CompStat: A Major Advance in Police Management that Requires Forecasting
NYPD Police Commissioner William Bratton is credited with starting CompStat (Computer Statistics or Comparative Statistics) in 1994. Furthermore, the NYPD credits CompStat and related policies with the over 70% reduction in murders and large decreases in other major crimes in New York City.
CompStat is a police version of management by objectives. It is a monthly peer review, accountability, and problem-solving process in which precinct commanders review the past month's performance measures and discuss actions/plans for the coming month.
CompStat has short-term forecasting needs and requirements that are fueling the interest in crime forecasting and provide forecast specifications:
- Short-term Hot Spot Forecasting - Needed are one-month-ahead forecasts for major crimes (so called part 1 crimes including homicide, aggravated assault, larceny, robbery, burglary, rape, and motor vehicle theft) in as small geographic areas as possible. Needed also is a GIS that can display forecasts as choropleth (color-shaded area) maps with drill down to relevant individual crime points and records.
- Counterfactual Forecasts - Business-as-usual, extrapolative forecasts are needed for evaluating the most recent historical month's crimes. Was last month's crime level in a particular area significantly higher or lower? Has there been a pattern change or just outlier data point? This is an area where traditional forecast tracking signals (e.g., CUSUM) and prediction intervals have application.