Borders are complex, not least in a geo-political sense; they have a huge number of processes that take place around them. Here in the UK, there are at least 25 different government departments and agencies that have jurisdiction over some part of the border. This could include more obvious processes such as collecting customs duty, issuing visas or stopping drugs entering the country. Other jurisdictions include the not so obvious processes of checking for invasive species of insects in imported timber, monitoring the quality of olive oil imports or setting regulations around the transport of lithium-ion batteries. Whatever the remit, it generally involves highly interdependent and often varying relationships between a wide array of entities. A perfect scenario for graphs.
Capgemini’s UK Graph Guild is an initiative dedicated to helping clients understand how graph technologies can be used to solve real world problems. While more information on the guild can be found in Introducing Capgemini’s UK Graph Guild, this blog follows on from Graphs or network analysis for public sector government departments by focusing specifically on use-cases for graph technologies at the border and their benefits. So, let’s jump straight in:
Implementing the huge number of processes at the border is an equally large number of people. Human capital management is an approach to HR that perceives employees as assets whose future value can be enhanced through investment. Graphs can be used to untangle the network of skills, competencies, training, roles and projects that make up an organisation’s human capital landscape. This can empower agencies to understand where skills are grouped, predict what skills will be needed in the future as projects and roles change, highlight whether those skills should be acquired through training or recruitment and create personalised career paths for employees. This would provide governments with the insights needed to effectively invest in border workforces for the future.
360-Degree ‘Customer’ View
Every journey across a border will involve interactions with multiple government agencies. Even if the interactions don’t require the same information from a passenger or trader, no-one agency will have a view of the entire journey. This lack of a holistic view of the ‘customer’ creates inefficiencies and inconsistencies for both government and the passenger or trader. A graph database can be placed over the top of siloed legacy systems, allowing disparate datasets to be integrated. This has the benefit of providing governments with a more complete view of entities using their services, enabling them to save time and provide a more coordinated and accurate service. Furthermore, the ‘customers’ benefit by only having to provide information once, and in-turn receiving services that better suit their needs.
Disruptions at the border are inevitable. What sets a good border apart from the rest is its ability to mitigate as many disruptions as possible and efficiently resolve any that do occur. Both of these can be aided by the use of graph algorithms to analyse the global structure of physical transport networks at and around the border. Centrality measures can be used to identify critical points and bottlenecks while pathfinding algorithms can highlight alternative routes and rank them by cost to both government and industry. Furthermore, because of the interconnectedness of graphs, the impact of the diverted traffic on the surrounding areas can be understood to ensure new disruptions aren’t created in the process.
Given the complexity of the border, even small changes in the ecosystem can have far-reaching effects. This is most obvious in the introduction of new policies. Being able to model how a policy will influence the physical transactions at the border will allow government to create more innovative and effective policies while minimising the risk of adverse consequences. Such a capability would leverage knowledge graphs, which codify information making it possible to use the relationships to derive new knowledge.
Supply Chain Diversity
Just like a business, most countries have suppliers, other countries from which they import commodities they require. Quite often, some of these commodities are critical ones, food or medicines for example. Items that are needed no-matter what. Again, like a business, ensuring the supply chain of these commodities is vitally important. As supply chains are inherently graphs, using graph technologies to analyse them will allow governments to improve their resilience and robustness. This will safeguard against single points of failure in critical supply chains and optimize a government’s ability to respond to global crises.
Identity & Access Management
As the world continues to digitise, being able to provide the correct levels of access to the depth and breadth of data required is increasing difficult. This complexity is no longer suited to traditional rule based IAM methods. Graph-based techniques not only simplify the process but enable it to be more fine-grained and personalised. This solution is not only applicable to databases and systems but could also be scaled to a national level simplifying and streamlining the process of entering and exiting a country. Moreover, the additional context provided by graph can make passport, visa and citizenship processes more efficient as well as increasing assurance that the physical entity matches the presented identity.
This should not be considered an exhaustive list of uses for graphs at the border. This blog hasn’t even touched on the more traditional border security use-cases of public health & biosecurity, misdeclared & fraudulent goods, the illegal movement of people, and dangerous people & goods. Nor has it touched upon graph-based search and recommendations to help citizens, companies and government employees navigate the wealth of information and data at the border. Overall its clear to say that there are many interesting and un-tapped avenues for using graphs at the border for the benefit of both government and citizens, and it will be interesting to watch the innovation that occurs over the next decade.
If you would like to know more about Capgemini’s UK Graph Guild, or if you want to know how we can help you apply graphs to your data, please email me at firstname.lastname@example.org.
Jake is a senior data scientist in the Insights & Data practice, with over 5 years’ experience building analytical and machine learning solutions for the public sector. He is always on the look-out for what will become the future of analytics.