A data-sharing approach for greater supply chain visibility (2023)

Amid the lingering effects of the COVID-19 pandemic, rising inflation, the war in Ukraine, geopolitical tensions in East Asia, and more frequent extreme weather events, manufacturing supply chains continue to struggle in bringing goods when and where they are needed. These disruptions have affected all aspects of end-to-end supply chains, producing demand shifts, supply and manufacturing capacity reductions, and coordination failures. Prior to 2020, most supply chain designs lacked the resilience needed to cope with these disruptions, and, in response, companies have tried to diversify their sourcing and increase inventories and manufacturing capacity, all of which have led to increased cost.

Now more than ever, companies need a new paradigm for cost-competitive resilience if they are to redesign supply chains while maintaining their competitive advantages. Firms are increasingly turning toward better contingency planning, improving organizational readiness and worker flexibility, automation, and building more collaborative relationships with suppliers to improve supply chain resilience. Other strategies include moving from vertically specialized to vertically integrated firm structures and trading lean supply chain designs for more decentralized network designs. By redesigning products and supply chains for greater agility, firms are creating greater opportunities for postponement and a reduced need for highly accurate demand forecasts.

In support of these strategies toward cost-competitive resilience, a potent first step is to improve end-to-end supply chain visibility, which provides companies with real-time data and a holistic understanding of their partners across the end-to-end supply chain, starting upstream at the procurement of materials or semifinished goods and ending downstream when products reach the end customer. By knowing the real-time location, production rates, and delivery schedules (among other variables) of raw materials, components, and final products across the global supply chain—whether in manufacturing plants, port terminals, warehouses, or in transit—it becomes easier and quicker to identify disruptions, mitigate their impact, and improve productivity. Improving resiliency requires the public and private sectors to establish visibility across the logistics ecosystem. To this end, the U.S. government should use its convening power and—in partnership with supply chain stakeholders—promote the development of freight data exchanges that enable interoperability, while fostering a competitive market for innovative software solutions.

U.S. supply chains are a collection of decentralized systems, each with its own objectives, decision rules, and levels of visibility. Challenges regarding data quality, availability, interoperability, and immediacy increase when attempting to coordinate and manage multiple supply chains and their multi-modal logistics infrastructure. Data are rarely shared across supply chains and only occasionally shared across firms in the supply chain and logistics industry. Furthermore, interoperability is a major hurdle as shippers, carriers, and end customers employ different technologies and tools for collecting data—the ports of Los Angeles and Long Beach use different software platforms, for example. Before the pandemic there was little effort or need to build resilience and agility into primarily lean supply chains or into the supply chain infrastructure. Today, the lines of authority and responsibility for the national supply chain are neither clear nor well understood.

Prior to 2020, U.S. businesses embraced the mantra of lean supply chains, leaving supply chains vulnerable to large-scale disruption. Assuming stable geopolitics, predictable and smooth demand of raw materials, work-in-progress, and finished products, lean supply chains allowed manufacturing capacity and inventories to be minimized, saving business huge sums in the process. But lean supply chains also left U.S. businesses exposed to disruption risk when the COVID-19 pandemic struck and disrupted virtually all supply chains. These disruptions created supply reductions and considerable demand volatility. During the initial phases of the pandemic, supply chains failed to deliver necessary personal protective equipment, ventilators, oxygen concentrators, and other critical gear to healthcare workers battling on the frontlines. As consumer behaviors shifted in response to global lockdowns, demand dropped dramatically for some products, but in some cases (often boosted by governmental stimulus funds) quickly surged back to near pre-pandemic levels. This whipsawing of consumer demand resulted in automotive companies, for example, cancelling orders for semiconductors when demand initially dropped dramatically, leaving them unable to secure orders when demand returned and producers were busy responding to an increase in orders for consumer electronics for workers stuck at home.

