Monday, November 30, 2009
Black Friday shoplifting
Shoplifters on Black Friday ripped of bracelets from the Buckle, rum from Russ's Market, jeans from Sears, a Marie Osmond wallet from Four Star, a sweater from Von Maur, and a portable 7" TV from Kohl's.
Kohl's, by the way, must have opened awfully early on Friday. The shoplifting case was the first of the day, reported at 4:44 AM. The early bird gets the worm.
Friday, November 27, 2009
While the Packers were winning
REALLY DRUNK MAN IN GOLD DODGE 4DR IN FRONT OF LIQUOR STORE
INFANT LEFT UN ATTENDED RED PONTIAC GRAND PRIX
BYFRND IS OUTSIDE WANTS TO BEAT HER UP AGAIN
COMP SAYS THAT PEOPLE ARE TYRING TO DRUG HER AND DO THINGS TO HER
44 YOM SAYS THAT HE JUST WOKE UP AND THAT HIS FEET ARE FROZEN
V PUNCHED & HIT BY UNK PR CAUSNG LACERATIONS/ABRASIONS/V WENT TO HOSP
KWN RESIDENT OF HOME PUNCHED VICTIM APPROX 20 TIMES
V WAS PUNCHED BY KWN PRTY WHEN ARGUMENT BECAME PHYSICAL
V PUSHED AND HIT BY KWN PRTY DURING PHYSICAL CONFRONTATION
MOTHER'S BF KICKED PUNCHED BIT AND SCRATCHED VICTIM
V SCRATCHED WHEN TRYING TO SEPARATE MOTHER'S BF & BROTHER IN FIGHT
V'S EXBF IS OUT OF PRISON & KEEPS CALLING HER UPSETTING V
V'S SON GOT ANGRY AND WAS YELLING AT OTHER FAMILY MEMBERS
DAUGHTER'S EX-HUSBAND MADE THREATS OVER THE PHONE
V'S GF WAS ANGRY & DROVE HER VEH INTO BACK OF HIS VEH TO CAUSE DAMAGE
V'S BF BROKE HER CELL PHONE DURING ARGUMENT
Wednesday, November 25, 2009
LA take away
I have one more post about my side trip to Los Angeles late last week for an NIJ-sponsored meeting on predictive policing. One of the reasons the concepts of predictive policing are being widely adopted, even if the phrase itself does work its way into the lexicon, deals with the realities of municipal budgets. Virtually every city is dealing with a budget crises to one degree or another, and the consensus of opinion is that it is not just a short term issue: it is the new normal.
One of my fellow panelists in LA, San Francisco Chief George Gascon, described the conundrum. He pointed out that police and fire services are consuming an increasing percentage of the total municpal budget, while parks, pools, libraries, and other municipal services have been decimated. Strictly from a budgetary standpoint, we are becoming a police state. It is unsustainable in California. To a lesser extent, this is also true in Lincoln, where, despite our small size, the police department and fire department are becoming a larger wedge in the budget pie every year as the rest of municipal government shrinks. Chief Gascon opined that the use of analysis to better target resources is an imperative to keep the cost of policing at a level citizens are willing to support.
The good news here in Lincoln is that we are already doing an effective job of smart policing. We serve this City at a very low cost per capita, without sacrificing quality. Many police departments could learn a lot from our use of information, problem-oriented policing, prioritization, and prevention strategies as methods to maintain high productivity without breaking the municipal bank.
Last Thursday, the attendees at the predictive policing meeting toured LAPD’s new headquarters building, and their $107 million real-time crime center. The facilities are impressive, and the efforts underway to use analytics and information to improve police services are apparent. I came away, however, with a very positive feeling that even though we may not have the impressive video wall that LAPD’s RACR boasts, we take a back seat to no one in our ability to get actionable information into the hands of our personnel, and to work creatively to provide police services in an efficient and effective way. We should always, though, be on the lookout for ways to improve even further, and open to considering new ways of doing business.
Tuesday, November 24, 2009
Predictive policing
In a nutshell, predictive policing is the practice of using data and analysis to predict future police problems and implement strategies to either prevent or ameliorate those problems. It borrows from the principals of problem-oriented policing, information-led policing, hot spot policing, community policing, situational crime prevention, evidence-based policing, and intelligence-led policing. Can you tell that we have a penchant for catch phrases in policing?
