Exploiting the Data Goldmine – How analytics can make the difference for Law Enforcement
The current economic climate means that times remain tough for law enforcement agencies. Not only are they forced to cope with ever-shrinking budgets and thinly-stretched resources as manpower levels are reduced, they are also under growing pressure to deliver more with less. In looking to meet these challenges, the variety of data agencies need to hold, from crime records to number plate recognition information to suspicious activity reports, could be their biggest asset.
If properly exploited, this data could provide invaluable insight for agencies in their battle to fight crime while driving efficiencies.
Unfortunately at the moment, agencies are not exploiting the full value of the data they have. The issue is that most law enforcement systems today still work in isolated silos. Data is often held across a vast array of standalone systems. Agencies are therefore often not able to access this data easily, or more importantly, use it effectively.
Changing to big data analytics
The good news is that most agencies understand this needs to change. They realise they must find a way of using the big data they hold to streamline their own operations internally and get a holistic view of criminal activity. A data platform that enables information to be viewed and analysed holistically, whether physically located in an HR system, crime or number plate recognition system, has to be the foundation. Once this is in place, then Big Data Analytics can be applied to start to extract insight and provide value.
Of course, advanced analytical techniques have been used in finance and retail environments for years to achieve efficiencies and increase profit margins. The same techniques can and should be applied to law enforcement to achieve similar results. For example, agencies could be analysing all available data to understand crime patterns and keep officers focused on the top crime prevention priorities, understand where duplication is occurring and target resources most efficiently.
Equally, rather than having to hold daily briefings, agencies could use big data analytics to push briefing information in real-time to officers on the beat depending on their physical location – so they are only receiving information that is actually relevant to them.
However, traditional analytical techniques are often not sufficient in the new online world. Gone are the days when most data was held in nicely structured formats, within relational databases. Today, a lot of it is unstructured text in the form of word documents, transcripts, witness statements or internet chatter. This kind of data is potentially really valuable to law enforcement agencies. Unfortunately, in the past, they’ve had to invest vast amounts of time and resource in manually going through this data to make sense of its content and extract the useful nuggets of information from it.
Today, this is rapidly changing thanks to the latest developments in text analytics. Sophisticated linguistic rules and statistical methods can evaluate text just like a human mind – minus the inconsistency and ambiguity. The latest text analytics technology automatically extracts keywords and topics, categorises content, manages semantic terms, unearths sentiment and puts everything in context.
By applying text analytics, agencies can begin to extract intelligence from unstructured data and turn it into a more structured format which can then be analysed together with their structured data. This is really ‘changing the game’ for agencies as it means they can now exploit all of their data, not just the structured content.
Finding the Answer with Big Data Analytics
From the perspective of the agencies themselves, however, the real ‘value add’ of Big Data Analytics is that they don’t need to know what they are looking for before they start. They don’t need to have to wade through the haystack looking for the needle. With the latest advanced analytics technology, officers don’t have to rely on asking specific questions or running specific queries.
Instead, the analytical techniques will model the data and push information of interest back to the officer or analyst, drawing their attention to relevant content, effectively pushing the needle from the haystack. This can then be processed through standard analysis and investigation processes to determine if it is viable intelligence, effectively converting Big Data into actionable intelligence.
To do this, agencies must start deploying the right technologies to extract as much value as they can from that data. Without the right tools, pinpointing relevant data in Big Data that might potentially be of use would be resource intensive and unaffordable. With the right solutions, agencies can sift out irrelevant information and highlight areas of interest, whether that be to achieve efficiencies or drive preventative policing strategies.
Director, Public Security, SAS