November 17, 2025 • 18 mins
Episode: 00293 Released on November 17, 2025 Description: In the fifth installment of Research Remix, Jason Elder and Jamie Roush unpack a 2014 study by Joel Kaplan, Philip Marotta, Eric Piza, and Leslie Kennedy examining whether the physical landscape contributes to felonious assaults and batteries against police officers. Using Chicago Police Department data, the researchers identified how risky facilities such as foreclosures, problem buildings, bars, schools, liquor stores, gang territories, and apartment complexes combine with environmental features like alleyways, poor lighting, and crowd density to elevate officer danger. Jamie explains why these spatial elements matter, how analysts can integrate non-traditional spatial data into proactive officer-safety work, and how dispatchers and CAD systems can benefit from enhanced risk-flagging. The conversation also highlights opportunities for analysts to expand their GIS layers, develop yearly governance on spatial data sources, and build prioritization models that identify the highest-risk locations and times of day. This episode is a practical roadmap for analysts aiming to support officer safety through environmental awareness, spatial modeling, and data-driven risk mitigation. 🎧 Listen, share, and keep talking! [Note: Description produced by ChatGPT.] Get to know more about Jamie, Joel, and Eric by listening to their previous episodes: https://www.leapodcasts.com/e/atwje-jamie-roush-the-aha-moment-analyst/ Dr. Joel Caplan: https://www.leapodcasts.com/e/acia-risk-terrain-modelling-dr-joel-caplan-teaches-us-everything-we-need-to-know/ Dr. Eric Piza: https://www.leapodcasts.com/e/atwje-eric-piza-the-researcher-at-heart-analyst/ Name Drops: Related Links: https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1193&context=jj_pubs https://www.cpted.net/ https://popcenter.asu.edu/content/understanding-risky-facilities https://www.simplypsychology.org/routine-activities-theory.html Association(s) Mentioned: Vendor(s) Mentioned: Contact: jamielroush@gmail.com,  https://www.linkedin.com/in/jamie-roush-5b399967/ epjets@stockton.edu Transcript: https://mcdn.podbean.com/mf/web/x292indjf8a3t6mm/RR04_transcript.pdf Podcast Writer: Podcast Researcher: Theme Song: Written and Recorded by The Rough & Tumble. Find more of their music at www.theroughandtumble.com. Logo: Designed by Kyle McMullen. Please visit www.moderntype.com for any printable business forms and planners. Podcast Email: leapodcasts@gmail.com Podcast Webpage: www.leapodcasts.com Podcast Twitter: @leapodcasts
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Welcome to Analyst Talk with Jason Elder.
(00:01):
It's like coffee with an analyst,or it could be whiskey with an
analyst reading a spreadsheet,linking crime events, identifying a
series, and getting the latest scoopon association news and training.
So please don't beat that analystand join us as we define the law
enforcement analysis profession.
One episode at a time.
How we doing?
Analysts?
Jason Elder here with anotherLE, a podcast Deep Dive
(00:23):
research remix with Jamie Roush.
Jamie, how we doing?
Doing great, Jason.
So before we get into our topictoday, We're mostly through the
college football season now.
Are you okay with Florida State?
'cause they started outhot and then they went not,
yeah, it's been a tough, toughseason for Florida State, but.
Know, we'll see what happensin the next couple games.
(00:44):
We still have a few more, including theSunshine Showdown against the Florida
Gators, so we'll see what happens.
Yeah, I, I do feel that it was a littlebit of a tease that Alabama game, that
first game of the season was such a tease.
'cause it, they came in so flying high.
They're like the firstthree or four games.
Oh yeah, it was definitely a teasefor all of us, I can tell you.
Still potentially bowl eligiblelooks like again, a couple more
(01:06):
games for the rest of the season.
So we're just kind of hoping toget into those, the postseason
with a, at least a Good Bowl game.
So.
All right, very good.
All right.
What are we talking about today?
So today, Jason, we're gonna throw itback to the spatial element of crime
that we've talked about again on someof the previous research remixes.
We're gonna talk about whether thespatial element of crime is correlated
(01:27):
to felonious battery of police officers.
