The document discusses the implementation of intelligent insight-driven policing, highlighting the need for unified incident reporting and understanding community dynamics for operational effectiveness. It emphasizes the integration of data from various sources to enhance situational awareness and officer support, while addressing challenges in officer analytics and accountability. The report suggests a move towards advanced data management and analytics for more proactive policing strategies.

1. 1
Intelligent Insight
Driven Policing

2. 2
Today’s Speakers
S I M O N TAY L O R
S V P W O R L D W I D E C H A N N E L S &
A L L I A N C E S
M I C H A E L C I Z M A R
F O U N D E R & M A N A G I N G
P A R T N E R
I A N W I L L I A M S
M A N A G E R O F A N A L Y T I C S &
I N N O V A T I O N

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Agenda
T H E N E E D F O R I N S I G H T S
1 . U N I F I E D I N C I D E N T R E P O R T I N G – A C T I O N A B L E I N S I G H T S
2 . U N D E R S TA N D I N G T H E C O M M U N I T Y – P R O A C T I V E AWA R E N E S S
3 . S U P P O R T I N G T H E O F F I C E R – I N S I G H T S F O R W E L L N E S S
Q & A

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68%
Of LEAs have or are
planning to implement
unified information
platforms
Research on the Impact of Technology on Policing Strategy in 21st Century – DOJ - 2017

5. 5
I N F O R M AT I O N
M O D E L
Any format, any
platform, any source
Officer
Generated
Policing
Systems
Application
Generated
Index Search Intent BuildApp
RULE
ENTITY
ML
NLP
BOOST
SIGNAL
F U S I O N P L AT F O R M
FUSION
POI 360
FUSION
Crime Search
IntelligentPolicing
FUSION
Community
Insight
P O L I C I N G E F F I C I E N C Y S O L U T I O N S

6. 6
Unified Incident
Reporting
• Legacy Data Insight
• Unified KM
• NIBRS Compliance
POI 360
• Unified View
• Relationships
• Indicators & Intervention
Social & Community
Support
• Social Data Integration
• Proactive Awareness
• Operational Effectiveness
Unified Incident
Reporting
• Legacy Data Insight
• Unified KM
• NIBRS Compliance
POI 360
• Unified View
• Relationships
• Indicators & Intervention
Social & Community
Support
• Social Data Integration
• Proactive Awareness
• Operational Effectiveness
Operational Insight

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M A P P I NG THE PATH
O P E R AT I O N A L I N S I G H T S
I S A P R O C E S S
Organizational Maturity
ProcessMaturity
0
No Awareness
Multiple Silos of
Information
1
Unified
Platform
Unified Index
Platform
2
Insights in
Workflow
Search & Insight
in Officer
Workflow
3
Situational
Awareness
Pushing Insights
to Officer in field
4
Knowledge
Assist
Investigative
Assistance
through ML

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Integrated
Incident
Reporting
N I B R S 2 0 2 1

9. 99
JANUARY 2021
COMPLIANCE
the U C R (U ni fi ed
C ri me R eporti ng)
P rogram i s reti ri ng
the S R S (S ummary
R eporti ng S ystem –
Mo n th l y ) a n d w i l l
transi ti on to a
N IB R S -o n l y d a ta
col l ecti on by
January 1, 2021
National Incident-Based Reporting System
(NIBRS) is an incident-based reporting
system used by law enforcement agencies in
the United States for collecting and reporting
data on crimes. Local, state and federal
agencies generate NIBRS data from their
records management systems.

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Connecting the Policing to Insights
Routine, Predictable, Uni-channel, Static Database,
Defined Process, Functional Knowledge & Databases
BEFORE
Multisource, Multi DB, Multiformat, Internal /
External, Interrelated, Distributed
NOW

11. Data Scientist Driven Activity Operational Analytics
Meet the “Last Mile Problem”
RawData
Velocity
Variety
Veracity
Volume
Value
DataCollection
ETL, Capture,
Archive,
Move &
Manage
DataLake
Store to
HDFS, Azure
or AWS,
Break down
for processing
LakesideUnderstanding
Select,
Describe,
Explore,
Verify Quality,
Parse, Clean,
Join &
Structure
DataRefinery
Model,
Aggregate &
Transform
Multi-
Structured
Data (JSON)
Transactions&Interactions
Retain
runtime &
historical
models for
ongoing
refinement
ApplicationConstruction
Contextual
Business Use
Cases
Cubes for
Navigation &
Mining
Intelligence&Analysis
User Specific
Visualization,
Presentation,
Dashboards &
Reporting
BigDataManagement
&Analytics
❶ ❷ ❸ ❹ ❺ ❻ ❼ ❽
Problems with Getting to Policing Data

