Link

Individual, innovative, but isolated solutions are already available in the marketplace, lending greater efficiencies to particular components of supply chains. However, these innovations are not part of a more comprehensive, wide-sweeping solution set that creates end-to-end efficiencies. Therefore, they still do not provide the intelligent, agile, and connective answers required to make positive, demonstrable improvements along the entire spectrum of supply chains.

For instance, companies have already introduced ways to make segments of supply chains smarter through innovations like transportation management systems (TMS) and enterprise resource planning (ERP). Although these types of solutions provide a higher degree of intelligence to supply chains through algorithms, machine learning, and computational tools to automate essential processes, they are in essence streamlining the traditional models of supply chains without lending them broad sweeping technologies sufficient in scope and autonomy to allow them to learn.

That isn’t to say, however, that these innovations won’t play a pivotal role in ultimately making supply chains cognitive and intelligent enough to learn through repetition. In fact, by implementing these individual components of smart technology, supply chains are laying a critical foundation to serve as the proper connective tissue linking these components – primarily through blockchain-based solutions. For the time being, though, today’s supply chains are still limited by their weakest links. No matter how smart, fast, or flexible individual portions of the framework become, supply chains will still bottleneck information and inhibit efficiencies unless given complete autonomy. To get beyond these limitations, we need properly autonomous networks.

A Cognitive Supply Chain That Serves Multiple Functions

Traditional logistical frameworks evolving into cognitive supply chains is an inevitability. E-commerce will only continue to become more immediate and ubiquitous, with supply chains smart and flexible enough to account for such demands. With foundational components in blockchain, IoT, additive manufacturing, and AI already being integrated into modern supply chains, a solid footing continues to take shape that autonomous, automated, cognitive networks will build from.

Once that framework is in place, cognitive supply chains will function within three core areas – intelligent decision-making, data-gathering and automated execution, and the maintenance of network state. As it stands, isolated, segmented technologies like enterprise resource planning systems, smart algorithms, and both industrial and nonindustrial machines manage those functions separately. Human beings currently act as the conduit that allows data and, more importantly, the decisions made based on that data to funnel through the smart but not cognitive networks.

As AI technology continues to advance, however, there will come a point in time where intelligent AI’s work autonomously, serving as superior replacements for human beings as that conduit that empowers the systems to make decisions and allows them to learn. Blockchain technologies will provide the secure communication and distribution of sensitive data throughout the cognitive supply chains to build autonomous networks, creating the necessary machine trust for them to function efficiently and effectively.

Building a Truly Open Market

Information silos and communication gaps that plague traditional supply chain models will become a thing of the past as cognitive networks fully leverage the collective power of intelligent technology, big data, and instant communication. Together, these innovations will completely redefine how economies conduct trade. From a microeconomic perspective, modern organizations with supply chains best able to successfully navigate the crowded and complicated waters of digital commerce will be those rewarded with success.

Once intelligent, cognitive supply chains work autonomously, winners and losers will be separated by those with supply chains most capable of quickly learning relative to innumerable variables and, most significantly, making sound decisions based on the data and lessons learned. Given the prescient abilities of AI-based systems, that sound decision-making will not only be based on current information and demand but on shifting consumer affinities as well.

Successful organizations will be those with cognitive supply chains that can effectively look down the road and accurately predict what consumer behavior and the resulting marketplace will look like in the future. Autonomous networks will always have one eye on current demand and the other firmly placed on what’s to come.

To learn more, download the Animal Ventures Assets Chain report.