24th February 2025
Master data management in UK policing
Part two: Effective crime prevention – the view from the front line
By An-Chan Phung, Chief Innovation Officer, Civica
It’s a cold wet day in February and two police officers have just finished responding to a call out. They return to their incident response vehicle. Just before they get in the car the first officer, PC Sharma, identifies a woman across the street that appears dishevelled and has what look like fresh bruises on her face. He is concerned that she recently experienced some violence. She has a young child with her.
They cautiously approach to ask her how she is. The more junior officer, PC Jones, enquires about where the bruises have come from, but she is reluctant to engage. He asks where she is going and if she would like any assistance. She says no. PC Sharma asks her if she feels safe. Although she tries to brush them off again and keep walking, her body language gives a clear indication that she is in a state of distress and that there is probably more to this. They decide that it is necessary to proceed with opening an investigation.
This is a difficult but, unfortunately, not uncommon scenario. But what if this whole situation could have been avoided with a more joined-up approach to data management that unlocks new, preventative strategies?
Improving data maturity in UK police forces
In our recent blog, we looked at the current state of data management in UK police forces, highlighting that there is a lack of data maturity borne out of outdated systems, legacy technology and inefficient processes. The unfortunate conclusion was that these barriers impact police officers’ ability to perform their civic duties.
This time we turn that idea on its head and look instead at the huge potential that connected data offers towards effective crime prevention. In particular, we’ll look at how Master Data Management (MDM) can enhance proactive policing to deliver a much more targeted approach to preventing crime. Evidence will show that the only way forward is to start connecting the dots between the various data sources that are available.
Unlocking the available data
The good news is that this isn’t about creating something completely new. Collecting data is not the challenge for police. In fact, police forces have an abundance of useful data that external partners can supplement and enhance even further. The mismanagement of this data, however, means it is not leveraged to even a fraction of its potential as a strategic asset in crime prevention.
Currently, police data is recorded across multiple disparate systems. This makes it fragmented, disorganised, poor quality, often duplicated and rarely linked up.
From a practical point of view, this hampers the job of frontline police officers such as PC Sharma and PC Jones. Building an accurate picture of a criminal situation or investigation relies on cross-checking data points across a variety of different systems, which are often incomplete, inconsistent or unavailable for reactive situations like the one described above. Cross-referencing is not only time-consuming, but it also creates a frustrating user experience and ultimately reduces the effectiveness of proactive policing.
What happens in a system where we remove the disparate systems and instead work from a consolidated and accurate view of a person, location or object? Or, more in police terms, what happens when we create a golden nominal that joins up all the data sources seamlessly to create a view across POLE?
Proactive policing
Let’s return to our scenario.
The details that might have led to the woman falling victim to violence would likely incorporate a myriad of circumstances. Perhaps her partner is a known offender with a criminal history and has harmed other women in the past, but in a different jurisdiction. Perhaps police have been called to their home address before to follow up on disturbance reports from the neighbours. Maybe there is other information around their use of alcohol or drugs, or connections with known offenders.
This is all information that will sit within police data records but that may not have been connected within the disparate data ecosystem. More connected data, on the other hand, has the potential to help police officers establish details that can aid their investigation.
Let’s bring in another member of the team. Ms Abebe is a specialist data analyst in the force. She has been analysing the correlations between postcodes and registered visits to accident and emergency (A&E) over the last 18 months, mapping the results against households that have children known to social services. She had been building a report around hot spots and trends in domestic violence and was preparing her recommendations to be presented to senior management at a later date.
Under current conditions, it is usually not possible to easily share this vital information to officers like PCs Sharma and Jones on demand. In fact, the clunky data management system means they are probably missing out on far more insights that could be used for effective crime prevention.
As Ms Abebe knows, data collection for crime analysis goes beyond criminal files. She is looking at wider trends and non-obvious relationships, such as the fact that domestic abuse is more likely to occur in the time after a football match. She’ll be exploring evidence of red flag behaviours from perpetrators on social media, such as interactions with hostile groups or posting hateful comments.
These are all types of supplementary information found in crime analytics that become extremely helpful in supporting proactive policing, but only if they can be integrated effectively into intelligence, both strategically and directly to the frontline.
Changing the narrative with better data management
Had all this connected data been available in our example, there would have been greater opportunity for earlier police intervention and the introduction of proactive measures to reduce the risks to vulnerable people like our victim.
For example, would the perpetrator have been under closer scrutiny at their last interaction with the police? Would the response to the disturbance at the home address have been treated differently if there was awareness of the partner’s history of violence towards women? Would the victim, who has been in A&E four times and had two visits from social services over the last year, have been flagged at an earlier date as highly vulnerable?
Of course, the answers are all yes. The joined-up data has the power to help with providing a multi-agency approach and possible safeguarding options for the victim.
Empowering officers with data
While there is a lot of great work being done to improve proactive policing both on the frontline and behind the scenes in data teams, it is not yet joined up effectively enough.
Dealing with this issue at the source means introducing better interoperability of data. Thankfully, there is software available from Civica that can make this happen.
The impact of combining data sources into an easily accessible, consolidated and accurate view of a person, location or object is that chief officers will have a greater level of intelligence with which to make proactive decisions. This approach empowers officers to build a far clearer picture of the context behind crimes before they need to approach locations or civilians.
When an officer is responding to a call, for example, imagine if rather than going system-by-system to find the information they need, they can access everything via one portal that is enabled by the golden nominal view to join up all of the relevant pieces of information mentioned above.
Officers that are better informed are able to take proactive courses of action, which will help build trust in the community. This is also an important piece of the puzzle to improve both police officer and citizen safety, which we will be looking at in more detail in the next articles in this series.
Better Outcomes and building more confidence in police
Let’s see how our scenario could have been different:
The sound of glass smashing on a concrete floor followed by the slam of a door echoes across the landing where Laura waits. She stares over the safety chain through the crack of her open door, her mobile phone clutched firmly to her ear. "Yes... please send someone quickly - there is a disturbance next door...".
PC Sharma and PC Jones are first to receive the call and as PC Sharma navigates their car through the narrow streets to the block of flats, PC Jones is presented with information that dramatically alters how this case is being dealt with.
“Call from Laura McFadden residing at Flat 5a regarding a disturbance at Flat 5e. She has called three times previously. Residents of 5e are Jane Bishop and her daughter Neveah Bishop along with partner, Thomas Purdue. Jane has been in hospital multiple times in the last 12 months, as has Neveah. Thomas is on the violent offender's register. Social services have previously been involved with Jane and Neveah.”
All this information is provided to PC Sharma and PC Jones along with the contact details for the social worker previously involved with Jane and Neveah, allowing them to support Jane in the most appropriate way and avoid unnecessary outcomes.
For more information on how to link up data and analytics systems to achieve the golden nominal view, you can read more about Civica Master Data Management for police forces here.
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