What is the story in your data? Using the example of the Metrolinx Regional Transportation Plan, this presentation shows how data visualization and storytelling can be used to transform data into knowledge and action. The Metrolinx business case framework is introduced as a consistent and robust evidence-based framework to evaluate projects. • Examples of Data visualization and storytelling with transportation models • Mapping project benefits and impacts to explain the value proposition • Mining new data sources, including PRESTO business intelligence, to better understand and illustrate customer behaviour

1. OCTOBER 23, 2018
SMART TRANSPORTATION FOR INTELLIGENT CITIES
Director, Research & Planning Analytics, Metrolinx
Joshua Engel-Yan
Telling the Story:
Transforming Data & Evidence into a Compelling Narrative to
Support Decision Making at Metrolinx

2. 2
Q: Who is the Most Famous
Transportation Planner of All Time?

3. 33INSERT FOOTER

4. EXAMPLE: COMMUTER FLOWS BETWEEN CITIES
4
Can you find the pattern in this data?
DATA SOURCE: STATISTICS CANADA

5. TRANSFORMING DATA INTO MAPS
5DATA SOURCE: STATISTICS CANADA, PRODUCED WITH KEPLER.GL

6. TRANSFORMING DATA INTO ART?
6DATA SOURCE: STATISTICS CANADA, PRODUCED WITH CIRCOS

7. TRANSFORMING DATA INTO VIDEOS
7

8. TRANSFORMING DATA INTO KNOWLEDGE
8

9. WHAT MAKES A GOOD STORY?
9
• Something to blow up!
• Conflict, tension, two opposing
forces
• Honesty and grace, authenticity
• Impact to entertain and inspire
• Vulnerability, being open to
experience
• Emotion, human experience
• The audience is part of the story
• Seed an idea, start with an image
IMAGE SOURCE: HTTPS://WWW.PM360ONLINE.COM/EMOTIONAL-VERSUS-LOGICAL-APPEAL-WHICH-WORKS-BEST-FOR-MARKETERS/

10. 10
Hi,
I’m Josh from Metrolinx.
Today I would like to tell you a story…

11. 11SMART TRANSPORTATION FOR INTELLIGENT CITIES
PROLOGUE
Introduction to Research
& Planning Analytics

12. INTRODUCTION TO METROLINX
12
• We plan and deliver transportation
network in the Greater Toronto &
Hamilton Area
• Operate GO Transit, Presto & UP
Express
• Plan complete transport system
including TDM, New Mobility, Cycling
Network etc.
• Measure impacts of decisions using
Business cases
SMART TRANSPORTATION FOR INTELLIGENT CITIES

13. RESEARCH & PLANNING ANALYTICS
Purpose:
• To strengthen Metrolinx’s culture and capacity for evidence-based transportation
planning and investment decision-making that delivers benefits to the region.
13SMART TRANSPORTATION FOR INTELLIGENT CITIES

14. WHO WE ARE & WHAT WE DO
14SMART TRANSPORTATION FOR INTELLIGENT CITIES

15. WORLD PREMIERE

16. 1616
Start with the question…
Data is not the goal.
As a ______ (job title)
I need ____ (data analytics solution)
So I can____ (solve a problem)

17. WHAT IS A STORY? THE HERO’S JOURNEY
17SMART TRANSPORTATION FOR INTELLIGENT CITIES
START
CALL TO
ACTION
OVERCOME
OBSTACLES
MIDPOINT
CLIMAX
Establish
Routine
Everything
Changes
Tension
Rises
Tension
Rises
Everything
Changes
Dénoument
Frodo
Image: http://vsbattles.wikia.com/wiki/Frodo_Baggins

18. THE STORY ARC – TRANSPORTATION PLANNING
18SMART TRANSPORTATION FOR INTELLIGENT CITIES 18
START
THE QUEST
FOR THE RTP
A VISION OF
THE FUTURE
THE FINAL BATTLE:
IMPLEMENTATION
Congestion is intolerable &
Population is growing
Call to Action
Data Scientist
Image: https://www.lifespanfitness.com/
Visualization
Analytics
Exploration

19. 19
TODAY’S STORY
Prologue Introduction to Research & Planning Analytics
Act 1 The Quest for an RTP
Discovering Mobility Patterns & Trends
Act 2 A Vision of The Future
Measuring the Benefits of the 2041 RTP
Act 3 The Final Battle: Implementation
Business Cases & Making it Happen

20. 20
Hi,
I’m Josh from Metrolinx.
Today I would like to tell you a story…

21. 21
About how we used
data, analytics & story telling
to help create the 2041 Regional Transportation Plan

22. 22
How do create a transportation system that
is safe, convenient, reliable and sustainable for
a region that is rapidly growing & changing?