We're gonna really answer this kindof question of does the physical
landscape play a role in batteryand assault of police officers
and law enforcement officers?
So as obviously all of us know lawenforcement officers by their nature
encounter these situations where they'retasked and faced a lot of risk and in
(01:47):
a lot of cases non-accidental injury.
Again, there's lots of reasons for that.
Aggression towards police, naturaluse of force incidents, and while
the research in the past in both ofthose areas has really focused on
offender and officer characteristicsthat give rise to non-accidental
injuries of officers, there's beenvery little research that's actually
(02:08):
focused on the physical landscape.
And are there specific spatial elementsacross the landscape essentially
that give a higher probability?
Of assault and battery ona law enforcement officer.
So in 2014, Joel Kaplan and EricPiza and others kind of explored
the environmental characteristicsof where this type and this very
(02:29):
specific type of violence occurs.
They looked specifically at kind ofareas for violence that are often more
narrow or kind of like small spaceslike housing complexes with alleyways
which can then decrease the distancebetween an offender and an officer.
They looked at abandoned structures andunlocked facilities and secure shelters,
(02:51):
places that could potentially give riseto ambushes, which end up in battery
and assault on law enforcement officers.
And then they often just looked atregular locations with just a high crowd
density, people that are in very tightquarters and very, very tight spaces.
Often places like bars and nightclubs.
And so what the research team did isthey used data from the Chicago Police
(03:12):
Department specifically related to assaultand battery with a firearm that was
directed towards law enforcement officers.
And they started focusing in on kindof these particular types of areas
and they found essentially that thereare places that are risky, risky
facilities, which we often have heardfrom problem oriented policing as well.
(03:33):
But they also looked at thingslike data on foreclosures, data on
abandoned buildings, code enforcementlocations, areas where there is a
limited amount of street lighting.
And essentially they kind of focusedin on looking at are there a series
of characteristics that give rise tothese types of assault and batteries?
Now, what's really interesting about thisis that for those of us who have done
(03:54):
this work for a long time, we know that.
Crime prevention through environmentaldesign or subhead is a very big part
of being able to prevent crime orworking towards prevention of crime.
So what the research team found inreviewing this data and looking at these
geographic characteristics is that theyfound essentially that in this order.
Foreclosures or problem buildings.
(04:15):
Again, those ones with large codeenforcement, unsecured properties,
bars, schools, gang territories,or gang affiliated locations,
apartment communities, and liquorstores pose the highest risk and
kind of the highest probability of.
Finding assault and batteriesat these particular locations.
Now, it's probably not uncommon formost of us to think about it, but the
(04:38):
idea is, is that the researchers notedthat when you take these locations,
these risky type of facilities,and you intersect characteristics
like dim lighting, poor lighting.
Alleyways, street corners, thingsof that nature, that it obviously is
a higher probability of the abilityto have an assault and battery
on a law enforcement officers.
(04:59):
They said that essentially some ofthese locations, not surprising,
the unsecured buildings, the problembuildings and the foreclosures are
often locations with no governance,no one to watch them, to protect them.
And essentially that is.
One of the conclusions that they drewthat kind of led them to say, essentially,
those are probably locations that are thehighest for these types of risk as well.
(05:22):
Now for the analysts who are listeningtoday, they also added in the temporal
component, which all of us focus in on.
When we look at space, we lookat space and time together, and
they focus in on saying thatthere are specific times in which.
Officers respond to calls for service orCAD runs at these risky locations that
also correlate to a higher probability.
(05:43):
The 2:00 AM closure of a bar,for example, is gonna be.
A compounding factor to givingrise to assault and battery
on law enforcement officers.
Hmm.
So there's a lot there.
I, I guess my first thing that I'mthinking of is, it reminds me of
routine activities theory, and that'swhere my head was going, because
(06:05):
it seems like in some of those.
Situations.
It might seem odd to say that an officerdoesn't have a capable guardian, but
in some of the theory with routineactivities, the, the lighting, the.
Spacing that deals directlywith routine activities.
It's dealing with that idea that there'sa certain situations, that there is
(06:30):
this absence of a capable guardian.
