Transforming siloed data into actionable intelligence at U.K. borders

Building on one of the case studies discussed by Leidos during their breakout session at this week's Building the Smarter State conference, Ben Lewis, Senior Solution Architect at Leidos U.K looks at efforts to ensure secure and efficient data sharing in the government's border control efforts. 


While the departments that manage the U.K. Border already collect reams of data on trade and passenger transactions, the U.K.'s planned £705 million revamp of its border control systems will generate even more structured and unstructured data for the government to process.

Leveraging this data and intelligence is critical to improving the U.K. border as it can reduce security risks, enable better supply chains and trade and improve the passenger experience. Gone will be the days of ‘random’ border checks. Instead, interventions will be intelligence driven.

As intelligent systems are put in place to leverage value from data, a unified strategy across dependent users, groups and departments is necessary to derive precise and valuable insights. In addition, data standards, increased data handling capabilities and streamlined systems will play an important role in delivering actionable intelligence.  

With a proven track record of building applications and collaborating with agencies across the globe on complex challenges, Leidos stands ready to support the U.K. government in its border control efforts and to ensure data sharing is secure and efficient.

A sophisticated and community-minded approach to data

In government, making decisions typically requires dealing with complex systems, with data from overlapping services that fall under the jurisdiction of many different groups. The U.K. Home Office Biometrics Programme, where Leidos is the prime systems integrator, is an example of bringing together different systems, used by law enforcement, immigration and asylum departments.

Without such an approach, data sharing with other departments or governmental bodies that need the same information is often problematic.  Data input, output and information flows need to be understood and where appropriate changed. Systems need to be designed with the end result in mind. To enable data-driven decision making, it’s helpful to think of the data journey as a kind of production line, going from data to the actionable intelligence required to impact the desired outcome.

Joining systems together for more effective services and reduced total costs, however, is only feasible when common data standards are adopted. If there are inconsistencies between systems, the whole production line is thrown into disarray and you can’t get valuable insight.

When it comes to data management, whether it’s related to identity management, digital citizen journeys or regulatory enforcement, its important to follow the 'write once, reuse many times' rule.  When you create a new element, structure it once and do it well, so that it doesn’t have to be recreated by other departments. Otherwise, if code is replicated across governmental departments, you have to compare, export or manipulate data, which introduces the risk of errors, development challenges and interoperability problems.

Best practices include building data libraries, establishing single-source information ownership, and designing systems in a way that can be customised to fit the needs of departments.

Getting more precise insight with a unified view

Data is only one piece of the puzzle. As day-to-day business systems increase in capability, data sourcing and management becomes more complex and wide ranging. Systems must offer an unambiguous unified view, so that connections can be made and real-time and historical data can be consumed.

A case study in the importance of a unified view is our collaboration with i-Tech 7, an offshore oil and gas infrastructure maintenance company. Since 2017, Leidos has been working with i-Tech 7 to maximise the value of its fleet of remote-operated and autonomous inspection vehicles. By using machine vision to analyse the standardised data collected from multiple sources, and by automatically comparing current data against normalised historical data, we helped automate up to 75% of the company's pipeline survey and inspection process. This intelligent assistance helped control engineers do proactive maintenance, which is far more cost efficient than reactive events.

Similar gains may also be achieved in border control by bringing together data into a unified view. Integrating data sources provides enormous opportunity for the U.K. border transformation. To do this, Government must embrace a shared data-to-actionable intelligence vision. This will enable targeted and informed decision making on how, where and when to target resources to drive the benefits of a modern border.

Learn more about this topic in this piece by Leidos looking at the opportunities for the UK to create a world leading border system or visit Leidos U.K.

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