Guest blog: Accenture - Finding a Balanced Data Strategy for Policing

Finding a Balanced Data Strategy for Policing

Tom Galloway, Data Strategy & Business Design Manager, Public Safety UK&I, Accenture

Policing in democratic states is currently driven by ‘front line’ concerns which are easily understood by the public. Behind the scenes though, leaders are confronted more and more by the challenges of effectively enabling routine activities. This leads to serious conversations about technology and more strategic use of policing data, with the UK Police National Computer alone containing some 30m individual person records in 2022.[i]

A popular framing suggests that a good business data strategy finds a balance between ‘offence’ and ‘defence’. [ii]  This explores a tension between using data to pursue opportunities while also managing emerging risks. Such risks include costly and unsustainable proliferation of isolated data, posing challenges for security and legislative compliance. For today’s police services there are strong arguments for both offensive and defensive themes.

Senior officers are keen to adopt evidence-based policing practices, using data to promote successful criminal investigations and better protect the public. With a desire to be responsive and adopt a “yes we can” mindset, it can feel tempting to launch into action immediately in pursuit of a wide range of complex and diverging objectives. This is not without its dangers. With complicated portfolios and aging legacy systems, delivery capacity in police data and technology departments quickly becomes overstretched. Many CIOs face challenges maintaining suitable governance and feel urgent work is needed to strengthen the foundations of their data estate.

A well-articulated data strategy helps to resolve these issues by communicating a simplified agenda. More than a vision of the future or another long to-do list for a police IT function, it should outline a framework for deciding between competing data objectives at an organisational level. A data strategy suggests not just what to prioritise and how to pursue it, but also why some specific goals should be pursued to the exclusion of others. A really good data strategy may even specify which potential objectives are less essential, preserving scarce capacity for more urgent tasks.

Among today’s police services, systemic themes that frequently merit attention include both data visibility and data quality. Better cataloguing of data assets plays a key role in kick-starting new initiatives, by referring people quickly to a central version of the truth. It also creates a basis for the difficult next stage of identifying, prioritising and resolving known quality issues within key datasets.

Having identified the necessary improvements to basic capabilities, we can then turn to the more interesting ‘operational’ policing data journeys. Perhaps we want to deliver an intelligence capability related to a specific crime type. Perhaps it is more about improving the efficiency with which physical assets or patrol resources are deployed (i.e. ‘precision policing’). Identifying a few key policing questions that refocus underlying improvements will create a much more harmonious trajectory and a much more streamlined set of technology investments.

Even with a well-calibrated data strategy, this is rarely an easy or uncomplicated path. In 2020 the National Policing Digital Strategy proposed that “data-driven insight has the potential to be a ‘force multiplier’ – increasing the predictability, precision, pace and impact of our interventions…”[iii] Policing organisations need to articulate what matters most to them, identify the most important basic enabling factors, and only then can they set about reaching their destination. For most services heading into 2023, refining and maintaining their overarching data strategy is still the first step in that journey.

This content represents the individual opinions of the author and is provided for general information purposes. It is not to be used in place of consultation with Accenture’s professional advisors. This document refers to marks owned by third parties.  All such third-party marks are the property of their respective owners. No sponsorship, endorsement or approval of this content by the owners of such marks is intended, expressed or implied.