Yeah.
And essentially bringing rise to a crime.
And in this particularcase, a very violent one.
That is then directed to towardsthose law enforcement officers.
Again, for various reasons, whetherit's just natural aggression or again,
a person that has a disdain for lawenforcement or someone who is prepared to
actually ambush a law enforcement officer.
(06:51):
There's many differentscenarios in which those things.
Give rise, but to your point, absolutely.
There really isn't a guardian in thosesituations and that that's essentially
what creates this type of harm forlaw enforcement officers as well.
Yeah.
My, my second thought is someof those types of situations
that , you listed, those might notnecessarily be part of the analysts.
(07:18):
Database, right?
I mean, obviously you're gonnahave your liquor stores, right?
Or your bars, you might have that.
But some of these either condemnedbuildings or problem buildings , it
might not be described that way.
So you're just gonna get anaddress and you might not have the
particulars of that address there too.
(07:40):
Categorize it as one of those high threatlocations as described in the study.
Yeah, Jason, I think that's a reallyimportant point, and one of the reasons
why I thought this study was importantto bring to this particular podcast is
that it really is a call for analyststo start thinking about non-traditional
data sets that are spatial in nature.
In some of the previous researchremixes we've talked about
(08:02):
non-traditional data sets.
Again, for workload or other types ofthings, but this is really a call to
start thinking about your inventoryof your spatial data and do you
really have a good handle on all ofyour jurisdiction's risky facilities?
Is that data being updatedon a regular basis so that.
(08:23):
When you're looking at this kind ofdata, you have the ability to do modeling
and being able to provide insightsabout these particular locations.
To me, I think this is really important.
Although this topic is one that probablyanalysts wouldn't think about is within
the purview of their day-to-day work.
We are in the US right now reallyfocusing in on officer safety and health
(08:45):
and wellness and if we can as analysts.
Be able to use things like restrainmodeling and more spatial types of
approaches to identify these locations atspecific times that then create a higher
probability for our officers to be goingthrough an assault or battery or potential
for assault or battery situation.
(09:06):
Providing that proactively to ourorganization becomes really valuable.
And it's something that then theorganization can consume and say, Hey,
maybe we change our call protocol at thistype of facility at this time of day.
And you create some of these kind ofwhat we call alternate response plans.
(09:26):
And I think that becomes really, reallyvaluable for organizations as well.
I think one of the criticisms that peoplewould say is, is that most agencies.
A lot of officers would say, well, Iknow that these are, these are places
that I potentially can be more harmedor have a non-accidental injury.
But I think within the data we always findinsights that maybe correlate things in
a way that not everybody had, would'vethought that location at that time of day.
(09:51):
And again, that's where analystshave the ability to really kind
of put that data forward with thismindset of kind of the officer
safety, wellness and health approach.
Yeah, and this is an alsoan great opportunity to help
out the dispatchers as well.
The 9 1 1.
Dispatchers because this isobviously information that they
(10:14):
should know and be aware of
yeah, I mean, I think it caninform CAD systems, right?
You can create additional, almostevery major CAD system has the
ability to create additional flags.
This is another data source essentiallythat can help with that flagging.
It then does alert the dispatcher as well.
But I also think from a dispatchperspective, it really gives value
(10:36):
to dispatchers being able to say,at this time of day, in this type of
facility, I might have to not onlysend additional officers, but if it
breaks bad, what is our protocol gonnabe and how are we going to adjust to
send more people to these locations?
Right?
So it's kind of more of like this ideathat dispatchers can proactively be aware.
(10:57):
If something does go wrong in asituation like this is if you do have an
assault or battery on a law enforcementofficer, that this is what our protocol
is specifically gonna be for that,for these type of facilities as well.
Yeah.
It almost seems like it's almostthe two extreme situations.
It's scenarios where it's.
We talked about the lighting or justproblem buildings something where it would
(11:21):
just be maybe the officer on their own.
And then there's the other extreme whereit might be a bar or a skull where there
might be a lot of people on there andyou're dealing with more maybe uprising
type of scenario there.
So it seems like it's the both extremesthat got covered in this study.
Yeah.
