Taking the Stress out of Supply Chains with Graph Technology

According to the World Economic Forum (WEF), “Governments, businesses and individual consumers suddenly struggled to procure basic products and materials, and were forced to confront the fragility of the modern supply chain. The urgent need to design smarter, stronger and more diverse supply chains has been one of the main lessons of this crisis.”

The WEF is absolutely correct. As global business shut down due to COVID-19, normal supplies have been disrupted, and sourcing has become more unreliable. These factors make transparency in the supply chain more vital, but also more complex.

Makers, shippers and buyers of goods need scalable ways of managing the vast complexities of serial numbers, supplier and facility details, certifications, documents and detailed questionnaires. However, even more essential at this moment is visibility and adaptability to quickly re-start their operations as the crisis eases and pivot to whatever the ‘new normal’ becomes.

Locating an individual item

Sourcing headaches have prompted brands to urgently review their supply chains, often moving to reduce risk by producing more locally. For example, non-specialist factories may scramble to produce Personal Protective Equipment to help plug gaps in national emergency stockpiles, but the reality is that supply chains today are invariably global and wide-ranging. At least some components will continue to be sourced internationally for just about every product.

Due to the pressure upon disrupted supply chains, businesses are at increased risk of delivering products that fail to comply with local and/or cross-border regulations, or fail to meet consumer demand for sustainability, social responsibility, and quality. A disrupted supply chain means components, if they show up at all, may now be coming from unvetted suppliers. These challenges can put the entire manufacturing operation at risk. For instance, in the closely-regulated pharmaceuticals industry, suppliers must be able to identify – at any given time – where an individual medicine item is. In the event of a safety issue, it is imperative that items can be quickly removed from the market to minimise the risk to consumers and the cost of redress.

As supply chain technology expert Frédéric Daniel, CTO of Transparency-One has noted, “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.”

Graphs offer advantages over traditional relational databases

Many organisations still store supply chain information in data silos, rendering it available in partial views only. Even if the data is stored in a single relational database, a simple, fast navigation through all the data in order to recognise how a production line or particular pallets and their contents are connected, would be next to impossible. The numbers of unique serial codes alone can run into billions, and CIOs need a highly scalable way to manage the vast volumes of data as well as analyse how items are related. With increasing connectivity and a move an Internet of Things, this complexity is unlikely to decrease.

Graph technology is an increasingly popular solution, because of its ability to record and compute over complex data interdependencies. The idea is that when you use graphs to track something, you create a hierarchy and rich context surrounding your data. For example, if you scan the code of a particular pallet, it will automatically recall not only its contents but each distribution centre it passed through, information about manufacturers and even subcomponent detail. Graph databases offer a tremendous advantage over traditional relational databases, maintaining high performance even with vast volumes of interconnected data. Graph analytics answers questions that are intractable without graph algorithms, such as identifying alternative manufacturing sources based on optimal distribution routes plus vendor similarities.

The real benefit for anyone thinking about Supply Chain 2.0 is that such a relationship-centric approach enables the manufacturer to better manage, analyse 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 database software. Adding graph analytics, they can better understand the global structure of their supply chain and make more accurate predictions for optimisations. Fast response times will be critical in order to comply with the latest global regulations on traceability and to manage time-critical product recall, as well as to manage surges and drops in demand. Business leaders need to use the crisis to tear up the rule book and think creatively about making their supply chains much more robust, agile and smart.

The author, Amy Hodler, is Director of Analytics and AI at Neo4j.

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