12. Data Scientist Driven The Last Mile Problem
Reduced Time to Value
Quantifiable & Faster ROI
ManagedData
Human
Process
Application
IndexIngestionPipelines
Ingest, Verify,
Index, Entity,
Cluster
ML Rules &
Algorithms
Ontology
Enrichment
BehavioralEnrichment
Insight,
Relevancy
Ranking,
Signals
Processing
Real-time
Learning
ApplicationVisualization
Dynamic
Prototype,
Build &
Visualization
Interactive
Dashboarding
Search,Discovery&
OperationalAI
RawData
Velocity
Variety
Veracity
Volume
Value
DataCollection
ETL, Capture,
Archive,
Move &
Manage
DataLake
Store to
HDFS, Azure
or AWS,
Break down
for processing
LakesideUnderstanding
Select,
Describe,
Explore,
Verify Quality,
Parse, Clean,
Join &
Structure
DataRefinery
Model,
Aggregate &
Transform
Multi-
Structured
Data (JSON)
Transactions&Interactions
Retain
runtime &
historical
models for
ongoing
refinement
ApplicationConstruction
Contextual
Business Use
Cases
Cubes for
Navigation &
Mining
Intelligence&Analysis
User Specific
Visualization,
Presentation,
Dashboards &
Reporting
BigDataManagement
&Analytics
❶ ❷ ❸ ❹ ❺ ❻ ❼ ❽
❶ ❷ ❸ ❹
Direct Alignment with Business Needs
Moving towards an Insight Driven View of Policing Data

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Operational Insights
T O R O N T O P O L I C E S E RV I C E
Looking Back
Insights Today
Path Forward
Toronto Police Service
Experiences with
Operational Insights

14. Integrating RMS Data with Legacy
M U LT I P L E L E G A C Y S Y S T E M S
C U R R E N T R M S
I N V E S T I G AT I O N F I L E S H A R E S

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SEARCH
FILTER
VISUALIZATION
NAVIGATIONINSIGHT
RELEVANCY STATISTICS RANKING
CORRELATION
ACTIVITY
CONTENT
INDEX
NATURAL
LANGUAGE
BOOSTED
RESULTS
MACHINE
LEARNING
QUERY RULE
MATCHING
USER
SIGNALS
FACET, TOPIC
& CLUSTER
D ATA
Files
Legacy
RMS
S O L U T I O N
Operational
Insights
NATURAL
LANGUAGE
MACHINE
LEARNING
QUERY RULE
MATCHING
USER
SIGNALS
FACET, TOPIC
& CLUSTER
Moving from Data to Insight

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Understanding
the Community

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Integrating Social
v I N F O R M T H E
C O M M U N I T Y
v G A I N P U B L I C
A S S I S TA N C E
v T R A N S PA R E N C Y F O R
I M P R O V E D T R U S T
v I D E N T I F Y M I S S I N G
P E R S O N S
v P R O A C T I C E
I N T E L L I G E N C E
G AT H E R I N G
v C R E AT E S O C I A L
T O P I C S & F O L L O W I N G
96.4% of law enforcement agencies use social media in one capacity or another

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A N E X A M P L E O F U N I F I E D O F F E N D E R P E R S P E C T I V E
“Insight Driven Policing Portal”

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Supporting
Officers
D ATA I N S I G H T S I M P R O V E O P E R AT I O N A L
W E L L N E S S

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30%
By 2023, 30% of law
enforcement & PS will leverage
[insight] systems for personnel +
organizational effectiveness
Implement an Early Intervention System to Improve
Accountability and Wellness in Law Enforcement, Gartner, 4 Sept 2020

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Key Challenges
¥ Data Related to Officer Activities is Stored in Decentralized
Data Sources
¥ Officer Related Analytics are Focused on Incident rather
than the personnel involved preventing insight
¥ Decisions related to officer wellness and accountability
have limited datasets and lagging indicators
¥ Trust at all levels between politicians, the public officers
and leaderships is needed to improve wellness and officer
training
Implement an Early Intervention System to Improve
Accountability and Wellness in Law Enforcement, Gartner, 4 Sept 2020

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Being an Officer is Challenging
Implement an Early Intervention System to Improve
Accountability and Wellness in Law Enforcement, Gartner, 4 Sept 2020
Officer
Support
é Employee
Retention
Professional
Development
Accountability
ê Healthcare
Cost
Personnel
Well-Being

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ü I M P R O V E S V I S I B I L I T Y &
C O N N E C T I V I T Y A C R O S S D ATA S O U R C E S
ü B R I N G E N H A N C E D I N S I G H T S T O
I N V E S T I G AT I O N S
ü I M P R O V E S A W A R E N E S S
Key Takeaways
Intelligent Policing
Toronto Police Service

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Questions &
Answers