What I like about that too, and again,I think this is really important
(11:44):
for the analysts listening, is that.
If you're taking this data and youare proactively looking at it and
saying is there a higher probabilitypotentially of officer assault
and battery at these locations?
You also can create a priority systemof the output of the analysis that you
create to say these are priority ones,these are the most risky facilities,
(12:06):
and these are the most risky timesfor this type of behavior activity.
But then you can also saythis is the least as well.
Again, I think it gives your organizationthe ability to develop some tactical
plans that are informed because maybefrom a staffing workload dispatch
capability, you can only really focusin on utilizing that priority one data.
(12:28):
But then when things free up or youhave the ability to look at some
of those priority twos or threes,et cetera, that the analyst has
provided now, then it gives the pathfor the organization forward, right?
Kind of.
Helps them say, Hey, if we can onlyprioritize a small group, here's the
small group we're gonna prioritizetoday, but then next year, let's
revisit this list again and thenlet's reprioritize next year as well.
(12:50):
As an analyst, you're actually creatinga product essentially that has strategic
value over a. Multiple periods oftime just by prioritizing that output.
Hmm, that's a good point.
I you talked about data setsand, expanding, the types
of data that analysts have.
I mean, this is definitely a goodexample of, of something to make sure
(13:12):
that your mapping layers have all these.
Particular types of, buildingsas, as I mentioned before, some
of them are gonna be readily.
We're gonna categorize them as such, butthere's gonna probably be some on here
that's on this list that isn't readilygoing to be designated as as such.
(13:36):
So it's definitely something that,that might be a, I I'm always trying
to give interns some, some jobs thatmight be a good thing for an intern.
It to do go through your list andmake sure that your geographic
database, your data is, is up to speed.
Yeah.
And I used to think about data in kind ofmulti different layers in terms of like
(13:56):
where the source of the data comes from.
Right?
So you have data that's within your.
Department or again, and then you've gotyour city county data, you have your state
or other governmental data, and then youhave private business data as well, right?
So looking at a list like this thatwe're gonna provide this study in, in
with this, with the podcast, being ableto look at the list and say, well, where
(14:19):
is the data source associated to that?
And what's my plan to start workingwith those different kind of entities
to be able to build this out?
Again, being knowledgeable about thefact that some of those data sources,
you might only get updated once a year.
Mm-hmm.
But you have a protocol in placeto, to get it updated once a year
and you're really kind of justcontinuing to build that kind of
(14:40):
governance process so that it's readilyavailable to you when you need it.
But also you know what the limitationsare to the systems that you have.
Yeah.
Do you know of any studies ondepartments and data governance?
I, I don't know if that's apractice in police departments.
I'm just thinking about back whenI was an analyst, I, I'm not sure
(15:02):
how much data governance per se.
We tried our best, but itwasn't as certainly as.
Taking it seriously asI've seen with others.
Talk about data governance.
No, it's a great it's agreat point to talk about.
There are a handful of what I wouldsay, mid or larger police departments
that are starting to develop reallygood data governance plans, including
(15:23):
a data strategy for the department aswell as a data governance approach.
And I think.
You'll start to see more ofthat within departments as well.
It is an area that really needs tocontinually build, be built out.
I just did some work with a researchinstitution with a individual police
department in this area, and one of thethings that we talked about was that
there have never been studies associatedto actual data governance practices.
(15:47):
Within law enforcement agencies.
So, to your question itreally doesn't exist today.
It's, and it's very haphazard, dependingupon kind of what the history of that
part department is as it relates to data.
So give us a quick summary thenagain maybe, go through the,
list there and let's make surethat we covered everything.
Yeah.
So in terms of overall in the study,there are specific places that are
(16:11):
associated with an increased riskof violence against law enforcement
officers and police officers in general.
As analysts, I think it's reallycritical to be focusing in on.
Data that you have to, to basicallytake what the study found, which
again are a lot of foreclosures,problem buildings, bars, schools,
liquor stores, apartment communities.
(16:32):
And being able to look at your own dataand see whether or not you have specific
locations and times that potentiallygive rise to this type of behavior.
