1. Crime Analysis for Problem Solvers Problem Oriented Policing Conference Charlotte, NC October 2004

2. #1 How should crime data be used?

3. Crime is relative 2003 Data

4. Auto Theft Vehicle Burglary Target 4 Walmart Auto Theft Time of Day Auto Theft Day of Week Total Vehicles Stolen: 30 % Recovered: 50% Avg. Time at Lot: 109 min. Avg. Vehicle Year: 1988 Walmart had 18 incidents predominantly between 12:00 – 20:00. The top makes include Fords and Hondas. Most Common Lot Addresses within Target Area #4 Walmart – 75 N. Broadway Best Buy – 59 N. Broadway Top Makes/Models Toyotas & Nissans

5. Motor vehicle theft trend

6. Types of motor vehicle theft

7. Recovered vehicles

8. Recovery by vehicle type

9. #2 Make better use of Calls-for-Service data

10. Top 10 Calls for Service Chula Vista 2003 1. 1.False Burglary Alarm8,882 12% 2. 2.Disturbance by Person3,977 5% 3. 3.Domestic Violence3,692 5% 4. 4.Traffic Collision3,680 5% 5. 5.Noise Disturbance2,759 4% 6. 6.911 Hang Up2,397 3% 7. 7.Vehicle Theft2,327 3% 8. 8.Petty Theft2,091 3% 9. 9.Vandalism1,983 3% 10. 10.Suspicious Person1,806 2% Total 33,594 44%

11. Domestic Disturbance Calls

12. #3 What amount of data should be used?

13. Too Much Data

14. Miami

16. Too Little Data Use at least 15-20 per category.

17. Drug-related calls

18. Adding data

19. #4 What type of data are most appropriate?

21. Estimating Magnitude of the Problem Complaints to police31 Arrests201 Suspects148 Chronic offenders60

22. Estimating Offenses Chronic offenders60 Tricks per day 3 – 5 Tricks per day 3 – 5 Days per week5 Days per week5 Weeks per year50 Weeks per year50 Estimated transactions67,500 Clearance rate 3/10 %

23. #5 How else can In- house data be used?

24. Utilize Narratives To determine usefulness of data To understand context of a problem Content analysis and coding for additional statistical analysis

25. Example: Construction Site Burglary Difficulty Index (Four Characteristics) SkillTransportAccessTime 0 No skill Walk away Outside/visible /unattached 0 to 5 minutes 1 Heavy, awkward, forcibly removed Car, small truck Outside attached, inside visible attached and/or unattached 5 to 10 minutes 2Skills/tools Truck and/or trailer Secured inside More than 10 minutes

26. Difficulty Index: Initial Analysis Difficulty Index ValuePercent 02% 14% 211% 3 416% 528% 613% 78% 87% 72% Port St. Lucie, FL Construction Site Burglary Analysis: N=155

27. Difficulty Index: Preliminary Analysis SkillTransport PercentPercent No skill 12% Walk away 12% Heavy/awkward/ forcibly removed 37% Small truck/car 70% Skills/tools51% Large truck 17% AccessTime PercentPercent Outside/visible/unattached21% 0 to 5 minutes 35% Outside attached, inside visible attached and/or unattached 41% 5 to 10 minutes 37% Secured inside 38% More than 10 minutes 28% Port St. Lucie, FL Construction Site Burglary Analysis: N=155-158

28. #6 When In-House Data Isn’t Enough

29. Auto Theft Offender Interviews A number admitted taking stolen cars into Mexico for sale A number mentioned the ease of breaking into older Toyotas (as well as Hondas) A number said they can use any old Toyota key to unlock some of the Toyotas (didn’t even need to shave the key) Many admitted to stealing from parking lots because it offered so many choices in unguarded settings

30. Las Americas Safer than CV Mall in Other Ways: -69% burglary -60% fights/disturb. -38% grand theft -84% petty theft zero robberies (16 at Chula Vista Mall) Number of Auto Thefts Access Control: A Critical Parking Lot Feature

31. Paseo Pa rk = K/1st = All grades Bus Stops AM Drivers and Walkers Traffic Congestion Problem: Who Drives to School and Why?

32. Observations of Drop-Off/Pick-up Times Explain Afternoon Crunch School start time: 8:30 School end time: 3:00

33. #7 What Analysis is Most Useful to Police Managers?

34. Volume Outliers: 10 Worst Parking Lots Account for 15% of all Auto Thefts in City

35. Rate Outliers: Vehicle Theft Rate Per Spot vs. Top 10 Lots Median: 3.1

36. #8 How can I use mapping to understand a problem?

37. Mapping Use mapping sparingly Should not be the central method used to direct police efforts Mapping most useful for bringing data together, scanning, and presenting analysis results.

38. Should we deploy officers based on this map?

39. Example: Scanning

40. Example: Bring Data Together

41. 2001 Recovery Rates - Trucks 2001 Recovery Rates - Cars Example: Presentation of Results San Diego County Recovery Rates

42. MOVED BUS STAND CAB STAND P P P P P=parking lot =no admission =no admission P HIGHWAY closed section closed section TØNSBERG BRIDGE P NEW CAB STAND Moved barristers Example: Presentation of Results Tønsberg downtown area From: Gypsy Cabs in Tønsberg – a Case for Problem-Oriented Policing Johannes Knutsson, National Police Academy and Knut-Erik Søvik, Vestfold Police District

43. #9 How do I know there’s a difference?

44. Test Relationships Ad hoc reasoning Use of statistics Statistical vs. practical significance

45. MeanSDN Residential Burglaries4.3623.66614 Construction Site Burgs2.524.16225 Date Span Port St. Lucie, FL Construction Site Burglary Analysis

46. Mean*SDN Residential Burglaries7.318.47479 Construction Site Burgs14.647.79130** Time Span *Statistically significant at the.01 level **58% of the CSBTs has a date span of 0 or 1 Port St. Lucie, FL Construction Site Burglary Analysis: N=155-158

47. #10 Did it work?

48. Effort to Reduce Traffic Collisions Through Citations Results: -Very weak correlation between cites and collisions -Not statistically significant Chula Vista Police Department

49. Domestic Violence Intervention Intervention Began

50. Domestic Violence Intervention Total # of DV Incidents Total # of Repeat Incidents Repeat Rate 1995 (pre-) 1,71359435% 1999 (post) 1,52752534% # of people revictimized 1 time 2 times 3 times 4 times 5+ times 1995 (pre-) 65%19%10%3%3% 1999 (post) 65%17%8%2%6%

51. Anti-Theft Device: Passive Immobilizers in Honda Accords Year Immobilizers Introduced Into Accords

52. Discussion and Questions Contact Information: Deborah Weisel dlweisel@social.chass.ncsu.edu dlweisel@social.chass.ncsu.edu Karin Schmerler kschmerler@chulavistapd.org kschmerler@chulavistapd.org Rachel Boba rboba@fau.edu