As the pandemic dragged on, key components of the supply chain faced unprecedented challenges. With commercial airline traffic at a fraction of its pre-pandemic level, air freight capacity dropped dramatically, as almost half of all air freight is transported by passenger airlines in the form of “belly freight.” Drivers, factory workers, longshoremen, and other workers up and down the supply chain were falling sick or affected by lockdowns, reducing manufacturing and logistics capacity globally. The closure of Chinese ports—part of the country’s “zero-COVID” policy—resulted in ripple effects across the global freight network, including major congestion at U.S. ports like Los Angeles and Long Beach. While U.S. supply chains responded well to this long list of disruptions, delivering more goods than ever before, that response could have been significantly improved and accelerated with greater system visibility and clearer lines of authority.

Today, the war in Ukraine, its knock-on effects of lower output from Europe’s factories, and the possibility of further geopolitical instability are causing supply chain managers and policymakers alike to rethink the risk of sourcing country-by-country, as country-level supply chain risk in times of conflict can change faster than supply chain networks can be redesigned and reconfigured. These disruptions and shortages are only reinforcing fears that supply chain volatility and uncertainty are unlikely to diminish soon, causing supply chain managers to continue to shift from lean to agile and often decentralized supply chain designs. The effects of this shift have had a material effect on inflation, with some researchers arguing that pandemic-related disruptions raised the inflation rate in 2020 by as much as 2.8%. Some economic commentators see pandemic-related disruptions as largely responsible for continuing record inflation today.

To better understand how visibility can improve the supply chain ecosystem, consider a single private sector supply chain. At each time that a decision is made, a supply chain manager bases her decisions on available data to achieve business and supply chain objectives like profitability, sustainability, resilience, or agility, while optimizing among them. Good decision-making needs well-defined supply chain objectives and decision rules that convert available data into decisions. We can think of a decision rule as an IF-THEN statement of the form: IF (data), THEN (decision). For example, IF the current inventory level is less than some predetermined level Y, THEN add enough items of inventory to bring the inventory level up to Y; IF the current inventory level is greater than or equal to Y, THEN do not replenish. As optimization models of supply chains tend to be large and complex, special analytic techniques or modeling are required to obtain close to optimal outcomes, but this simple example illustrates the basic dynamics of supply chains.

During supply chain disruptions, visibility is essential to provide the necessary data that supply chain managers need to make good decisions. Visibility into the supply chain can help quickly identify dynamically changing bottlenecks from origin to destination by tracking changing freight flows from one port to another and providing accurate estimates of carrier timing and actual cargo volumes carried, allowing inventories and manufacturing capacity to be repositioned. A supply chain invariably involves freight transfer at ports and terminals, and these transfer points are often the bottlenecks in the flow of freight. These freight transfer points are almost entirely privately operated and span all supply chain stakeholders (e.g., shipping lines, terminal operators, truckers, railroads, logistics firms, freight forwarders, warehouses, and cargo owners). National, state, and local authorities have an important role in regulating and overseeing these key nodes of the freight logistics network, but the lack of collaboration and data-sharing platforms between these private and public entities has severely hindered end-to-end visibility of the supply chain. As pandemic-era supply chain disruptions have clearly demonstrated, there is an urgent need for a well-designed data-sharing platform to create greater supply-chain visibility.

Although the various segments of the supply chain and logistics industry have made great strides in digitizing their internal operations, many still operate as legacy businesses, employing manual processes such as faxes, PDFs, emails, and phone calls (all of which may inject data transmission errors and delays) and are unlikely to exchange information with each other. Moreover, independent firms that are part of the same supply chain may not want to share data or their suppliers with each other to protect confidentiality, current or future competitive advantage, and/or legal compliance. Additionally, independent firms are often suspicious and even fearful of governmental agencies that request supply chain data. Hence, data may be corrupted by noise, delayed, and/or entirely unavailable. All these factors reduce the value of data and supply chain performance to inform real-time decision making—illustrating the need for better information sharing mechanisms.