Also being able to look at thosefacilities across your entire
jurisdiction and then kind ofproviding a list to your department.
Proactively letting 'em knowthat the possibility of having.
(16:54):
These types of batteries and assaultsto law enforcement officers at these
facilities is there and to at leastconsider a tactical and or a call
response approach to dealing withthese particular locations as well.
And again, as an analyst, reallyfocusing in on making sure you have
the data available to do this typeof analysis, and then being forward
(17:14):
thinking and being proactive toprovide it to your organization.
Again in a time when law enforcementagencies are really focused in on officer
safety, health, and wellness as well.
Alright, Jamie, appreciatethe information as always.
And for the listeners, as Jamie mentioned,we will put a link to the study in the
show notes and if you have used this dataor have something to add, please reach
(17:37):
out to us at lea podcasts@gmail.com.
Or find us on, on LinkedIn, FacebookX and give a comment there as well.
All right, Jamie, as always,thank you so much and you be safe.
Thanks Jason.
Thank you for making it tothe end of another episode of
(17:57):
Analyst Talk with Jason Elder.
You can show your support by sharingthis and other episodes found
on our website@www.podcasts.com.
If you have a topic you would like us tocover or have a suggestion for our next
guest, please send us an email at elliotpodcasts@gmail.com next time analysts.
Keep talking.
Welcome to Analyst Talk with Jason Elder.
(00:01):
It's like coffee with an analyst,or it could be whiskey with an
analyst reading a spreadsheet,linking crime events, identifying a
series, and getting the latest scoopon association news and training.
So please don't beat that analystand join us as we define the law
enforcement analysis profession.
One episode at a time.
How we doing?
Analysts?
Jason Elder here with anotherLE, a podcast Deep Dive
(00:23):
research remix with Jamie Roush.
Jamie, how we doing?
Doing great, Jason.
So before we get into our topictoday, We're mostly through the
college football season now.
Are you okay with Florida State?
'cause they started outhot and then they went not,
yeah, it's been a tough, toughseason for Florida State, but.
Know, we'll see what happensin the next couple games.
(00:44):
We still have a few more, including theSunshine Showdown against the Florida
Gators, so we'll see what happens.
Yeah, I, I do feel that it was a littlebit of a tease that Alabama game, that
first game of the season was such a tease.
'cause it, they came in so flying high.
They're like the firstthree or four games.
Oh yeah, it was definitely a teasefor all of us, I can tell you.
Still potentially bowl eligiblelooks like again, a couple more
(01:06):
games for the rest of the season.
So we're just kind of hoping toget into those, the postseason
with a, at least a Good Bowl game.
So.
All right, very good.
All right.
What are we talking about today?
So today, Jason, we're gonna throw itback to the spatial element of crime
that we've talked about again on someof the previous research remixes.
We're gonna talk about whether thespatial element of crime is correlated
(01:27):
to felonious battery of police officers.
We're gonna really answer this kindof question of does the physical
landscape play a role in batteryand assault of police officers
and law enforcement officers?
So as obviously all of us know lawenforcement officers by their nature
encounter these situations where they'retasked and faced a lot of risk and in
(01:47):
a lot of cases non-accidental injury.
Again, there's lots of reasons for that.
Aggression towards police, naturaluse of force incidents, and while
the research in the past in both ofthose areas has really focused on
offender and officer characteristicsthat give rise to non-accidental
injuries of officers, there's beenvery little research that's actually
(02:08):
focused on the physical landscape.
And are there specific spatial elementsacross the landscape essentially
that give a higher probability?
Of assault and battery ona law enforcement officer.
So in 2014, Joel Kaplan and EricPiza and others kind of explored
the environmental characteristicsof where this type and this very
(02:29):
specific type of violence occurs.
They looked specifically at kind ofareas for violence that are often more
narrow or kind of like small spaceslike housing complexes with alleyways
which can then decrease the distancebetween an offender and an officer.
They looked at abandoned structures andunlocked facilities and secure shelters,
(02:51):
places that could potentially give riseto ambushes, which end up in battery
and assault on law enforcement officers.
And then they often just looked atregular locations with just a high crowd
density, people that are in very tightquarters and very, very tight spaces.
