Using Technology and Big Data to Provide our

Customers with a Passenger Experience

Presented by Suresh Kakarla

CEO of TollPlus LLC

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Analytics: Current Industry Context

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3

4

2

Weak Performers Strong Performers

Analytics: Current Issues

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Limited Data Sources

Mostly Manual Analysis Effort

Low Confidence Recommendations

Extremely Difficult to Predict Customer Behavior

Long Durations for Analysis and Research

Does Not Consider Variability in Research Parameters

Impossible to Determine Cluster Classifications To Determine Correlated Usage Patterns

Advanced Analytics Model

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Analyze Business Needs

•Analyze Current Processes

•Identify Key Needs

Collect And Prepare Data

•Identify Data Sources

•Validate And Clean Data

Perform Exploratory Analysis

•Data Distribution Analysis

•Eliminate Outliers

Advanced Analytics Engine

•Clustering / Classifications

•Correlations

•Predictive/Forecasting

•Recommendations

Provide Insights

•Recommendations/Best Actions

•Business Strategy Advice

Internal

External

Graphical &

Desktop tools

Domain

Expertise

Data

Visualization Data Sciences

Process Framework

Multiple Regression

Logical Regression

Neural Networks

Decision Trees

1

2

34

5

Integration Engine

Customer Mobility and

Big Data Ecosystem

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Scoop

(Relational

/ CSV)

Flume /

Kafka

(Streams)

Custom

Scripts

Data

Ingest &

Process

Map

Reduce

Engine

Spark

Engine

Subjective

Data Mart

Subjective

Data Mart

Mongo

DB

MySQL

Elastic

Hadoop

FS

HBase

Staging / Collection layerTraffic

Rate

Demographics

Customer Feedback

Billing

Interoperability

Payments

Violations

Tag

Cost

Twitter

Facebook

DMV

DOT

Address Verification

Email verification

Domain Model Data

Analysis Specific Data

High Quality Data for Processing

Summarized/Aggregated/

Composed Data

Meta Data for Processing and

Tools

Indexed and Sharded Data

Reference Data

Event Data

Tool for ingesting

relational & character

separated files data

Tool for processing

streaming and event

information

Python, shell scripts or

programs to cleanse

incoming data and implement

security, file transfer, etc

Integration Engine

Customer Mobility and

Big Data Ecosystem

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Scoop

(Relational

/ CSV)

Flume /

Kafka

(Streams)

Custom

Scripts

Data

Ingest &

Process

Map

Reduce

Engine

Spark

Engine

Subjective

Data Mart

Subjective

Data Mart

Mongo

DB

MySQL

Elastic

Hadoop

FS

HBase

Staging / Collection layerTraffic

Rate

Demographics

Customer Feedback

Billing

Interoperability

Payments

Violations

Tag

Cost

Twitter

Facebook

DMV

DOT

Address Verification

Email verification

Domain Model Data

Analysis Specific Data

High Quality Data for Processing

Summarized/Aggregated/

Composed Data

Meta Data for Processing and

Tools

Indexed and Sharded Data

Reference Data

Event Data

Document database for

staging & storing summary

information

Index database, for best search response and

reference data

Store all data, including unformatted data,

warehouse @ lowest cost

Provide definition to Hadoop data, enable queries with SQL like

syntax

Integration Engine

Customer Mobility and

Big Data Ecosystem

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Scoop

(Relational

/ CSV)

Flume /

Kafka

(Streams)

Custom

Scripts

Data

Ingest &

Process

Map

Reduce

Engine

Spark

Engine

Subjective

Data Mart

Subjective

Data Mart

Mongo

DB

MySQL

Elastic

Hadoop

FS

HBase

Staging / Collection layerTraffic

Rate

Demographics

Customer Feedback

Billing

Interoperability

Payments

Violations

Tag

Cost

Twitter

Facebook

DMV

DOT

Address Verification

Email verification

Domain Model Data

Analysis Specific Data

High Quality Data for Processing

Summarized/Aggregated/

Composed Data

Meta Data for Processing and

Tools

Indexed and Sharded Data

Reference Data

Event Data

Lowest latency, in memory engine for

transformations & processing

The datamarts are created to store summary & final

information on i.e. customer notifications to

be sent today, relevant history, etc

Implement map reduce algo to find

answers

Statistical Intelligence by Toll Agency

Customer Mobility and

Big Data Ecosystem (Cont’d..)

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Mongo

DB

MySQL

Elastic

Hadoop

FS

HBase

Map Reduce

Engine

Spark

Engine

Subjective

Data Mart

Subjective

Data Mart

R

Analysis

Visualizations

Outcomes

Statistical Analysis

Domain Model Data

Analysis Specific Data

High Quality Data for

Processing

Summarized/Aggregated

/Composed Data

Meta Data for Processing

and Tools

Indexed and Sharded

Data

Reference Data

Event Data

Revenue Projection Intelligence

Pricing Efficiency

Customer Value Add Services

Customer Mobility Information

Services for Retail Sector

Vehicle Movement Intelligence

Services for Govt Sector

Vehicle Pattern Notification

Services for Logistics Sector

Kibana, X-pack and related tools

This is a bevy of statistical model tools that would do

predications with their occurance probability,

comparirion anlysis, etc

This is the tool to enable statistical analysis

ecosytem

Revenue Projection

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Financial Prediction

Models

Statistical Analysis

TechniquesProbability

• Revenue Projections

• What if analysis

• Exceptions alert

• Comparative analysisBenefits for Toll Agency• Forecast revenue based on factors that are non-

financial and qualitative

• Simulate the impact of adding a lane on revenue

• Conduct what if analysis and comparisons

• Ability to measure the accuracy of the metrics

calculated

1Revenue Details (Historical)

