Industry 4.0 is here.
Many observers foresee dramatic upheaval on the short-term horizon for supply chain management (if the Harvard Business Review article “The Death of Supply Chain Management” is any indication) as traditional management is transformed by seamlessly interconnected digital information networks. Supply chain research, however, has thus far not adapted to accommodate the accelerating pace of change. Until now, most meaningful research on the impact of digitalization has been done in the realm of computer science and information technology, not in the business realm.
Ted Stank, a professor in the Haslam College of Business at the University of Tennessee, Knoxville, believes that should change. Now is the time, he and his co-authors argue, to jump with both feet into this new universe of unknowns.
They’ve proposed a framework—the Digitally Dominant Paradigm (DDP)—to help supply chain management researchers pivot to a new way of thinking. This framework is based on middle-range theory (MRT)[1], which limits scope and variables to observable empirical relationships or phenomena within the focal discipline.
In the case of supply chain, the authors suggest exploring how digitalization might affect each known relationship, focusing specifically on how, why and when these relationships may or may not apply when exposed to the intermediary effects of the new digital reality. To do this effectively, researchers must make a whole new set of assumptions about the discipline, including 1) nearly limitless supply (thanks to online retailers like Amazon), 2) abundant technology (as all companies have access to sophisticated technology and real-time data) and 3) a collaborative—rather than adversarial—posture among supply chain entities. All of these ideas are reversals of long-held assumptions established in the analog age.
Applying this framework will naturally point to places that academic research could be producing deeper contextual work and lead to the formation of testable hypotheses.
Time-based fulfillment strategies provide an example of a relevant place to apply the DDP. Should a firm postpone creation of a product or service until after the customer demands it or create it in advance, at the expense of holding inventory? The digitalization of commerce is already dramatically altering the ways companies approach this decision, mainly by affecting the way managers see, think and act. To illustrate:
Seeing: Digitalization—such as social media data and immediate online order capture—enhances visibility by improving the quality of demand information up and down the supply chain. Sharing information is now the norm because it benefits the sharer as well as the recipient. That means demand itself is easier to pinpoint, as well as its location and timing, and managers can respond faster to unanticipated problems. This decreases the need to postpone product or service creation.
Thinking: Artificial intelligence (AI) and increased analytics capabilities make predicting the future far more reliable. AI can even prescribe solutions in real time for problems that appear by sending diagnostic tools or work instructions straight to the shop floor or by answering complex international trade questions for shipping personnel at the point they arise. Depending on the supply chain involved, this may make speculative creation of value the most effective way to operate, or it may enable a firm to allocate capacity more accurately for a response-based strategy.
Acting: Automations such as robotics, 3-D printing and drones make shifting tasks exponentially easier, faster and cheaper with fewer errors. As technology evolves, it may become even cheaper and easier to locate these automations nearer to the end customer. This creates an incentive to postpone fulfillment.
What does all this mean? Typical tradeoff calculations no longer apply. As you can see, digitalization provides incentives in both directions, leading to two researchable propositions:
1) Firms in digital supply chains are more likely to speculate than firms in analog supply chains because improved quality of data makes predicting demand the most profitable solution, and
2) Firms in digital supply chains are more likely to postpone than firms in analog supply chains because improved information enables them to customize products closer to the moment of consumption.
Many fascinating questions like these are long overdue for exploration by academic researchers applying rigorous scientific inquiry to the field of supply chain management. The answers can provide immediate value for organizations looking to revamp their business models through digitalization. Applying the DDP to the entire range of supply chain relationships and phenomena is critical to challenging long-standing assumptions and finding out which will survive in the world of Industry 4.0.
This article is based on research by Ted Stank (the University of Tennessee, Knoxville), Terry Esper (The Ohio State University), Tom Goldsby (the University of Tennessee, Knoxville), Chad Autry (the University of Tennessee, Knoxville) and Walter Zinn (the Ohio State University), forthcoming in International Journal of Physical Distribution & Logistics Management.
[1]Stank, T.P., Pellathy, D., In, J., Mollenkopf, D., & John Bell. “New Frontiers in Logistics Research: Theorizing at the Middle Range,” Journal of Business Logistics, Vol. 38, No. 1, pp. 1–12, 2017.