UK Police Face Common Data Challenges

The best kind of policing adopts a local focus, but that doesn’t mean there aren’t lessons to be learned from law enforcement officers internationally. Despite their different crime makeup, the United Kingdom has recently been experiencing similar successes and challenges in implementing data analytics compared to U.S. forces. A recent report from the U.K.’s Royal United Services Institute took a deep dive into big data practices across the British Isles, noting some familiar frustrations as well as recommendations for improvement that police in the U.S. and elsewhere would certainly find helpful.

Crime in the U.K. vs U.S.

The U.S. and U.K. are clearly very different countries, but share several broad characteristics, even in their crime trends. In both nations, crime rates have fallen since the mid-1990’s, particularly violent crime rates. The cause behind this trend in both countries is still a matter of debate. But America and the United Kingdom have each faced new challenges in the modern era of crime. Changing economics and social structures have served to upend the status quo, and any way the data is sliced can produce an array of seemingly contrasting findings.

The U.K. shares many traits in common with the U.S. in how its police forces collect and use that data, too. The RUSI report found that just as in the U.S., law enforcement agencies in the U.K. collect a huge amount of data every day, but have few strategies to put it to effective use. One of the most significant barriers to better data utilization in the U.K., according to RUSI, is the various tools and systems in place to gather and interpret it.

“This paper finds that the fragmentation of databases and software applications is a significant impediment to the efficiency of police forces, as police data is managed across multiple separate systems that are not mutually compatible,” the report stated in its executive summary. “Moreover, in the majority of cases, the analysis of digital data is almost entirely manual, despite software being available to automate much of this process.”

Some of this inefficiency is due to the nature of policing in the U.K. and much of the European continent. Although it recently voted to leave the European Union, the U.K.’s geographical location and status as an international hub still requires it to place almost equal emphasis on local and international crime data analysis. This has contributed to the proliferation of disparate crime databases used by U.K. police, and a lack of uniformity in data protocols. The RUSI study quoted a London police commissioner to explain the practical effects of the scenario: “If an officer is dealing with a crime from start to finish in terms of arrest and putting a file together, they will input the names of both the suspect and the victim 10 or 12 times.”

Low rates of analytics adoption

The report also found a pattern of inadequate and disjointed efforts to invest time and funding in better technology, particularly predictive analytics.

“Despite their proven effectiveness, few U.K. police forces have adopted crime prediction tools as part of their digital strategies,” the report found. “A great deal of officer time is still taken up with traditional beat policing, despite the fact that hotspot policing has been repeatedly shown to be significantly more effective at predicting where crime will happen, thereby allowing limited resources to be deployed to where they are most needed.”

This is another area where U.S. and U.K. police forces unfortunately share quite a bit of commonality. RUSI researchers found that while police in the U.K. did use crime-mapping techniques, they were predominantly retrospective and manually produced. But for nearly similar costs, the report found, police departments could employ predictive analytics tools that help provide proactive solutions to crime trends.

To that end, RUSI researchers noted that various predictive tools in use in various U.S. cities could find a home in the U.K. as well. These include tactics such as:

  • Predictive hotspot mapping: Implemented in jurisdictions throughout California since 2004, leading to marked reductions in local crime rates by helping police focus foot patrol efforts.
  • Predictive risk assessment of individuals: Used in various U.S. cities to develop lists of potential future violent offenders based on previous records and other factors.
  • Open-source analytics: Utilizing data sets outside of police systems that can be integrated into existing models, generating more comprehensive results.

Fighting crime with data

As well as recommending the adoption of several of these specific analytics approaches, the RUSI report made several broad suggestions for combating a lack of data efficiency within U.K. police forces. Primarily, the report urged law enforcement agencies to work more collaboratively, instead of the increasingly isolated approach that had been adopted throughout the country recently. Some of this problem is due to embedded, localized structures of government that would be hard to remove. But RUSI also noted deficits in the culture of officers in the UK, who generally were not trusting of new and unfamiliar ways of doing things. They recommended more high-quality training on predictive data tools to increase buy-in among leaders and improve attitudes in all team members.

Building a new model for policing is not something that can be successfully accomplished overnight, whether it’s in the U.K., U.S. or anywhere else. Visallo is working with law enforcement agencies to take small but meaningful steps toward more effective use of data in everyday work, with the ultimate goal of making communities safer for everyone.