Often places like bars and nightclubs.
And so what the research team did isthey used data from the Chicago Police
(03:12):
Department specifically related to assaultand battery with a firearm that was
directed towards law enforcement officers.
And they started focusing in on kindof these particular types of areas
and they found essentially that thereare places that are risky, risky
facilities, which we often have heardfrom problem oriented policing as well.
(03:33):
But they also looked at thingslike data on foreclosures, data on
abandoned buildings, code enforcementlocations, areas where there is a
limited amount of street lighting.
And essentially they kind of focusedin on looking at are there a series
of characteristics that give rise tothese types of assault and batteries?
Now, what's really interesting about thisis that for those of us who have done
(03:54):
this work for a long time, we know that.
Crime prevention through environmentaldesign or subhead is a very big part
of being able to prevent crime orworking towards prevention of crime.
So what the research team found inreviewing this data and looking at these
geographic characteristics is that theyfound essentially that in this order.
Foreclosures or problem buildings.
(04:15):
Again, those ones with large codeenforcement, unsecured properties,
bars, schools, gang territories,or gang affiliated locations,
apartment communities, and liquorstores pose the highest risk and
kind of the highest probability of.
Finding assault and batteriesat these particular locations.
Now, it's probably not uncommon formost of us to think about it, but the
(04:38):
idea is, is that the researchers notedthat when you take these locations,
these risky type of facilities,and you intersect characteristics
like dim lighting, poor lighting.
Alleyways, street corners, thingsof that nature, that it obviously is
a higher probability of the abilityto have an assault and battery
on a law enforcement officers.
(04:59):
They said that essentially some ofthese locations, not surprising,
the unsecured buildings, the problembuildings and the foreclosures are
often locations with no governance,no one to watch them, to protect them.
And essentially that is.
One of the conclusions that they drewthat kind of led them to say, essentially,
those are probably locations that are thehighest for these types of risk as well.
(05:22):
Now for the analysts who are listeningtoday, they also added in the temporal
component, which all of us focus in on.
When we look at space, we lookat space and time together, and
they focus in on saying thatthere are specific times in which.
Officers respond to calls for service orCAD runs at these risky locations that
also correlate to a higher probability.
(05:43):
The 2:00 AM closure of a bar,for example, is gonna be.
A compounding factor to givingrise to assault and battery
on law enforcement officers.
Hmm.
So there's a lot there.
I, I guess my first thing that I'mthinking of is, it reminds me of
routine activities theory, and that'swhere my head was going, because
(06:05):
it seems like in some of those.
Situations.
It might seem odd to say that an officerdoesn't have a capable guardian, but
in some of the theory with routineactivities, the, the lighting, the.
Spacing that deals directlywith routine activities.
It's dealing with that idea that there'sa certain situations, that there is
(06:30):
this absence of a capable guardian.
Yeah.
And essentially bringing rise to a crime.
And in this particularcase, a very violent one.
That is then directed to towardsthose law enforcement officers.
Again, for various reasons, whetherit's just natural aggression or again,
a person that has a disdain for lawenforcement or someone who is prepared to
actually ambush a law enforcement officer.
(06:51):
There's many differentscenarios in which those things.
Give rise, but to your point, absolutely.
There really isn't a guardian in thosesituations and that that's essentially
what creates this type of harm forlaw enforcement officers as well.
Yeah.
My, my second thought is someof those types of situations
that , you listed, those might notnecessarily be part of the analysts.
(07:18):
Database, right?
I mean, obviously you're gonnahave your liquor stores, right?
Or your bars, you might have that.
But some of these either condemnedbuildings or problem buildings , it
might not be described that way.
So you're just gonna get anaddress and you might not have the
particulars of that address there too.
(07:40):
Categorize it as one of those high threatlocations as described in the study.
Yeah, Jason, I think that's a reallyimportant point, and one of the reasons
why I thought this study was importantto bring to this particular podcast is
that it really is a call for analyststo start thinking about non-traditional
data sets that are spatial in nature.
In some of the previous researchremixes we've talked about
(08:02):
non-traditional data sets.
