Transcript Slide 1

Big data and real-time
information as game
changer?
Lauren Sager Weinstein
Head of Analytics
Customer Experience
Today’s presentation - agenda
1. Changing expectations
2. Open data – travel information
3. Big data
4. Key considerations
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Our purpose
‘Keep cities working and growing and make life better’
Plan ahead to meet the challenges of a
growing population
Unlock economic development and
growth
Meet the rising expectations of our
customers and users
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Customers’ Technology Expectations
• ‘Any place, any device’ access to all the tools and services customers need
• Tasks are made simpler, to save customers time
•Self-service is quick and easy
•Staff can fix customer problems easily
•A personalised service – my transport provider knows me
•Transport seamless - integrated information and ticketing
•Customers can easily find help if needed
•Information is easy to find - real-time and accurate
•Customer experience reflects customer expectations and needs
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TfL Travel information as open data
Live data and APIs include;
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Bus arrivals – stream and API
Tube movements, departures, status
Cycle hire docking station status
River boat status and arrivals
Roads status
Journey Planner API
Reference data includes
• Stations, stops and piers locations
• Timetables
• Future works on Tube, Roads
All available in our Developers’ Area of tfl.gov.uk
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Why open data – travel information
Public data
Reach
Optimal use of
transport network
Economic benefit
Innovation
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Our work in Big Data
Journeys on London Underground, typical week
450,000
400,000
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
S unday
Monday
Tues day
Wednes day
Thurs day
F riday
S aturday
Given our number of
customers, we have
big data– it becomes
‘Big Data Analytics’
when we combine it...
Inferring destination for bus trips
A customer taps an Oyster card
on the reader, which records the
location and time
Can we infer the exit point?
Stop
A
Stop
B
Bus events are recorded in the iBus system and we
can match this with our Oyster data
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Where is the next tap?
From the location of the next
tap (if there is one), we can
infer where a customer
alights
Station Y
If next trip begins at stop X, the
current segment is inferred to
end at stop A
Stop X
Stop
A
Stop
B
If next trip begins at station Y, the
current segment inferred to end at
stop B
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Using our Big Data tools
Tim e ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
LEWISHAM CENTRE
0
0
4
2
3
3
3
2
3
4
1
3
8
0
5 10 12
0
0
6
0
4
3
8
1
5
7
2
LOCKMEAD ROAD
2
0
5
4
3
6
4
2
4
5
3
8
7
6
5 18
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0
0
7
0
6
3
9
2
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8
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THE SQUIRRELS
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0
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3
6
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2
5
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3
7
7
6
5 18
8
2
0
7
0
6
3
9
3
8
8
2
ST MARGARET'S CHURCH / BRANDRAM ROAD
2
0
5
4
3
6
5
2
5
5
3
7
8
6
6 10
2
2
4
8
0
6
3
9
4
8
6
2
BLACKHEATH HOSPITAL
2
1
6
4
3
7
5
2
5
5
4
7
8
5
8 11
3
3
5
8
0
6
3
9
4
7
6
2
BLACKHEATH STATION #
2
1
6
3
4 11
7
2
6 11
8 11
8
7 10 18
9
7
8
9
0
9
5 12
6 14
4
5
ROYAL PARADE
2
2
6
3
4 12
7
1
6 11
8 12
9
8 10 19 10
7
7 12
0 12
5 14
5 14
4
3
MONTPELIER ROW
2
2
6
3
5 12
7
1
6 11
8 14 12