23. 23SMART TRANSPORTATION FOR INTELLIGENT CITIES
It all began, a short time ago,
In Union Station not so far away…

25. 2525SMART TRANSPORTATION FOR INTELLIGENT CITIES
ACT ONE:
The Quest for the 2041 Regional
Transportation Plan
Discovering Mobility Patterns & Trends

26. THE REGION’S TRANSPORTATION CHALLENGES
26
110,000 new residents every year
1 in every 4 trips crosses a regional boundary
79% of trips made by car
3.46 million cars owned in the GTHA

27. REGIONAL DEMOGRAPHIC CHANGES
27
$
$$$
Populatio
n
Employment Seniors Diversity Unaffordabilit
y
SMART TRANSPORTATION FOR INTELLIGENT CITIES

28. THE REGION IS GROWING
28
• The regional
study area is
defined
geographically
as the GTHA
and temporally
as 2041
SMART TRANSPORTATION FOR INTELLIGENT CITIES

29. THE REGION IS GROWING
29
• We can break
Growth Plan data
down into cities to
illustrate that rate of
growth is much
higher outside
Toronto
SMART TRANSPORTATION FOR INTELLIGENT CITIES

30. THERE IS RAPID GROWTH IN DOWNTOWN AND THE 905
30
• Strong residential growth
in 905 centres and outer
edge of build up areas
• Employment growth in
Toronto has significantly
outpaced Growth Plan
projections, projected to
meet target by 2025
• GO Expansion provides
faster travel between
suburbs and Downtown
SMART TRANSPORTATION FOR INTELLIGENT CITIES

31. A DIVERSE COMMUNITY WITH MANY UNIQUE NEEDS
31
• This map shows Census
data on the Top Five
Mother Tongue
languages in the Region
• Engagement requires
understanding different
ethnicities and unique
needs
SMART TRANSPORTATION FOR INTELLIGENT CITIES

32. INCOME INEQUALITY IS INCREASING
32
• This map shows Census
data on the fraction of
people with low income
by area
• Transit investments can
reduce the cost of living
and increase access to
employment
opportunities
SMART TRANSPORTATION FOR INTELLIGENT CITIES

33. THE POPULATION IS GETTING OLDER
33
• This map shows the fraction of people who are over age 65
• As the population ages, aging in place will require new mobility options including transit,
autonomous vehicles and mixed use communities
SMART TRANSPORTATION FOR INTELLIGENT CITIES

34. TRIPS ARE COMPLICATED
35
• This map shows
Transportation
Tomorrow Data
• As the population ages,
aging in place will
require new mobility
options including transit,
autonomous vehicles
and mixed use
communities
SMART TRANSPORTATION FOR INTELLIGENT CITIES

35. MOBILE PHONE DATA FROM SIDEWALK LABS & STREETLIGHT
36
• Replica is a new
planning tool from
Sidewalk Labs, provides
travel patters from
mobile phone data
• Could be used to
understand where
transit customers travel
and enhance existing
survey data
SOURCE: HTTPS://REPLICA.SIDEWALKLABS.COM/

36. SEGMENTATION OF CUSTOMERS BASED ON DATA FROM REPLICA
37
• Data from Replica can
also be used to isolate
trips by purpose, age,
start time and
household income
• These criteria can be
used as filters to
isolate specific patters
such as weekday vs
weekend trips
NOTE: REPLICA DATA ARE FOR ILLUSTRATION ONLY

37. BETTER PLANNING WITH ANONYMIZED PRESTO TTC-GO TRANSFER LOCATIONS
38
• Locations of population
and employment have
significant impacts on
travel patterns

38. CUSTOMER SEGMENTATION: REGIONAL TRAVELLER PERSONAS
39SMART TRANSPORTATION FOR INTELLIGENT CITIES
More likely to:

39. SUMMARY OF REGIONAL CHALLENGES
40
1. Align transportation and land use planning
2. Focus on moving people, not just vehicles
3. Improve the traveller experience
4. Respond to emerging future mobility options
5. Integrate fares and services across the region
6. Coordinate decision-making
7. Provide sustainable and long-term funding
SMART TRANSPORTATION FOR INTELLIGENT CITIES

