How Granular Data Can Help Businesses See Supply Chain Risk Earlier

What BIS Project Insight reveals about hidden dependencies across firms, ports, products and economies

A global supply chain disruption rarely begins as a headline. It may start with a component supplier slowing production, a vessel waiting longer at a port, or a company becoming increasingly dependent on a narrow group of counterparties. Individually, these shifts can look manageable. Across an interconnected network, however, they can develop into higher costs, delayed delivery and wider financial risk.

The challenge is that these changes may be difficult to see before they surface in trade volumes, prices or financial markets. Traditional statistics explain how much is moving between economies, but they offer less visibility into the firms, ports and relationships behind those flows. For Hong Kong businesses operating across regional and global markets, this raises a practical question: can emerging vulnerabilities be identified from changes in corporate and port relationships before their wider effects become visible?

Against this backdrop, Project Insight: uncovering the complexities of global value chains, published in July 2026 and led by the Bank for International Settlements (BIS), offers a useful framework for examining what aggregate trade statistics may not reveal. Developed by the BIS Innovation Hub Hong Kong Centre in collaboration with the Hong Kong Monetary Authority, the Organisation for Economic Co-operation and Development and DIW Berlin, the project explores how granular and macroeconomic data, advanced analytics and visualisation tools can strengthen the monitoring of global value chains. It does not seek to predict the next crisis or rank the world’s most vulnerable supply chains. Instead, it examines whether shifts in firm-to-firm and port-to-port relationships can provide earlier visibility into emerging bottlenecks, concentration and transmission risks. This article takes a closer look at the report's analytical approach and what it may mean for businesses managing complex cross-border dependencies.

Why Traditional Trade Statistics Can Miss Hidden Dependencies

Global value chains are not simply a sequence of imports and exports. The BIS report describes them as a complex web of firms, balance sheets and production stages spread across economies and industries. Risk therefore depends not only on trade volume, but also on the structure of the network behind it.

An economy may appear to source a product from several markets while the underlying activity remains concentrated among a small number of companies or a common corporate group. Similarly, a company may maintain a long supplier list while most of its purchasing remains dependent on one counterparty or one critical product source.

The same principle applies to logistics. A backup port or route may appear to provide resilience, but it offers limited protection if it is exposed to the same congestion pattern or infrastructure constraint. To assess resilience more effectively, businesses need to look beyond the number of alternatives and examine whether those alternatives are genuinely independent.

How Project Insight Connects Firms, Shipments, Ports and Ownership

Project Insight combines a historical snapshot of granular commercial data from 2018 to 2024 with publicly available macroeconomic information. Together, the selected sources comprise more than 15 billion observations.

• More than 300 million seaborne containerised packages and shipments between over one million entities.

• Around 50% of global containerised maritime trade by container volume.

• Additional data covering supply chain relationships, entity attributes, ownership linkages, vessel tracking, product-level trade, macroeconomic indicators and cross-economy input-output tables.

To make these sources comparable, the project team standardised identifiers and classifications, aligned units and time periods, addressed missing or implausible values and resolved entities across datasets. The cleaned information was then organised into four analytical layers: entity to entity, port to port, industry-economy to industry-economy and economy to economy.

The resulting interactive dashboard allows users to move from broad trade patterns to specific products, economies, counterparties and relationships. Rather than presenting one definitive map of supply chains, the project demonstrates a reusable data architecture and analytical foundation that institutions can adapt to their own data and priorities.

Four Ways Granular Data Can Strengthen Supply Chain Risk Monitoring

Detect changes before they are fully reflected in headline indicators

The dashboard tracks monthly movements in the number, value and weight of maritime shipments, together with product price measures derived from shipment value and weight. These indicators can help users spot deviations from established patterns and determine where further investigation may be needed. A sustained decline in shipment frequency, for example, may carry a different implication from a brief fluctuation.

For businesses, these data are most useful as early-warning signals rather than automatic predictions. Combined with commercial context, they can support earlier review of sourcing plans, inventory assumptions and financial exposure.

Identify where delays are occurring across the shipment lifecycle

Project Insight separates maritime shipments into detailed stages using timestamps for container gate-in and gate-out, vessel loading and unloading, and vessel departure and arrival. It then develops measures including total processing time, container clearing time, vessel clearing time and vessel congestion rate.

