Most of the news coverage surrounding recent supply chain crises has focused on retailers failing to keep their shelves stocked. The consumer’s pain felt at the shelf was so visceral and so thoroughly covered by the media that it often overshadowed the very real supply chain challenges faced by manufacturers as they struggled to meet demand.
In May 2021, the manufacturing sector reached a record high on its Backlog of Orders Index, at 70.6%, while Backlog of Services peaked at 65.8% in June that same year. The Covid-19 pandemic created a vicious cycle—labor shortages, raw material shortages, production delays, increased costs, and shifts in demand, all of which culminated in many manufacturers folding, being absorbed by competitors, or simply unable to fulfill orders.
There’s still volatility today, and macroeconomic conditions have further underscored the need for innovations that increase supply chain visibility. A global pandemic, instability in Eastern Europe, climate crises, forest fires, hurricanes, even the recent threat of a UPS strike add to fluctuations in supply and demand and the ability to deliver, increasing risk of bottlenecks in global supply chains.
Supply chain visibility is needed at every point in the value chain, whether raw materials, goods being shipped, inventory at hand or elsewhere. Advances in AI and Machine Learning are starting to enable a more flexible and transparent supply chain, which can help manufacturers weather volatility in a way that forward-thinking retailers are beginning to use.
How Digital Twins Can Provide Value
At the cutting edge of these advances are Digital Twins, virtual representations of the supply chain that leverage real-time data to accurately know the position of goods on a real time basis, and predictive analytics to optimize operations. With a digital twin, organizations no longer have to wait multiple days to update their inventory status; instead, there’s instant visibility into the entire cache of products and where they are located.
For manufacturers, digital twins increase efficiency by seeing inventory in real time, creating visibility into decision postponements, updating possible alternative transportation models, and updating or rethinking the possibility of shipping not only from warehouse to stores but directly to the consumer. A digital twin creates the ability to analyze scenarios and sense not only external changes but any internal changes in the system, enabling it to suggest alternatives. This technology is still in its nascency but will be gaining in importance as its benefits are better understood.
The ideal digital twin not only communicates frequently but comes out of the box ready to make an immediate impact. In a global supply chain that has seen exponential growth in ecommerce, digital twins will soon become a necessity.
Changes in Purchasing
What has precipitated the need for this higher level of visibility? Organizations must increasingly be able to adjust to today’s complex, interconnected retail market. Previously, items were both sold and fulfilled to a customer through one channel. Now the customer can choose to purchase an item through multiple channels—the web, social, mobile, wholesale, in-store, or marketplace.
These purchasing methods, multiplied with the many new fulfillment channels—local delivery service, ship to store, ship from store, warehouse, BOPIS, and dropship—have created a modern supply chain that is too multifaceted to comprehend manually. Additionally, product development, manufacturing, transportation, and ultimately consumption now span many international borders. These more interwoven and complex supply chains create greater ramifications if any link in the chain is broken. Automation is needed to account for more variables than the human mind has the capacity for.
Manufacturers might see this as a problem on the retailer's end—supply chain on the manufacturer’s end has usually been more traditional, based on a combination of previous orders and a supply chain manager’s instincts and experience. In short, it has been less tech driven. However, in today’s complex demand environment, and as manufacturers move toward the Direct-to-Consumer (D2C) business model, this approach is increasingly outdated.
According to Diffusion's 2020 Direct-to-Consumer Purchase Intent index, 25% of American consumers were making nearly one-fifth of their purchases from D2C brands. If manufacturers want to meet the needs of today’s brisk and complex marketplace, they need to take the data-driven, AI and machine learning approach to supply chain that some retailers have started to champion.
Modern, successful manufacturers looking to break into the Manufacturer-to-Consumer (M2C) model are investing in data unification to deal with this interwoven market, on the premise that piecing together many dissimilar systems can cripple an organization’s potential. As retailers know all too well, a disjointed supply chain indeed often results in a negative customer experience: inventory unavailable to purchase, inconsistency across channels, and canceled orders. A piecemeal approach to modernization often results in additional operation complexity, which means higher costs, low fulfillment rates and a dependency on manual processes—all of which can lead, unsustainably, to waste.
Real-time Data
Digital twins can help. Both supply chain managers and customers benefit from the incorporation of real-time data. Real-time data empowers companies to provide better customer service and meet customer expectations. With real-time visibility into inventory levels, manufacturers and retailers can ensure product availability and reduce delivery lead times. In addition, by analyzing demand data in the moment, retailers use the resultant insights to personalize their offerings, anticipate customer needs, and provide a more seamless and tailored experience. This translates directly upstream to manufacturing, wherein if demand can be anticipated, sourcing of materials and components can be that much more accurate and waste-free.
Therefore, even if a manufacturer has no desire to pivot to M2C, technology that increases supply chain visibility can still greatly benefit the organization. In choosing a supplier, advanced analytics can factor in cost, lead time, and transportation options to land on the optimal supply partner. Increased transparency means manufacturers and suppliers no longer have to play the blame game when dealing with logistical challenges.
The dashboard will pinpoint the inefficiency and who is responsible for remedying it. Counterintuitive though it may seem, taking out the human touch in this case can improve collaboration between supplier and manufacturer. Another value in real-time, advanced analytics is in the identification of alternative transportation routes and methods. The pandemic, the war in Ukraine, and extreme weather patterns and climate crises have brought this to the fore, as these systems have been able to create in-depth models for geopolitical, environmental, or global health challenges. When the next global supply chain crisis occurs, a data-driven approach stands to provide something of a safety net.
While increased supply chain visibility boosts profitability, it also creates sustainable business practices. AI-powered demand forecasting lessens a manufacturer's carbon footprint by decreasing waste. Enhanced supply chain visibility also allows manufacturers to trace the origins of raw materials. By having a clear view of the entire supply chain network, manufacturers can ensure compliance with sustainability regulations. In 2023, profitability is increasingly entwined with ethics—improved supply chain visibility allows manufacturers to accurately convey their sustainability initiatives and achievements to both retailers and consumers.
Next-generation supply chains will leverage machine learning and technologies such as digital twins to boost visibility. Increased transparency will foster improvements in forecasting, inventory management, sourcing raw materials, and sustainability. Manufacturers should embrace these changes—it’s a fact that every instance of global volatility has led us, of necessity, to more resilient, efficient, and future-proof supply chains.
Inna Kuznetsova is CEO of ToolsGroup, a supply chain planning and optimization firm.