8 10 20 11
8
6 11
0 14
5 15
8 15
3
4
ST GERMANS PLACE
2
2
6
3
5 12
9
1
6 11
8 16 12
9 13 21 11
9 12 15
0 15
6 15
8 16
3
4
STRATHEDEN ROAD / SHOOTERS HILL ROAD
2
2
6
3
7 14 11
2 11 17 13 23 20 12 19 37 13 24 17 18
0 21
6 18
8 18
3
4
BLACKHEATH / ROYAL STANDARD
4
3 10
9 15 29 23 10 26 43 25 40 48 27 27 54 28 43 29 22 10 21
8 20 10 17 11
6
KIRKSIDE ROAD
4
6 11 11 15 33 26 11 32 43 27 43 50 34 28 54 29 43 32 23 10 24
9 22
8 17 11
6
WESTCOMBE PARK STATION #
4
7 12 11 16 33 26 12 32 43 27 45 50 37 30 54 31 43 32 24 10 24 10 21
9 18 11
7
WESTERDALE ROAD
4
7 12 11 16 32 27 11 33 43 26 45 50 38 30 54 28 43 31 23 11 23 10 21
8 17 10
5
SAINSBURY'S AT GREENWICH PENINSULA
5
7 16 16 18 30 43 18 36 43 34 46 50 40 44 56 34 43 32 22 11 27
9 24 11 18 11
5
ODEON CINEMA
5
8 15 16 19 29 46 25 38 42 36 47 50 40 43 54 40 43 31 22 11 27 10 24 11 18 11
5
MILLENNIUM VILLAGE SOUTH
5
8 15 18 19 29 47 25 39 42 37 47 50 40 43 56 40 43 31 22 11 26 11 22 11 19 11
5
MILLENNIUM VILLAGE / OVAL SQUARE
5
8 16 19 18 34 48 28 44 43 45 47 50 40 42 55 40 47 30 31 12 30 12 26 14 23 15
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NORTH GREENWICH STATION <>
8
8
2
8 15
7
8
2
5 20
3
8
5
7
5
4
6
5
3
7
9 10
6 21
4
9
4
2
BOORD STREET
8
7
2
8 14
7
8
1
6 20
3
8
5
7
5
5
6
4
3
7
9 10
6 21
4
9
4
2
BLACKWALL LANE
8
8
3
8 14
7
8
0
9 16
3
9
4
8
9
6
6
3
3
7 11
9
6 24
3 12
5
2
MORDEN WHARF ROAD
8
8
3
8 14
7
9
0
9 16
3
9
4
8
9
6
6
3
3
7 11
9
6 24
3 12
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2
BLACKWALL TUNNEL / EAST INDIA DOCK ROAD
8
6
3
7 12
7
6
0
6 13
3
9
5
8
9
7
6
3
3
7
9
8
6 23
4 11
5
2
ANDREW STREET
9
6
3
7 12
7
6
0
6 14
4 13
8 11 10
9
6
7
4
8
8
8
6 23
3 14
5
3
ST LEONARD'S WHARF
9
6
4
9 13
5 11
3
9 16
6 18 10 15 11 12
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9
6 10
9
8
7 23
4 14
8
3
COVENTRY CROSS ESTATE
9
7
4 10 13
5 12
3
9 16
6 17 11 15 11 11
6
8
6
9
9
8
7 23
4 14
9
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BROMLEY BY BOW STATION <>
5
6
4
7 12
4
9
1
7 13
4 10 15 10
9
7
5
6
4
9
9
7
8 22
4 14
6
3
GRACE STREET
5
6
4
7 12
4
9
1
7 13
4 10 15 10
9
7
6
6
4
8
9
7
8 22
4 13
5
3
BOW INTERCHANGE
5
5
2
6
9
4
7
1
7 10
2
8 11
9
8
6
6
6
4
8
8
7
7 18
5 12
4
3
MARSHGATE LANE
4
5
2
6
8
4
7
1
7 10
2
8 11
9
8
6
6
6
4
8
7
7
6 18
5 11
4
3
WARTON ROAD
4
6
9
9 15 10
9
3 13 17 12 21
9 18 20
8
3
6
4 12
9
6
8 17
6 11
7
3
STRATFORD HIGH ST STN [DLR] / CARPENTERS ROAD
4
6 10 10 16
9
7
3 13 19 14 24 12 21 23 10
3
7
4 12
9
8 10 16
6 10 10
3
STRATFORD BUS STATION <> # [DLR]
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 -1
0
0
0
0
0
0
0
0
0
We use our analysis to monitor
congestion so that we can tailor our
bus services where needed
We also use this for our bus route
groupings so we can design good
transfer points
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Our Big Data plans
Many more topics and questions to explore!
• Integrating ticketing, bus, traffic congestion, and incident data for
better performance of the bus and road networks
• Integrating social media with our customer data for deeper
understanding
• Looking at weather data to see how it affects transport use
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Big Data + Open Data = insight together
• Our strategy is to make as much data openly available as
possible
• Where data has a sensitive element (e.g. some journey data)
we aggregate to publish summary statistics and provide
some sample data that is open to all
• We also have a controlled area for researchers to access
disaggregate sensitive data
• As a result, much of our work has been informed by our
collaboration with academia
• And we are exploring some further opportunities to bring our
data and other data together.
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THANK YOU
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