Again, for workload or other types ofthings, but this is really a call to
start thinking about your inventoryof your spatial data and do you
really have a good handle on all ofyour jurisdiction's risky facilities?
Is that data being updatedon a regular basis so that.
(08:23):
When you're looking at this kind ofdata, you have the ability to do modeling
and being able to provide insightsabout these particular locations.
To me, I think this is really important.
Although this topic is one that probablyanalysts wouldn't think about is within
the purview of their day-to-day work.
We are in the US right now reallyfocusing in on officer safety and health
(08:45):
and wellness and if we can as analysts.
Be able to use things like restrainmodeling and more spatial types of
approaches to identify these locations atspecific times that then create a higher
probability for our officers to be goingthrough an assault or battery or potential
for assault or battery situation.
(09:06):
Providing that proactively to ourorganization becomes really valuable.
And it's something that then theorganization can consume and say, Hey,
maybe we change our call protocol at thistype of facility at this time of day.
And you create some of these kind ofwhat we call alternate response plans.
(09:26):
And I think that becomes really, reallyvaluable for organizations as well.
I think one of the criticisms that peoplewould say is, is that most agencies.
A lot of officers would say, well, Iknow that these are, these are places
that I potentially can be more harmedor have a non-accidental injury.
But I think within the data we always findinsights that maybe correlate things in
a way that not everybody had, would'vethought that location at that time of day.
(09:51):
And again, that's where analystshave the ability to really kind
of put that data forward with thismindset of kind of the officer
safety, wellness and health approach.
Yeah, and this is an alsoan great opportunity to help
out the dispatchers as well.
The 9 1 1.
Dispatchers because this isobviously information that they
(10:14):
should know and be aware of
yeah, I mean, I think it caninform CAD systems, right?
You can create additional, almostevery major CAD system has the
ability to create additional flags.
This is another data source essentiallythat can help with that flagging.
It then does alert the dispatcher as well.
But I also think from a dispatchperspective, it really gives value
(10:36):
to dispatchers being able to say,at this time of day, in this type of
facility, I might have to not onlysend additional officers, but if it
breaks bad, what is our protocol gonnabe and how are we going to adjust to
send more people to these locations?
Right?
So it's kind of more of like this ideathat dispatchers can proactively be aware.
(10:57):
If something does go wrong in asituation like this is if you do have an
assault or battery on a law enforcementofficer, that this is what our protocol
is specifically gonna be for that,for these type of facilities as well.
Yeah.
It almost seems like it's almostthe two extreme situations.
It's scenarios where it's.
We talked about the lighting or justproblem buildings something where it would
(11:21):
just be maybe the officer on their own.
And then there's the other extreme whereit might be a bar or a skull where there
might be a lot of people on there andyou're dealing with more maybe uprising
type of scenario there.
So it seems like it's the both extremesthat got covered in this study.
Yeah.
What I like about that too, and again,I think this is really important
(11:44):
for the analysts listening, is that.
If you're taking this data and youare proactively looking at it and
saying is there a higher probabilitypotentially of officer assault
and battery at these locations?
You also can create a priority systemof the output of the analysis that you
create to say these are priority ones,these are the most risky facilities,
(12:06):
and these are the most risky timesfor this type of behavior activity.
But then you can also saythis is the least as well.
Again, I think it gives your organizationthe ability to develop some tactical
plans that are informed because maybefrom a staffing workload dispatch
capability, you can only really focusin on utilizing that priority one data.
(12:28):
But then when things free up or youhave the ability to look at some
of those priority twos or threes,et cetera, that the analyst has
provided now, then it gives the pathfor the organization forward, right?
Kind of.
Helps them say, Hey, if we can onlyprioritize a small group, here's the
small group we're gonna prioritizetoday, but then next year, let's
revisit this list again and thenlet's reprioritize next year as well.
(12:50):
As an analyst, you're actually creatinga product essentially that has strategic
value over a. Multiple periods oftime just by prioritizing that output.
Hmm, that's a good point.
I you talked about data setsand, expanding, the types
of data that analysts have.
I mean, this is definitely a goodexample of, of something to make sure
(13:12):
that your mapping layers have all these.