This provides a more actionable view than a general statement that a port is congested. Businesses can examine whether delays are concentrated before loading, between loading and departure, between arrival and unloading, or before the container leaves the destination port.

The dashboard also compares congestion correlations between ports. If two ports regularly experience congestion at the same time, one may not provide effective redundancy for the other during a disruption.

Measure whether supplier and product diversification is genuine

The project analyses trade exposure through the number of unique counterparties, bilateral counterparty and product shares, the Herfindahl-Hirschman Index and the four-firm concentration ratio. These measures distinguish between having multiple relationships and distributing business meaningfully across them.

For management teams, the practical questions are not only how many suppliers are available, but how much activity depends on each supplier and whether the alternatives are commercially viable and genuinely independent.

The analysis should also consider whether apparently separate counterparties share ownership, geography or logistics infrastructure. These connections can leave a business exposed to the same underlying disruption despite having multiple direct relationships.

Trace how disruption may spread through connected networks

Project Insight applies network metrics across entities, ports, industries and economies. Degree centrality considers the number of connections; eigenvector centrality considers connections to other important nodes; betweenness centrality measures how often a node sits on shortest paths between others; and closeness centrality considers how easily a node can be reached across the network.

These measures can reveal intermediary firms or ports that may not be the largest by shipment value but still occupy positions through which disruption could spread quickly. The BIS report also notes that shocks affecting central firms can spill over into credit markets, equity valuations and bank balance sheets, linking supply chain visibility with wider financial stability.

What the Findings Mean for Hong Kong Businesses

For Hong Kong companies managing cross-border sourcing, trade finance, credit exposure or third-party risk, the report points to a broader shift in how resilience should be assessed. The focus is moving from isolated transactions and aggregate volumes towards the relationships that connect companies, products, ports and markets.

• Look beyond direct suppliers to identify shared upstream dependencies and indirect exposure.

• Measure concentration by value and business criticality, rather than relying on supplier count alone.

• Test whether alternative ports, routes and counterparties are exposed to the same underlying constraint.

• Connect operational monitoring with entity identity, ownership and financial information to build a fuller view of risk.

• Use granular indicators to trigger investigation and scenario planning, while retaining human judgment and business context.

This approach can help procurement, finance, treasury, logistics and risk teams work from a more consistent view of exposure. It also supports more focused stress testing by showing which relationships may be difficult to replace and which network positions could amplify a local disruption.

Using Project Insight as an Analytical Framework, Not a Complete Risk Map

Project Insight is explicitly a proof of concept and should be interpreted within the scope described in the BIS report. It does not provide comprehensive coverage of global supply chains or identify where risks definitively reside. Its historical datasets are snapshots, while the maritime shipment data cover around half of global containerised trade by container volume.

Air and land transport, services trade and undisclosed relationships are not fully represented. Commercial sources may also be biased towards larger or publicly reporting firms, while classification harmonisation and entity matching across datasets may introduce error.

The dashboard and indicators should therefore be used as a framework for observing structures and changes, not as a stand-alone basis for policy, investment or commercial decisions. Their value lies in making dependencies more visible and providing a foundation that users can extend with internal data, sector knowledge and expert judgment.

From Tracking Trade Flows to Understanding Business Dependencies

Project Insight's central contribution is not a single metric. It is the shift from measuring aggregate trade flows to examining the relationships through which disruption can spread.

A more useful view of supply chain risk asks not only how trade volumes have changed, but also which firms and routes are difficult to substitute, where concentration is increasing and which network paths could turn a local event into wider operational and financial consequences.

Granular data cannot remove uncertainty. It can, however, help businesses identify structural change earlier, investigate emerging signals and plan responses with greater context. For companies operating from Hong Kong into complex regional and global markets, this provides a stronger foundation for more informed resilience planning.

For organisations seeking to translate this analytical perspective into a more practical view of their own supply chains, D&B Shipping Insights can provide company-level visibility into shipping activity, transaction volumes and the roles businesses play across trade relationships. Explore D&B Data Blocks and Shipping Insights to learn how this data can support a more connected understanding of suppliers, customers and trade dependencies.

Source
Bank for International Settlements Innovation Hub, Project Insight: Uncovering the Complexities of Global Value Chains, July 2026.

This article summarises the published report for a Hong Kong business audience. Project Insight is a proof of concept and does not provide a complete picture of global value chains.