From the public sector perspective, improving supply chain visibility is especially challenging, as it requires the involvement of a wide range of private and public supply chain stakeholders. To this end, the White House announced in March its Freight Logistics Optimization Works (FLOW) initiative, a pilot program for a voluntary and secure national exchange for key intermodal freight data available to all participants who share data.

The FLOW initiative aims to be sustained by a virtuous cycle: As communication improves across supply chains and an increasing number supply chain stakeholders participate, that will lead to more and better data becoming available, which, in turn, will speed up delivery times and reduce consumer costs. Data collected will then support collaborative industry decisionmaking to manage cargo flows, speed up movement, and reduce costs. Eighteen initial participants included shippers (Target, Land O’ Lakes, Albertsons, and others), port authorities (the ports of Long Beach and Los Angeles, among others), carriers (CMA CGM, MSC, UPS, and FedEx), terminal operators and port services (Fenix Marine Services, Global Container Terminals, and others), and brokerage and warehousing (C.H. Robinson and Prologis). As of August 2022, the number of participants had reportedly increased to 36, including several additional shippers (e.g., Procter & Gamble, Samsung), carriers (Maersk, DHL, Hapag-Lloyd, and others), container terminal and port services (e.g., APL Terminals, Consolidated Chassis Management, etc.) and the Flexport freight forwarder.

While the FLOW initiative is a positive step forward for providing needed supply chain visibility, and is making good progress, it needs broader representation from: (i) additional critical supply chain stakeholders; and (ii) private sector support from logistics software providers.

First, FLOW should expand by including participants from under-represented U.S. supply chain stakeholders, including domestic freight transportation carriers, rail, pipeline firms, cargo airlines, and passenger airlines that carry cargo. More than 80% of annual U.S. freight transportation spending goes toward trucking, but even with the addition of new participantstrucking firms are relatively under-represented in FLOW. The same can be said for railroad carriers.

Secondly, FLOW should reach out to supply chain software leaders. Logistics software providers along with leading multinational corporations have been developing tools for supply-chain visibility, and the FLOW initiative would be strengthened by their inclusion. Examples include the blockchain-based TradeLens developed by Maersk and IBM; Project44; and the Netherlands-based Digital Container Shipping Association (DCSA), which is developing digital supply chain standards.

Digital standards are necessary to achieve visibility, and they need to scale across all modes of transportation to simplify handoffs. Today, each step of an intermodal transaction has its own standards, if any at all. Air freight has long used well-defined standards developed by the International Air Transport Association (IATA), employing API (application programming interface) documentation as opposed to the rather anachronistic electronic data interchange (EDI) to attain real-time visibility. It was only in 2020 that ocean freight began developing such standards with the DCSA, which has as its members leading carriers and shippers, but adoption still lags. Land freight, which includes terminal operations, drayage companies, third party logistics companies (3PLs), freight forwarders, and rail processes, is where visibility is even more cumbersome and has no clearly defined standards. APIs have the potential to revolutionize the cargo industry by allowing real-time data exchange, unleashing customer-centric innovation and finally bringing the industry up to date.

Finally, developing a collaborative platform such as FLOW, capable of supporting planning before the next crisis and data-driven risk mitigation during a national crisis, requires broader buy-in from industry. To achieve this buy-in, public sector supported foundational research should investigate the merit of sharing data with the other FLOW participants. To this effect, the following questions need to be addressed: What is the value for a firm to participate in FLOW? What are the associated risks? Answers to these questions could guide the public sector in determining what incentives and ecosystem investments should be provided to retain current collaborators, attract new ones, and better align private sector objectives with the nation’s strategic public health, social, defense, and economic priorities.

Eleftherios Iakovou is the Harvey Hubbell Professor of Industrial Distribution at Texas A&M University and the Director of Manufacturing and Logistics Innovation Initiatives at the Texas A&M Engineering Experiment Station.
Chelsea C. White III is the Schneider National Chair in transportation and logistics and is a professor at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

IBM provides financial support to the Brookings Institution, a nonprofit organization devoted to rigorous, independent, in-depth public policy research.