Let’s Restart Our Broken Global Supply Chains with Graph Technology


With global business having been shut down due the pandemic and lockdown, normal sources of supply have been disrupted, and sourcing has become unreliable. Many firms are struggling to meet baseline demand due to insufficient supply and others are trying to streamline to meet unprecedented spikes in demand for certain products. Transparency and agility in our supply chains have never been more complex or more vital. We need new ways to analyse and manage highly complicated inter-dependencies in order to ensure resilience and continuity of supply chains.

Manufacturers and shippers of goods have always needed a highly scalable way to manage the vast volumes of serial numbers, supplier and facility details, certifications, documents and complex regulatory requirements. However, as The Big Reset begins, organisations must also adapt to unprecedented amounts of change that look to be a new normal. In parallel, businesses will need to assure consumers that they can continue to deliver products that meet standards and maintain full compliance with international regulations as well as sustainability, social responsibility, and quality targets.

As supply chain technology experts Transparency-One’s CTO Frédéric Daniel has noted, “The more complicated a supply chain is — the more components, suppliers, and facilities involved — the more vulnerable it is, regardless or vertical or sector. Supply chains that have multiple tiers, are heavily globalised, and/or involve several components or stages of transformation are inherently more complicated and at greater risk of being impacted by a pandemic or other crises.”

Supply chains are complex networks of interdependent processes and components that must work in concert to meet demand. As businesses are forced to make real-time adjustments, they may source components from suppliers who are difficult to vet or take risks that could put their entire operation in jeopardy. For example in closely-regulated industries such as pharmaceuticals, suppliers must be able to identify where any individual medicine item is, at any given time. In the event of a safety issue, it is imperative that items or batches can be quickly removed from the market to minimise the risk to consumers and intelligently targeted to minimise the cost of redress or widespread product recall.

The technical challenge of meeting these targets can be onerous. That being said, Daniel continues, “a supply chain’s vulnerability largely depends on how prepared the business is to deal with a crisis. Businesses who have visibility into their supply chains and know who is involved, where they are located, how their products are potentially impacted, and what alternate sources are available to them are much better equipped. Those who lack this knowledge are more vulnerable because they do not have the information needed to make informed decisions”.

To have the flexibility to deal with a crisis requires having visibility into complicated relationships with thousands of product lines containing even more subcomponents, produced across multiple sites which are then sold into hundreds of markets and millions of consumers. This is not well represented in tables in rows: keeping track of all these items, let alone analysing them, exceeds the scope of the old standard ways businesses have organised supply chain data, specifically using relational database systems (think Oracle or Microsoft SQL Server). Consider the numbers of unique serial codes that alone can run into billions; CIOs need not only a highly scalable way to manage the vast volumes of serial numbers but more importantly the ability to quickly analyse all relationships between them – and everything else in their supply chain.

Graph technology is used to manage and analyse complex networks like supply chains, because of its ability to record data interdependencies at scale and use relationships to find patterns. Graphs offer a tremendous advantage over traditional relational databases, maintaining high performance even with vast volumes of data. Instead of using relational tables, graph databases are purpose-built to analyse interconnections in data, and are closely aligned with the way humans think about information. Graph algorithms use relationships to understand the structure of data and uncover meaningful shapes that can be used to infer behaviour. Graphs are practically impossible at analysing the relationships between a large number of data points.

Such a relationship-centric approach enables the manufacturer to better manage, read and visualise their data, giving them a truly trackable and in-depth picture of all products, suppliers and facilities and the relationships between them. Using a graph database, manufacturers can typically demonstrate 100 times faster query response speeds than that enabled by relational databases. Graph analytics can answer questions that are intractable without the use of relationship-based algorithms. That sort of response time and insight is critical during this crisis and will continue to be relevant as organisations work to mitigate the supply chain risk that has been exposed. Supply chains need to build resilience to comply with the latest global regulations on traceability and to manage time-critical product recall, as well as to manage the surges and drops in demand that the pandemic has heralded. Graph database and analytics technology is a great enabler and an effective solution for organisations that need to work with complex supply chains and provide the level of highly granular governance and sourcing capability our global economy demands.