40. 4141SMART TRANSPORTATION FOR INTELLIGENT CITIES
ACT TWO:
A Vision of the Future
Measuring the Benefits of the 2041 RTP

41. 42
THE PLAN & FIVE CORE STRATEGIES
Strategy 1:
Complete
Delivery of
Current
Regional
Transit
Projects
Strategy 2:
Connect more
of the Region
with Frequent
Rapid Transit
Strategy 3:
Optimize the
Transportation
System
Strategy 4:
Integrate
Land Use and
Transportation
Strategy 5:
Prepare for an
Uncertain
Future
38 Priority Actions to Support the 5 Strategies*

42. FREQUENT RAPID TRANSIT NETWORK
43

43. 44
THE FRTN – A MULTI-LAYERED RAPID TRANSIT NETWORK
• Integrated network
• Fast, reliable service
• Frequent (every10-15 minutes all-day)
• Customer focus

44. 2041 RTP KPI DASHBOARD
45
Key Performance Measures:
• Length of Infrastructure
• Transit Travel Time
• Total Trips & Mode Share
• People in Walking Distance
to Transit
• Congested Travel (VKT)
• GHGs per capita from auto
driver trips

45. 46
EXPANDED TRANSIT, CYCLING AND HOV INFRASTRUCTURE

46. 47
SHORTER TRAVEL TIME

49. INCREASE IN TRANSIT TRIPS
50

50. 51

51. 52
GREATER ACCESS TO FREQUENT RAPID TRANSIT – INCREASING EQUITY

52. BENEFITS OF THE 2041 RTP
53

53. DATA STRATEGY & 2041 RTP
54
• Use big data to optimize infrastructure and improve services
• Action 5.6: Develop a regional transportation big data strategy
• Create a regional transportation big data portal, providing consistent and transparent
data collection, management and reporting.
• Establish regional standards for transportation data sourcing, formatting, privacy,
security, ownership and reporting.
• Identify and acquire new transportation data on all modes of transportation for
planning and operations (e.g., crowd-sourced traffic data).
• Advance coordination and standardization of transportation forecasting, modelling
and business case methodologies to support decision-making and evaluation.
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54. 5555INSERT FOOTER
ACT THREE
The Final Battle: Implementation
Business Cases & Making It Happen

55. 56
THE FRTN – A MULTI-LAYERED RAPID TRANSIT NETWORK
• Integrated network
• Fast, reliable service
• Frequent (every10-15 minutes all-day)
• Customer focus
Developing this diverse network in a cost effective way requires a robust
methodology to maximize value for money through ridership growth and
customer benefits  business cases

56. BUSINESS CASES AT METROLINX
57
• Business Cases ensure investments are
consistent with our goals and strategic
objectives
• Provide the appropriate level of evidence for
decisions throughout the project’s lifecycle
• Create clear accountability and defined roles and
responsibilities for decisions
• Create a feedback loop from project initiation to
post in-service evaluation to support continuous
improvement

57. WORLD PREMIERE

58. 59INSERT FOOTER

59. COMPONENTS OF A METROLINX BUSINESS CASE
FINANCIAL
CASE
STRATEGIC
CASE
ECONOMIC
CASE
DELIVERABILITY &
OPERATIONS CASE
• Determines the strategic
value of addressing a
problem
• Options are evaluated against
strategic objectives
• Establishes ‘why’ a project
should be pursued
• Assesses economic costs
and benefits to individuals
and society
• Establishes ‘what the benefit
to society’ is in economic
terms
• Assesses affordability and
financial value for money
• Focuses on capital and
resource requirements for the
corporation
• Establishes ‘how much the
project will cost’ in financial
terms
• Provides evidence on
engineering viability
• May consider procurement
strategies, and deliverability
and operating risks
• Establishes ‘what is required
to deliver and operate’ the
project
60

60. EVIDENCE IS REFINED THROUGH THE PROJECT LIFECYCLE
61

61. 62
EPILOGUE
What’s Next?

62. PARTING THOUGHTS
63
• There is always a story in the data/analysis.
• What does it mean?
• What’s the story?
• How can I tell that story in a compelling way to inspire action?
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63. 64

64. Research & Planning Analytics, Planning & Development, Metrolinx
Joshua.Engel-Yan@Metrolinx.com
Thank You