BEST PRACTICES
Prioritizing Data
Rights / Storage / Purpose
D Tim Witten
24 | Mass Transit | MassTransitmag.com | JULY/AUGUST 2017
Urbana, Ill.
D
Andrew
Johnson
Chief Operating
Officer
Champaign-
Urbana Mass
Transit District
ATA IS ARGUABLY THE MOST IMportant
aspect of our organization,
but managing, prioritizing and utilizing
it all isn’t simple. Here are fi ve
powerful questions that led to powerful
results for our organization:
Do you own all of the rights to the
data and follow the appropriate processes?”
If you don’t own the data, you can’t
manipulate and share the data, therefore
you have no fl exibility to change and
adapt with trends. Too many intelligent
transportation systems’ deployments are
conducted without a clear understanding
of data ownership. We follow the U.S.
Department of Transportation’s Systems
Engineering Process for ITS and make
sure that we have full access and rights
to data. By doing so, we can prepare for
future technology and design, procure
and deploy better systems.
How do you decide what stays and
what goes? We store all data onsite with
remote backups and we keep as much of
it as we can. We do this because storage
and processing is becoming cheaper, and
we want to be prepared for the unknown.
What level of staffi ng do you need
and what do their qualifi cations need to
be? Finding the right person to fi ll an ITS
role is much more important than having
a large quantity of people in your division.
For example, in a transit data analyst,
you need someone who understands
transit operations, can communicate effectively
and can manipulate data from
a variety of sources. We’ve been able to
hire employees with impressive writing
or research backgrounds and then train
them on the transit portion of the job.
How do you prioritize the data? Staff
time is fi rst dedicated to getting the best
possible information to the public. Our
ITS team ensures customer-facing systems
are functioning properly and providing
customers with the information
ITS Manager
Blacksburg
Transit
they need. Th e data that we collect builds
our web service, which feeds information
into our app, website, texting service and
third-party developers’ apps. Since our
customers rely on this information, it’s
important to ensure everything is working.
Th e data is also used to generate reports
for the Federal Transit Administration,
state and local stakeholders, and
internal operation planning.
Initially our focus was on documenting
the report generation processes and
automating this when possible. Once
this was accomplished, we switched
our focus to producing deeper analysis
where needed and building additional
processes for local data analysis needs.
Recently, staff time has been spent
building a trip generation model for
student-based housing. Th e housing
complexes are hard to handle in existing
models, so BT is using historical data in
combination with land-use data to predict
how changes in bedroom count or
service levels may aff ect ridership.
“Why are you collecting all of this
data?” Th e goal of all data collection is to
better educate our customers. If we know
exactly where a bus is located, how many
people are on the bus, when it will arrive
at a certain stop, then why shouldn’t
the customer have this information? We
collect this data to give customers confi -
dence in navigating our system. In order
to manage, prioritize and utilize all data
collected, you need to understand that
data takes planning. To reap the benefi
ts of data collection, you need to have
a well thought-out plan, appropriate infrastructure
and the right staff .
Blacksburg, Va.
ATA MANAGEMENT CAN MEAN
so many things and is especially
challenging for mid-size agencies
like Champaign-Urbana Mass Transit
District. Given our annual ridership of
12.7 million, we accumulate the same
types and volume of data as larger
properties and have much of the same
technology in place, but we have fewer
people to manage, analyze and apply
that data. We’re fortunate to be in a university
town, where we’re able to augment
our own talent by participating
in student projects and hiring interns
from the University of Illinois. I like to
say we’re small, but mighty.
CUMTD’s commitment to continual
improvement dictates that we are
always improving processes to utilize as
much of the data that our vehicles give
us as possible. Whether we’re analyzing
information to justify a new stop, fi x
an issue with service delivery, allocate
stop amenities, or create easier ways for
people to understand and use our system,
our planning model is cyclical and
constant. We plan, run service, collect
data, analyze it, and improve. Th en we
repeat that process. In doing so, we are
careful to actively seek human input.
Th e human factor is something
oft en overlooked when talking about
data analyzation and application and
that’s a mistake. Planning needs vary
based on community development or
redevelopment.
One of the more creative and compelling
things CUMTD does with data
is to use our static planning data to supplement
the real-time data coming out
of our CAD/AVL system. In essence,
we are able to pull information from
that real-time feed and match it up with
static planning data.