Particular types of, buildingsas, as I mentioned before, some
of them are gonna be readily.
We're gonna categorize them as such, butthere's gonna probably be some on here
that's on this list that isn't readilygoing to be designated as as such.
(13:36):
So it's definitely something that,that might be a, I I'm always trying
to give interns some, some jobs thatmight be a good thing for an intern.
It to do go through your list andmake sure that your geographic
database, your data is, is up to speed.
Yeah.
And I used to think about data in kind ofmulti different layers in terms of like
(13:56):
where the source of the data comes from.
Right?
So you have data that's within your.
Department or again, and then you've gotyour city county data, you have your state
or other governmental data, and then youhave private business data as well, right?
So looking at a list like this thatwe're gonna provide this study in, in
with this, with the podcast, being ableto look at the list and say, well, where
(14:19):
is the data source associated to that?
And what's my plan to start workingwith those different kind of entities
to be able to build this out?
Again, being knowledgeable about thefact that some of those data sources,
you might only get updated once a year.
Mm-hmm.
But you have a protocol in placeto, to get it updated once a year
and you're really kind of justcontinuing to build that kind of
(14:40):
governance process so that it's readilyavailable to you when you need it.
But also you know what the limitationsare to the systems that you have.
Yeah.
Do you know of any studies ondepartments and data governance?
I, I don't know if that's apractice in police departments.
I'm just thinking about back whenI was an analyst, I, I'm not sure
(15:02):
how much data governance per se.
We tried our best, but itwasn't as certainly as.
Taking it seriously asI've seen with others.
Talk about data governance.
No, it's a great it's agreat point to talk about.
There are a handful of what I wouldsay, mid or larger police departments
that are starting to develop reallygood data governance plans, including
(15:23):
a data strategy for the department aswell as a data governance approach.
And I think.
You'll start to see more ofthat within departments as well.
It is an area that really needs tocontinually build, be built out.
I just did some work with a researchinstitution with a individual police
department in this area, and one of thethings that we talked about was that
there have never been studies associatedto actual data governance practices.
(15:47):
Within law enforcement agencies.
So, to your question itreally doesn't exist today.
It's, and it's very haphazard, dependingupon kind of what the history of that
part department is as it relates to data.
So give us a quick summary thenagain maybe, go through the,
list there and let's make surethat we covered everything.
Yeah.
So in terms of overall in the study,there are specific places that are
(16:11):
associated with an increased riskof violence against law enforcement
officers and police officers in general.
As analysts, I think it's reallycritical to be focusing in on.
Data that you have to, to basicallytake what the study found, which
again are a lot of foreclosures,problem buildings, bars, schools,
liquor stores, apartment communities.
(16:32):
And being able to look at your own dataand see whether or not you have specific
locations and times that potentiallygive rise to this type of behavior.
Also being able to look at thosefacilities across your entire
jurisdiction and then kind ofproviding a list to your department.
Proactively letting 'em knowthat the possibility of having.
(16:54):
These types of batteries and assaultsto law enforcement officers at these
facilities is there and to at leastconsider a tactical and or a call
response approach to dealing withthese particular locations as well.
And again, as an analyst, reallyfocusing in on making sure you have
the data available to do this typeof analysis, and then being forward
(17:14):
thinking and being proactive toprovide it to your organization.
Again in a time when law enforcementagencies are really focused in on officer
safety, health, and wellness as well.
Alright, Jamie, appreciatethe information as always.
And for the listeners, as Jamie mentioned,we will put a link to the study in the
show notes and if you have used this dataor have something to add, please reach
(17:37):
out to us at lea podcasts@gmail.com.
Or find us on, on LinkedIn, FacebookX and give a comment there as well.
All right, Jamie, as always,thank you so much and you be safe.
Thanks Jason.
Thank you for making it tothe end of another episode of
(17:57):
Analyst Talk with Jason Elder.
You can show your support by sharingthis and other episodes found
on our website@www.podcasts.com.
If you have a topic you would like us tocover or have a suggestion for our next
guest, please send us an email at elliotpodcasts@gmail.com next time analysts.
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