Global supply chains are operating in a constant state of flux where traditional approaches don’t work anymore. The need of the hour is to swiftly access alternative suppliers, distribution channels, or fulfillment partners, adapting to rapidly changing market dynamics. In this article, we explore how shifting from linear models to a connected, cognitive, and responsive supply chain network can boost visibility, collaboration, and, ultimately, resilience.
Supply chains worldwide continue to grapple with economic uncertainties, geopolitical tensions, and unpredictable demand shifts. Events like COVID-19, canal blockages, and fluctuating demand have only highlighted the vulnerabilities within traditional supply chains. In response, companies have focused on improving visibility, agility, and collaboration, as well as adopting multi-shoring, onshoring, and nearshoring practices. Despite these efforts, increased complexity and macroeconomic challenges continue to pose issues like latency and lag.
In addition, the unpredictability of demand has added urgency to the need for real-time decisions. Last month’s shipment data can’t address the sudden demand boost triggered by a social media post – companies need weekly or even daily sales visibility to improve forecasting accuracy and react swiftly to changes in demand. It is no longer enough to make supply chain decisions sequentially; rather, there is a need to know everything simultaneously—a comprehensive, real-time understanding of events to respond swiftly and efficiently to market changes.
Traditionally, supply chains have used siloed solutions and control towers to manage specific issues. However, the trend is moving towards supply chain orchestration that provides a holistic view integrating all parts of the enterprise – both horizontally across functions and vertically with partners.
IDC predicts that by the year 2028, 35% of G2K companies will use supply chain orchestration tools to improve responsiveness by 15%.
Source: IDC FutureScape: Worldwide Supply Chain 2024 Predictions
Think of supply chain orchestration like the body’s proprioception. When you’re walking or running and step on a bump, your body instantly knows what’s happening and adjusts to prevent injury. Supply chains, however, aren’t quite there yet. They don’t have that immediate, comprehensive awareness to make integrated, intelligent decisions.
But technology is catching up. We’re moving towards end-to-end and vertical integration, allowing for greater responsiveness. This means our supply chains can start to function more like that proprioceptive system, with real-time adjustments and scenario modeling. We’re beginning to balance factors like sustainability, cost, and execution more effectively, aiming for optimized decisions rather than constant trade-offs.
A higher degree of orchestration would make supply chains more adaptive and resilient, but that road is not without challenges.
Supply chain orchestration requires each element in the value network—from suppliers and channel partners to warehouses and logistics providers—to work in harmony. Companies need to have visibility of what is happening across the value chain, be able to collaborate, exchange data, and orchestrate supply chain processes with partner ecosystems seamlessly in near real-time. However, achieving seamless collaboration and real-time data exchange across the value chain remains a significant challenge. According to recent studies, only 21% of organizations have complete supply chain visibility, and many acknowledge their network collaboration as a work in progress1.
A key roadblock to building connected supply chains is partner readiness. External partners vary greatly in their technological and process maturity. Some are adaptable and ready to collaborate, while others may be unwilling or unable to do so. Second, even if partners are willing, they may lack the resources or desire to invest heavily in meeting collaboration standards. And finally, there is the element of trust and concerns about sharing data and processes.
Even if an organization is able to meet its partners where they are, data and systemic issues stand in the way. An IDC survey reveals a surprising reliance on legacy tools like phone calls, emails, and spreadsheets, which introduce latency and lag. The first challenge is ensuring the right tools for collaboration are in place. Another issue is the inconsistency in how companies talk about data. For example, in a company, what is the meaning of “sales”—does it refer to units, dollars, or something else? These differences can lead to confusion and miscommunication. In addition, each function often uses its own data sources, leading to discrepancies. Sales might use one data set for planning, while marketing and supply chains use different ones. There is a need to standardize terminology and data views so all functions within an enterprise operate from the same version of the truth.
The key to effective collaboration is going beyond mere integration to achieve true interoperability. Integration brings in data, but to make sense of it, you need to understand it in your context. For example, as a brand, you may have your own product codes, but your partners might use different codes for the same products when reporting sales. This means you need to harmonize the data to make it meaningful for your systems. Using a platform with defined canonical data models can help achieve this. By ensuring seamless interoperability, you can respond quickly and effectively to changes in your ecosystem, making better use of the data you receive from your partners.
Supply chain responsiveness requires moving inventory quickly from the closest supply source possible to meet the demand. Traditional, linear supply chains with one-on-one partner connections do not allow for this agility as they lack visibility beyond those connections. Many e-retailers struggle to take orders if they don’t have the product in stock, even if another partner does. By viewing the supply chain as a many-to-many network, companies can scout and scan for inventory across all partners, ensuring orders can be fulfilled even when their own stock is low. This connectivity beyond their direct customers and suppliers helps plug demand-supply gaps in near real-time and maximize fulfillment.
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One of our clients, a well-known sports apparel retailer, decided to bypass a leading online marketplace and run their own online store. However, they couldn’t do it alone due to limited inventory. They needed to rely on their retail partners. We helped them create an ecosystem that provided real-time visibility of retail inventory. When a customer visits their online store and a product is out of stock, the system can allocate stock from nearby stores. This way, customers can either buy online or pick up in-store, often leading to additional purchases. This collaborative approach allowed them to grow significantly without the added costs of new warehouses, leveraging the value of their retail network.
Using platforms like TradeEdge can make it easy to connect and onboard multiple retailers and distributors all at once. Once partners are on the platform, data sharing becomes almost instantaneous, allowing for quicker value realization. This setup offers near real-time demand sensing, improving forecasting accuracy by up to 20% and reducing stockouts. Additionally, tools and applications on the platform can help digitize operations, especially in emerging markets where partners may still rely on manual processes.
A clear understanding of demand, sales rates, and inventory levels across the network enables more accurate suggested ordering and auto-replenishment. This network visibility is a key step toward building an autonomous supply chain.
Disclaimer Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the respective institutions or funding agencies
