Measuring the ROI of Crime Analytics: Case Study from Lancaster, California

This is the final blog post of the Smarter Cities: Building Safer Communities in the Digital Age series. This series explores how analytics has empowered the street level bureaucrat, redefining the way public safety officials keep communities safe. Across the country, public safety organizations are leveraging crime analytics to improve efficiencies and connecting employees to data in new ways.

Cities rely on sound leadership and passionate public servants to improve the quality of life for citizens. In order to create a vibrant and healthy citizenry, organizations need to be smart as they deal with shrinking budgets to build sustainable economic growth for communities. This means cities need to adopt tools to proactively analyze data to improve decision-making.

Report Highlights

  • The City of Lancaster has adopted an IBM SPSS and Esri ArcGIS solution to fight crime
  • The City of Lancaster attained an ROI of 1301% in a payback period of .1 years since implementing a SPSS and ArcGIS solution to fight crime
  • Be sure to view other blogs in this series, exploring how Miami-Dade County and New York City have leveraged analytics in their public safety departments

As cities continue to implement transformative technology, agencies must accurately measure the return on investment (ROI) of technology adoption. The City of Lancaster is a great example of the benefits of leveraging analytics in the digital age. IBM recently conducted a study measuring the ROI of the City of Lancaster’s predictive analytics program. The case study from the City of Lancaster is highlighted below.

ROI Case Study: City of Lancaster

The City of Lancaster, California, was incorporated in 1977 and is part of Los Angeles County. The city currently has a population of over 150,000. Through a contractual arrangement, the Los Angeles County Police Department provides a fixed number of personnel to cover Lancaster as well as 40 other cities.

In 2008, Lancaster was in the midst of intense budgetary pressures and realized they needed a new way to protect the community and efficiently allocate resources. The City of Lancaster had an annual police budget of $24 million, and the prospects of additional funding were highly unlikely.

The city ultimately hired James Kobolt as the first Senior Criminal Justice Analyst in January of 2008. Kobolt purchased IBM SPSS and ArcGIS licenses to explore how to fight crime in a new way. Lancaster public safety officers estimated that roughly 35 percent of their time was spent on reducing Part I crimes, which are defined as murder and nonnegligent homicide, forcible rape, robbery, aggravated assault, burglary, vehicle theft, larceny and arson. The IBM SPSS and ArcGIS solution would be targeted to specifically fight crime using data.

By 2010, Kobolt had created predictive data models that accurately showed crime patterns. Esri maps showed heat maps and color codes to show crime throughout the city. These maps have provided the City of Lancaster with new insights and improved decisions as to how resources are allocated.

The results were staggering, as the city witnessed a 37% decrease in crime from their benchmark set in 2007. IBM also worked with Nucleus Research to understand the ROI for Lancaster County, benefits from the study included:

  • Lancaster saw a 35 percent reduction in Part I crimes in 2010 and a 42 percent reduction in 2011 compared to the 2007 benchmark rate
  • Over $800,000 savings in the partial year of 2010 when predictive analytics were implemented
  • By using predictive and geographic analytics, Lancaster was able to gain over a million dollars in productivity on a year-over-year basis.

The IBM case study also highlighted some initial costs Lancaster incurred to adopt a predictive analytics solution. The project costs included:

  • Software: The case study identified that the majority of the startup cost consisted of the original SPSS and ArcGIS licenses.
  • Hardware: Minor hardware costs were incurred due to purchasing SPSS and ArcGIS. The costs were minimal as they were able to host this solution on existing services.
  • Training: Costs related to having users learn SPSS and ArcGIS software, and how to input information correctly.
  • On Going Support: The city hired a data scientist as a consultant to clean data and structure data correctly for SPSS and ArcGIS feeds. Ongoing support costs have been minimal and primarily consist of software assurance and maintenance costs.

One important note from the case study is: “Since ongoing reports are automated, the current support for this software takes up less than an hour per month, which allows the City of Lancaster to spend less time finding the correct information and more time to translate these maps and trends into effective strategies to fight crime.”

The ROI was calculated to be 1301%, but to me, the more impressive number was the payback period was only 1 year. In other words, by investing in technology – the agency very quickly saw gains that led to cost savings.

The case study goes into more detail on how the ROI was calculated and is a great example for public sector professionals to explore the benefits of data analytics applied in law enforcement.

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