There is still more room for improvement, and transport operators are looking to real-time data analytics to drive greater efficiency and resilience in their operations.

1. Leading in real time
An investigation of the impact of real-time business on strategy and management.
1 Cisco Technology Radar / More information at https://techradar.cisco.com
Transport providers arrive early to
the challenges of automation
5. TRANSPORTATION
In 2011 New York’s Department of Transport
deployed wireless sensors across Midtown
Manhattan to measure city-centre traffic speeds, and
thereby congestion. Data were fed in real time to a
control centre, where algorithms remotely adjusted
traffic signalling, automatically smoothing jams and
easing flow. The pilot was heralded as revolutionary
by the then mayor, Michael Bloomberg. “We are now
using the most sophisticated system of its kind,”
he said, “to clear up Midtown jams at the touch of
a button.” The system has since been rolled out
citywide.
In truth, the use of real-time information and
automated systems in urban transport has a long
history. “We’ve had real-time systems for a long time,”
says Shashi Verma, director of customer experience at
Transport for London (TfL), the local government body
responsible for transport in the capital.
London’s computerised traffic signalling system
SCOOT (Split Cycle Offset Optimisation Technique),
which optimises traffic-light signals based on traffic
flow, has been operating for decades. The first
driverless trains came to the city in the late 1960s.
It is unsurprising, then, that companies in the transport
sector are more advanced users of real-time data than
most. In a cross-industry survey conducted by The
Economist Intelligence Unit (EIU), 40% of executives
from the sector say their organisations have
successfully incorporated real-time information into up
to half of their business practices. This is nearly twice
the cross-industry average of 22%.
The transport sector has been an early adopter of real-
time information and is wrestling with the challenges of
incorporating automation sooner than most
Written by The Economist Intelligence Unit

2. 0% 5% 10% 15% 20% 25% 30% 35% 40% 45%
% of transporation respondents
Justifying the investment required
Collecting relevant real-time information
Incorporating real-time information into existing business
processes
Designing new business processes around real-time
information
Having the skills to analyse and interpret real-time information
Incorporating the analysis of real-time information in strategic
decision-making
Choosing which decisions based on real-time information
should be automated and which should be taken by employees
Responding rapidly to real-time information
30%
30%
40%
28%
32%
44%
48%
24%
Which of the following are the biggest challenges your organisation faces in
using real-time information?
% of transporation respondents
2 Cisco Technology Radar / More information at https://techradar.cisco.com
According to three-quarters of transport executives
surveyed, real-time data already play a major role in
both operations management (76%), where real-time
information can help optimise the delivery routes,
for example—and customer service (76%). Examples
of using real-time data to improve the customer
experience include providing up-to-the-minute
information about a vehicle’s location, to allow
passengers to plan their journeys or to let delivery
recipients know when a parcel can be expected to
arrive.
There is still more room for
improvement, and transport operators
are looking to real-time data analytics
to drive greater efficiency and
resilience in their operations.
For example, monitoring the location of trains on a
network in real time and adjusting their speed can
allow operators to shorten the distance between
vehicles—the headway—on their networks. “The
average headway can be reduced from around
three minutes to 80 seconds with no risk to safety,”
says Andreas Mehlhorn, head of Siemens Mobility
Consulting. “The line can handle 50% more traffic
and cut its energy consumption by up to 30%.”
These achievements require automation: no human
operator could react to real-time changes in the
position of coaches fast enough to keep them at a
safe distance.
Here again, transport companies
are ahead of the pack: 78% of those
surveyed by The EIU say they have
automated business processes in
order to respond instantly to real-
time information, compared with 50%
across all industries.
However, their advanced use of automation presents
them with advanced challenges. Choosing which
decisions based on real-time information should be
automated and which should be taken by employees
is identified as a challenge by 48% of transport
executive surveyed, their most commonly cited
challenge (see chart).
For TfL, one important factor influencing this decision
is the complexity and significance of the decision in
question. “If that decision is reasonably simple, then
you can leave the computer to get on with it. If the
decisions get complicated, then human intervention
is always the right thing to do.”

3. This reflects in part the fact that the sheer volume
and variety of the data available to transport
operators is almost unique. Anything—from personal
and vehicle location data, to ticketing data and
scheduling, to weather and social media sentiment
data—can be used somehow. Data are available
from fixed and mobile sensors, but also from
crowdsourcing. Google, for instance, provides live
traffic information based on information gathered
from Android phones. All of this could well lead to
analysis paralysis.
TfL’s Mr Verma warns against collecting data
for data’s sake: instead, transport organisations
should start with the problem before looking to see
whether real-time data could help. “It has to be for a
purpose,” he says.
For example, TfL knows that every time it rains
in London, demand on the tube and bus network
goes up by about 4%. But what do you do with that
information? “You can’t run more trains and busses
every time it rains.”
That said, Mr Verma sees real-time data playing an
even more crucial role in the future, by allowing TfL
to predict service issues before they arise. “The real
holy grail is predictive,” says Verma. “What you want
to know from the real-time data is whether you’re
going to confront a problem in five or ten minutes’
time. If you can act in advance of that problem
occurring, then maybe the problem won’t occur at
all.”
London’s Victoria Underground Station is one of the
city’s most congested, and managing the flow of
passengers at peak times is extremely demanding.
If two trains arrive at the same time, causing 2,000
to converge onto the Underground line, the station
will be overwhelmed, says Mr Verma. But closing the
station is disruptive.
The ability to predict ten minutes in advance whether
multiple trains will arrive simultaneously, and how
full they will be, would allow operators to start taking
advance action further ahead. “Being able to stop
stations from closing would be a fantastic thing to
do.”
“Using data to do things of that kind is an
inexpensive way of squeezing more capacity out,”
Mr Verma says. “That is the kind of research work
that we’re engaged in right now. I have no doubt
we’ll get there.”
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This article, written by The Economist Intelligence Unit
and sponsored by Cisco, examines global organisations’
use of real-time information and its impact on strategy
and management. It is based on a global survey of 268
executives, just under one-third of whom hold positions
in the IT department, while 47% are members of the
C-suite. Respondents were drawn from companies in the
healthcare, transport, retail, healthcare, manufacturing
and energy sectors, 49% of which have annual revenue
over US$500m.
Information overload
The second most common challenge is incorporating the analysis of real-
time information into strategic decision-making, as identified by 44% of survey
respondents.