Digital Supply Chains and the New Normal

Stephen DeAngelis

March 18, 2021

Over the past year there has been a lot of talk about the “new normal.” With vaccines being rolled out, infection rates coming down, and an end of the pandemic within sight, it’s time to talk seriously about the new normal and how it will affect supply chains. Ilya Katsov (@ikatsov), head of data science for Grid Dynamics, asserts, “The Coronavirus disease (COVID-19) pandemic has been the biggest disruptor of supply chain operations since the 1940s.”[1] The disrupter in the 1940s was, of course, the Second World War. It took a concerted global effort following the war to reach a “new normal” and those efforts were neither easy nor quick. Hopefully, reaching a new normal following the pandemic won’t take as long; however, it still won’t be easy and it will, once again, take a concerted global effort. Shubho Chatterjee, a digital transformation, strategy, technology and operations executive, insists the new normal will hasten the requirement for digital supply chains at a pace many companies and workers will find challenging. He explains, “COVID-19 has accelerated digitization of the workplace giving precious little time for the workforce to react, learn and progress.”[2] He believes organizations face a threefold challenge:

 

  • A younger pool of entry and mid-levels entering the workforce;
  • A mature workforce; retire-ready within the next few years taking their expertise and knowledge with them; and,
  • Rapid advances in new technology and capabilities, such as cloud and A.I.
 

A younger pool of employees, most of whom will be tech savvy, could be a good thing; however, losing the mature workforce and the knowledge they have garnered over their careers could be a bad thing if that knowledge is not captured. Chatterjee adds, “Despite the challenges, organizations have embraced technology and accelerated digitization. This acceleration in the use of technology, digitization and new forms of working will continue to be sustained. It has been reported that, as a result of COVID-19, organizations have moved 20- to 25-times faster than thought possible on building supply-chain redundancies, improving data security and increasing use of advanced technologies in operations and services.”

 

Technology trends transforming supply chains

 

If Chatterjee is correct about the rate of transformation and the need to reskill the supply chain workforce, business executives need to understand the technologies driving these changes so they can future-proof their organizations. Katsov identifies five technology trends he believes will play a significant role in supply chain transformation. They are:

 

  1. New data and methods. “In 2020,” Katsov explains, “managers of supply chains and inventories had to work through numerous shocks related to lockdowns, reopenings, shifts in consumer behavior and economic downturns. These efforts were widely supported by analytics tools and data science teams that adjusted forecasting and optimization models to account for unprecedented shocks. Many of these adjustments were implemented using new signals and data sources not normally used before the pandemic such as seasonal influenza statistics, international data, macroeconomic data for the major crises of 2000 and 2008, and so on. These developments will continue in 2021, and many of the techniques and improvements adopted during the pandemic are likely to be around for a long time.” At Enterra Solutions®, we certainly found this to be true. In order to help clients cope with changes brought about by the pandemic, we developed the Enterra Global Insights and Optimization System™ that created new ways to combine and analyze data to reveal how the pandemic was changing the business environment.
  2. Integrated decision support tools with predictive components. Bain analysts, Michael C. Mankins and Lori Sherer (@lorisherer), assert, “The best way to understand any company’s operations is to view them as a series of decisions.”[3] They add, “We know from extensive research that decisions matter — a lot. Companies that make better decisions, make them faster and execute them more effectively than rivals nearly always turn in better financial performance. Not surprisingly, companies that employ advanced analytics to improve decision making and execution have the results to show for it.” Katsov adds, “Although decision support tools and predictive models have been widely adopted in supply chain management, it is often a challenge to develop integrated solutions for complex chains that have multiple types of warehouses (e.g., for regular, bulky or perishable products) and multiple distribution channels and service level agreements (e.g., regular or same-day delivery).”
  3. Adoption of prescriptive methods. There are four types of analytics: 1) Descriptive Analytics (i.e., what happened in the past); 2) Diagnostic Analytics (i.e., why something happened); 3) Predictive Analytics (i.e., what can happen next); and 4) Prescriptive analytics (i.e., what you should do to achieve a particular outcome). In today’s fast-moving business environment, all four types of analytics are required; however, prescriptive analytics are fairly new. Katsov predicts companies will increasingly adopt cognitive technologies with prescriptive capabilities. He writes, “Manual analysis of forecasts and other predictive outputs will be replaced by systems that have a higher level of automation and combine statistical, econometric and risk scoring models to make decisions more autonomously.”
  4. Adoption of simulation and reinforcement learning methods. According to Katsov, “Simulation-based methods and advancements in reinforcement learning enable optimization using simpler procedural models of the supply chain environment that unlock new levels of decision automation. However, this approach has its own challenges because the number of decision variables and entities that participate in the process are typically extremely high.” Cognitive technologies can handle many more variables than older systems and can conduct multiple “what if” exercises much faster than such exercises could be conducted in the past. Another simulation technology of interest is digital twin technology. John Gomez, a supply chain automation specialist with 6 River Systems, explains, “A digital supply chain twin is a digital model of a real-world entity or system. It represents all relationships between every entity in the real-world supply chain from end-to-end, including customers, warehouses and distribution centers, manufacturers, logistics providers, markets, weather and more. Combining the ideas of IoT and modeling, it uses sensors to gather data which feeds the digital supply chain replica. … Digital twins serve as proxies for their real-world counterparts. Programming a twin to encapsulate data allows analysts and supply chain leaders to make changes to the twin without impacting any connected applications, and likewise, changes to connected applications without affecting the twin. Supply chain leaders can apply prescriptive analytics and AI to a digital twin to enhance situational awareness and support better, faster decision-making — either by augmenting human decision-making or automating the decision-making process entirely.”[4]
  1. Omnichannel operations. Katsov notes, “Over the last few years, many B2C companies have adopted omnichannel capabilities such buy-online-pickup-in-store (BOPIS), and many B2B businesses have either developed their own e-commerce platforms or integrated with marketplaces. These developments have elevated the role of omnichannel inventory management and introduced additional challenges and complexities.” Despite the challenges and complexities, organizations that master omnichannel operations will thrive in the years ahead.
 

Other technologies Gomez believes supply chain professionals must be familiar with include: Cloud technology; the Internet of Things; robotics (including driverless vehicles and drones); 3D printing; and blockchain.

 

Concluding thoughts

 

With all the talk about digital supply chains, autonomous supply chains, and the need to upskill the workforce, Chatterjee notes, “There is fear that human workers will be automated out of the workforce.” He reports, however, “The growing consensus is that A.I. and humans can leverage complementary strengths and effectively augment each other. People and organizations that will understand how A.I. fits within workflows and how people can work collaboratively with algorithms will be more competitive than those that are unable to do so.” With new technologies being introduced at an astonishing pace, supply chain professionals need to be lifelong learners.

 

Footnotes

[1] Ilya Katsov, “5 Trends in Supply Chain Analytics and Optimization in 2021,” Supply & Demand Chain Executive, 15 February 2021.
[2] Shubho Chatterjee, “The New Normal Will Require New Digital Skills,” SupplyChainBrain, 7 February 2021.
[3] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.
[4] John Gomez, “Ultimate Guide To Technologies That Are Transforming Supply Chains,” LogiSYM Blog, 16 February 2021.