Forget broken windows. Data is a criminal’s worst nightmare
New York in the early 1990s was a cesspit of crime and corruption. Inefficient and under-supported justice systems battled against organised crime and street hoods, while citizens cowered in their homes – literally too scared to walk the streets.
Contrast that to the New York of the 21st century, a global metropolis where crime has become a diminished event. In 1990, New York experienced 112 380 robberies, a figure that fell to 18 187 by 2018. Ditto for murders, which collapsed from 2 605 in 1990 to 289 in 2018.
Many have claimed credit for these falling figures. Often the most famous reason given is Broken Windows, a theory that states if you deal with the small problems in a city – vagrant buildings, idle beggars and so forth – you can tackle the big issues as well. But Broken Windows was mostly a PR campaign to show New Yorkers that their municipality was doing something.
Instead, the real change came through CompStat, an integrated data analytics system that provided several benefits. The two most important were crime intelligence predictions and performance accountability.
What changed New York from crime pit to international hub was data analytics. It’s a capability that all police and security agencies should invest in, says SAS South Africa’s Director Sales: Government Security Cluster, Francis M Makai-Mateyo: “Using data is a big benefit that anybody, especially in police services or security clusters, should take. It helps provide insights on crime trends, and as an accountability tool, it keeps track of where the information was when it came in, who put it in how it was, how it was recovered, and what it’s going to be used for.”
Empowering existing investments
Security clusters have not been ignoring the value of digitisation and have invested in large digital ERP systems to help manage their information. Yet, while those additions have been potent, they also have big limitations when it comes to generating insight, creating process visibility and recommending improvements.
The field of analytics opens many new doors on information, without disregarding the investments made on previous systems. Makai-Mateyo refers to the South African Police Force as an example: “SAPS has been working on becoming an exemplary police force that uses digital technologies. They installed a mainframe around 20 years ago. But as with so many modernisation projects, it doesn’t reach all their requirements. That’s for different reasons, such as buy-in or not aligning with established processes. But they don’t have to get rid of that system.”
Rather, those systems are accumulating a lot of essential data that can be analysed to help improve performance and speed up processes. A modern analytics platform solution can securely plug into different data sources and aggregate information that different people in the organisation can use. This can relate to the performance of individuals, but also tracking the life cycle of a case while reducing fragmentation and duplication.
“Let’s look at an electronic docket,” Makai-Mateyo explains. “Analytics can look at the information captured about the offender or anything, as well as all the data that’s around that person or case. So if, for instance, there is a Francis M Makai, and a Francis Makai, it would be able to single view each of the two separate offenders, or if the offender is charged for two different things in different places. Through analytics, you can connect those dots automatically.”
Zoom out further, and it’s feasible for a case file to exist on one continuum, from the police service to the courts to correctional services. While systems such as ERPs can capture the information, analytics adds deep insights. Since it can tap into different systems’ databases, it’s not necessary to consolidate the various systems across different stations and jurisdictions to create detailed analytics.
Lock and loading data
The benefits are clear, and the disruption is minimal. So how can decision-makers in the security cluster get started with analysing their data? Caleb Sibeko, Head of Public Sector Sales at SAS South Africa, recommends a few steps to consider. First, avoid reactively going for a big bang approach: “It’s very tempting to want to solve everything at once. But the do-it-all big bang approach is something from a past era. Today, you can introduce and scale a platform from very small to very big. So I advise that you start small. Look for specific problems you want to solve and apply the analytics to focus on those.”
An example of this is an analytics service that focuses specifically on detective case files and information gathering. But analytics can be used to address any area, including staff management (HR) and vehicle management (motor pool).
Next, it’s essential to have a data management strategy: “Put in place a data management strategy that integrates data across different clusters. This will create a federated view of your data. For instance, if we focus on the integrated justice system, you will have a centralised federated layer that will provide an aggregated view of the data, combined with the case management system that hasn’t been digitised.”
Lastly, look at best practice around the globe. In the decades since CompStat, different security clusters have been working on and investing in new generations of data analytics systems suited to their requirements. Today, there is a wealth of such information, which can be explored with the collaboration of a data analytics solutions provider. This approach also deals with another challenge: access to data management skills.
A well-informed and organised security cluster can comfortably beat crooks and criminal enterprises by staying a few steps ahead of them. The missing ingredient is often information, something modern analytics can provide without disrupting existing systems.