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Effective Crime Forecasting Using Historical Data for Enhanced Police Resource Allocation

This report outlines a data-driven approach for police departments to enhance their crime forecasting by utilizing historical crime data and census information. By collecting and analyzing specific parameters such as crime date, type, location, and suspect demographics, law enforcement can identify trends over time. This method enables departments to pinpoint crime hotspots at the zip code level, facilitating strategic police presence deployment and resource allocation. Ultimately, this proactive strategy aims to reduce crime rates and improve community safety through effective data analysis.

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Effective Crime Forecasting Using Historical Data for Enhanced Police Resource Allocation

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  1. Analytic Assignment 2 Alden Buric, Heidi Habecker, Tzu-Chi Hsia, Ryan Merckel

  2. Forecasting • Use Historical Data • Use Trends • The Police can use their own data rather than a third party. • For more specific information such as education and income, they can use census data.

  3. Parameters • Most departments already do this but the Police will need to collect information such as: • Date • Type of crime (as specific as possible) • Address and zip code where crime occurred • Age, race, and address of suspect

  4. Trends Using this data, the Police can watch trends over months, type of crime, and in certain zip codes. • For example, they can run an all-crime report across all zip codes and put that data into a scatter-graph to pin-point the largest concentration of crime and the zip codes in which they occur. • They can then run reports that are zip code specific to look at trends month over month by type of crime. • Using these trends will tell them when, and in what zip codes to increase Police presence.

  5. Dashboard Sample

  6. Analytics - Figure out staffing levels - Which zip codes need more officers than others - Cut costs through effective forecasting - Questions? Comments? Concerns?

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