What distinguishes predictive policing from other paradigms is the emphasis on using analysis to anticipate problems--rather than responding to problems after they have occurred. At the simplest level, this might mean using crime analysis to determine the likely patterns of drive-by shootings, then deploying police officers to the areas and at the times these are most likely to occur in order to preempt the crime. At a more complex level, it might mean watching the trends in the spot copper price, and implementing strategies (such as legislation and scrap business monitoring) to reduce the marketability of stolen copper in advance of an anticipated spike in thefts.
None of this is exactly new, but predictive policing is gaining some steam because of the huge influx of data into police work, and our increasing ability to use these data to not only find existing trends and patterns, but to anticipate new ones. We know, for example, well in advance what the proliferation of a hot product like portable GPS devices will mean. When a new nightclub is planned, we can anticipate the impact on crime and police problems. You could build a pretty effective mathematical model to anticipate what happens when 500,000 square feet of retail space is developed, or when 600 two bedroom apartment units are built, because we have lots and lots of data about what goes on in similar situations.
Business has been using these analytics and models for a long time to make decisions: it's not just chance that there's a new Walgreen's on the corner, and Starbucks didn't just throw a dart at the map when deciding where to locate that new store. In policing, we are just starting to use our data to anticipate police problems. We are babes in the woods compared to the private sector.
Whether the predictive policing moniker persists and becomes part of the fabric of policing remains to be seen. There are all sorts of labels out there, some are a flash in the pan, some with great staying power. You might see articles, books, grant solicitations, and conferences galore on predictive policing. Conversely, the term might fade from use rather quickly. Regardless of whether the label gets sticky or not, these concepts are here to stay. Police departments will continue to improve in their ability to analyze data and formulate strategies based on these analyses.
Monday, November 23, 2009
Quite a night
A few weeks ago, reporter Deena Winter asked me if she could spend a shift with one of our downtown officers. Officer Chris Vigil got the assignment, and the result was this article in yesterday’s Sunday Lincoln Journal Star.
It’s good for citizens to get a glimpse into the world their police officers encounter on game days—or for that matter on about any Thursday, Friday, or Saturday. It helps build support for the police, and creates a little greater understanding about the challenges we encounter. While most LPD officers are Husker fans just like other Nebraskans, the experience of game days is not quite the same for a police officer in downtown Lincoln as it is for the fans.
Police experience taxed my loyalty to my alma mater. Back in the 1970’s and 1980’s, I worked every home game for 13 consecutive seasons. When I finally had the seniority to do so, I swore that I would never darken the door at Memorial Stadium voluntarily. For about a decade, I kept that pledge. When I finally returned, I learned that the experience as a spectator with a ticket can actually be rather pleasant. I must admit, though, that I don’t feel entirely disappointed when I must enjoy the game in the man cave at home.
I salute the officers who endure the long, trying, and tiresome day of a Nebraska home football game. They put up with all manner of abuse and deal with some of the worst behavior imaginable by otherwise “law-abiding” citizens. It takes a thick skin, a cool head, and more patience than you can imagine.
Go big red.
Friday, November 20, 2009
Big drop

Thursday, November 19, 2009
Teachable moment
Rita, a teacher at one of our local public high schools, emailed me earlier this week. Monday’s post Roll your own statistics caught her eye. She told me that she was a regular reader of my blog, and had gathered some of our data to create a project for the students in the computer applications class she teaches. She wondered whether I would be interested in seeing the assignment.
Are you kidding? Of course, I was interested. She sent the assignment along in her next email, and jokingly offered to grade my work if I completed the assignment. Now, how in the world could I pass that up? I skipped lunch, and did the assignment.
The students (and me) were given two years’ data by month on thefts from vehicles—one of our most common and significant crimes. The job was to format an Excel spreadsheet, and create a graph comparing the trends in 2008 and 2009. In order to complete the project, students would have to apply some basic Excel skills: create a new workbook, enter data, merge cells, insert rows, format cells, copy cells, calculate formulae, and design and format a line graph. It made a nice project for students with basic Excel skills moving towards the intermediate level.
The best part, though, was the “thought question” at the end of the assignment sheet: “What are some of the most effective strategies that can be used to avoid being the victim of this crime?” I gave Rita my lengthy list, but what I really liked was the idea of high school students—frequent victims of this crime—thinking about the things they can do to protect their car and their stuff. That’s a teachable moment, and I hope she is able to amuse the students in her class with the story of the police chief completing the same assignment they worked through.
P.S. Just for fun, make yourself a table of thefts from vehicles from 2002 to 2008, and look at the annual totals. That’s an eye-opener.