Unlocking the power of technology and data to transform community policing and improve public safety

Unlocking the power of technology and data to transform community policing and improve public safety 

Technology is embedded in every part of our lives-transforming how we connect, work, learn, and access services. This shift is critical to supporting the government's 'Take Back Our Streets' mission, with part of the aim being to crack down on antisocial behaviour with more neighbourhood police. 

Facing budget constraints, policing is under pressure to deliver more with less, while AI-driven innovations open new avenues for efficiency. Instead of seeking new solutions, there's growing interest in maximising current technology. At Sopra Steria, we're aligning our product roadmap with Police Industry Charter principles by focusing on: 

• Interoperability - designing technology solutions that integrate with existing systems. 

• Collaboration and partnership - enabling partnerships with a purpose, building shared objectives and working collaboratively to deliver the highest standards of service to benefit the public. 

• Maximum Transparency by Default (MTBD) - ensuring clarity on data use and value delivered. 

As part of the 'Take Back Our Streets' mission the government has committed to Neighbourhood Policing (NHP), focusing on issues like antisocial behaviour, knife crime, and violence against women. Revitalising community policing is essential, even more so given the new digital and local threats that officers now face. Effective responses will vary based on local challenges, demographics and preferred methods of communication. 

Technology and data are key to enabling these traditional policing strategies and ensuring they meet the specific needs of each community efficiently and effectively. Here we discuss the factors which contribute to the successful implementation of policing strategies that align to Government priorities. 

Engagement

Building trust and confidence relies on effective community engagement. Each community's needs are unique, so using a data-driven approach is essential. Police forces have access to vast data sources-ranging from crime data and intelligence, to census and open-source information. 

The challenge is transforming this data into actionable community insights. AI, especially machine learning, is speeding up this process, delivering tailored, relevant data. With it, police can avoid generic approaches and customise their engagement strategies to meet specific community needs. 

Targeting activity 

Since the introduction of the Anti-Social Behavior (ASB) action plan, aimed at restoring public confidence that policing will deal with ASB quickly and visibly, several forces have received funding in support of targeted visible hot spot patrols. A recent Home Office evaluation of the effectiveness of hot spot policing demonstrates compelling benefits, such as:  

• Reduced crime rates by 7%  

• Indicative ROI of £2.20 for every £1 spent 

This strategy, concentrating resources in high-crime areas, has become integral to broader crime reduction efforts. 

Research indicates hot spot tactics are most effective when activity is clearly recorded and timed, as shown by the 'Koper Curve', which recommends a 10-15-minute presence per visit to balance deterrence with efficiency. Transparent reporting on officers' actions, such as stop-and-search or public interactions, is crucial for building public trust.  A 2017 study by Lum and Koper shows that recording and reporting officer activity in hot spot policing builds public trust. Transparency about interactions and stop-and-search powers boosts confidence and deters abuses. 

Our Patrol Planning tool is an extension of our computer-aided design (CAD) technology: SmartSTORM. The module allows forces to map out and geofence hot spot zones, select waypoints or locations of interest, and track officer movement within them. And they've been designed specifically for hot spot policing by experts with direct experience in managing hot spot policing teams.  Patrol Planning helps forces create an evidence-based, preventative approach to crime hot spots without the need for officers to use new technology or manually record their activity.   

Hot spot policing reduces crime rates and harm while improving public trust through visibility. Data-backed hot spot policing has proven effective against ASB, violent crime, and offences related to violence against women and girls (VAWG) in night-time settings. 

While valuable, police officers' local knowledge is less effective than evidence-based hot spot identification. A 2019 study by Braga et al found data-driven police deployments significantly reduce crime, especially violent crime, without displacing it. 

Relying solely on instincts can introduce bias and lead to inefficient use of resources, detracting from transparent, evidence-based policing. 

Intuitive prevention and intervention 

Using AI for crime prevention might sound futuristic, but it's already helping police and partners make informed decisions. AI is especially useful in guiding Secondary Prevention efforts, helping police pinpoint where to focus on at-risk groups, and providing early intervention for young people likely to become offenders or victims. 

Data sharing and interoperability with partners 

Bringing together stakeholders like police, healthcare providers, local authorities, schools, and community groups enables a more comprehensive approach to tackling crime at its roots. Effective collaboration hinges on robust data-sharing frameworks that support smooth information flow, accurate records, and clear decision-making. This framework not only enhances individual-focused responses but also supports broader strategic initiatives, allowing stakeholders to align on social issues, policy efforts, and impactful change with a shared understanding and commitment to resolve them. 

Evidence based learning 

Policing is fast paced, with constant emergencies, complex investigations, and high demands, leaving little room for in-depth performance evaluations. While quick 'hot de-briefs' are standard, comprehensive evaluations are rare. 

To drive continuous improvement, adopting a learning-based culture supported by data analysis is essential. AI can play a big role by handling repetitive tasks and interpreting data, freeing up officers to focus on actionable insights. This blend of technology and human expertise allows for efficient, meaningful evaluations that help adapt and evolve practices over time. 

The role of technology in modern policing 

In summary, the traditional 'Peelian Principles' of Neighborhood Policing remain largely unchanged, however the methods of implementing these principles successfully require significant thought. For community policing to be effective, it must combine the solid foundations it is built on with transformative technology and data insights, to ensure activity is targeted and productive. Harnessing new technology is crucial in reducing back-office activity and inefficient processes, allowing police officers to be exactly where they are needed, in the community. The public should expect no less.  

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