2Cost Details (Historical)

3Other Financial Data

4Traffic Data

5DMV Information

6Other Market Data

This is a multi variable analysis, in which financial bond performance data will be modified based on non financial items in

isolation or in conjunction. They will define actions for the toll agency and help in making decisions to achieve any dynamic goals. This also can be used to measure the performance of actions taken

and their effectiveness within a time slice. This can identify/indicate if any factors that have not been considered or

misinterpreted in the causal analysis that is done in the past

Customer Value Added Services

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Decision Tree

processing

Renewal

Notification to

Customer

By Toll Agency

Auto Renewal by

Agency

Benefits for Customer• Improved Customer Experience

• Reduction in Travel Times

• Auto renewal/replenishment

Benefits for Toll Agency• Revenue & Traffic Forecasting

• Additional Revenues

• Reduced Congestion

• Reduction in Operational Costs

Customer Service

Request for

Auto Renewal through

Toll Agency

DMV

1 Demographics

2 Billing

3 Violations

4 Tag

5 DMV/DOT

6 USPS

7 Transit

8 Address Verification

9 Email Verification

Customer lifestyle improvements

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Notification to

Customer

By Toll Agency

Benefits for Customer• Notification 4 to 6 Hours in-advance, for traffic pattern

change, accidents, etc.

• Personalized travel time based information

• Better Information to manage life better

Benefits for Toll Agency• Better revenue from uniform traffic patterns

• Better congestion management

• Better customer service

1 Demographics

2 Billing

3 Violations

4 Tag

5 Market data

6 Public Event information

7 Transit

8 Geo positioning / maps data

Predictive Analysis

Event processing

Exception determination

Customer Mobility Information services

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Benefits for Retail Company• Effective Campaign management and

Promotions for road customers

• Use Customized & Intelligent Billboards

• Better Anticipate Customer Volumes

Associative Analyzed

Cluster Analyzed

Retail Company

Benefits for the Toll Agency• Additional Revenue

1 Traffic

2 Demographics

3 Rate

4 Customer Feedback

5 Billing

6 Interoperability

7 Payments

8 Violations

9 Tag

10 Maps/Geo Positioning

Knowledge of customer segmentation with respect to time can generate complex campaigns, which will help retail industry and the

customer both. E.g. Big events like a particular rock concert is the only place where a customer category adverts occur, here they will

know which day and which time and where a segment of customers are by using the agency data. The customer is completely

deidentified and personal information is scrubbed in compliance with govt regulations.

Vehicle Pattern Notification Services

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Processed & Segmented Data/

Streams

Logistics

Benefit for the Logistics Company• Optimized Road Vehicles

Operational Efficiency

• Optimized Cost Management

• Determination of Operation Actions

• Discovery of Opportunities

Benefit for the Toll Agency• Additional Revenue

1 Traffic

2 Demographics

3 Rate

4 Customer Feedback

5 Billing

6 Interoperability

7 Payments

8 Violations

9 Tag

10 Maps/Geo Positioning

Vehicle Movement

Intelligence Services

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Notification

engine

Alert

Prediction Engine

Benefits for Customer• Alerted on Traffic congestions

• Alert on Rate changes

• Alert on Emergency Conditions

• Improved Customer Experience

Benefits for Toll agency• Better Traffic Management

• Increased Revenue

• Increased Customer Subscription

Benefits for Govt Sector• Alerts to Fire Department on

Hazardous Vehicles

• Alerts Police Department for

Criminal Tracking

• Alert on Emergency Conditions

1 Rate

2 Traffic

3 DMV/DOT

4 Weather Data

5 Events Information

6 Market Analysis Data

7 Other Market Data

8 Analysis Summary Data at Toll Agency

Bigdata Program

Roadmap for a Toll Agency

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Budgeting and Cost Benefit Analysis

Business Case Specification

Corporate Data Dictionary

Specification

Organization User Identification

Identification for Operational

Procedures for Analytics

Configure Business Data

Analytics Specifications

Configure Clustered Software

System

Provision Hardware and

Software for the Analytics needs

Identification and Integration of

Organizational Data Across Various

Sources for Analytics

Define and Implement

Operational Processes for

Hardware Usage

Define and Implement

Monitoring and Error Resolution

Tools and Processes

Quick Refinement of Turn-around

Cycle Management Processes

Define Change Management,

Operational Practices

Strategic Implementation Operational

Bigdata Challenges

for a Toll Agency

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Strategic

Implementation

Operational

Bigdata Cost Benefit Analysis: A Forecasting Challenge

Alignment with Organization Strategy Needs Significant Thinking

Stakeholders Identification and Education will Require Good Planning and Coordination

Pooling Data Sources Require Significant Effort and Turn Around

Usage of Complex Statistical Methods and Tools will Need Higher Expertise

Legacy Systems: Integration and Feasibility Issues

Usage of Cutting Edge Technology Tools will Lead to Feasibility and Stability Issues

Monitoring Challenges will increase the Operational Burden

Error Recovery will involve significant Effort

Exponential Increase in Analysis Needs over Short Periods of Time will Impact Overall Timelines

Due to Significant Insight into Business from a Basket of New Perspectives and Questions will be Difficult to Manage