This document discusses how big data can help shipping and freight companies by allowing them to analyze large amounts of traditional and non-traditional data. It explains that traditional data comes from business systems, while non-traditional data includes real-time information from sensors, GPS devices and weather/traffic reports. Analyzing both types of data together using big data solutions can help carriers and shippers optimize costs, transit times and profitability by informing decisions around routing, delays and repairs. The document advocates that big data, when properly used with business expertise, can quantify decisions and help companies achieve objectives like reducing costs and improving efficiency.

1. Why You Should Care About
Big Data In Shipping & Freight

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5. What is “big data in shipping?”

6. First, it's important to recognize
the difference between 'lots of
data' and 'big data.' traditional
technology has been serving
organizations’ analytics needs for
decades, allowing them to
analyze large data sets from
traditional sources such as
warehousing and distribution
systems.

7. ‘Big data’ takes it to
the next level,
allowing companies
to harness
extremely large data
volumes including
non-traditional data
types such as text,
audio and video in
conjunction with
information from
business systems in
a much more
economical fashion.

8. This Is Just An Expensive It
Solution Then?

9. No – it's not about it at all; remember the term “garbage in =
garbage out? That's too-much data, not big data. A company
needs to determine what they want to do...Reduce costs?
Increase revenue? Optimize transit times?
Hese are all serious strategic issues for both a carrier and a
shipper, whose implementation – or not – affects profitability on
every voyage
The carrier needs to sit with a company like ours in order to figure
out the questions that need to be asked in order affect positive
outcomes, and determine what is the traditional and
non-traditional data that goes into profitability.

10. What's Traditional Data Vs.
Non-traditional Data?

11. Traditional data is
look-back data
from ordinary
business systems;
fuel costs, transit
times, wages,
insurance, revenue
per teu. It's
accounting data
that's used to
determine the
profitability of a
voyage.

12. But non-traditional data is
time-sensitive data – weather and
traffic delays, port strikes,
unexpected repairs. It’s also
extremely large volumes of data
being generated from sensors, gps
devices, rfid tags and traffic
management systems.

13. And Non-traditional Data Is
Quantifiable?

14. Some is, some isn't, but it's all related to issues that can be
resolved or avoided. If a storm blows up, would you steam
through it? Perhaps not, but you’d use a ‘big data’ solution to
analyze gps-type information to quickly determine the costs of
other routes as opposed to not diverting.
Preventive technology is a lifesaver for most forms of
transportation from a container ship to a delivery truck; modern
sensor technology enables the carrier to be warned of failures
before they occur, which allows management to affect repairs
prior and on a timely basis.
Or a 3pl might get a message from his gps about a highway being
closed, so instead of having the truck idling in traffic burning fuel
and time; the driver would be re-routed.

15. This Sort Of Information Would
Be Equally Important For The
Shipper?

16. Absolutely; whether you’re shipping
the goods as a vendor, or receiving
them as the buyer; getting them to
the final destination on time,
undamaged, and in a cost-effective
manner is important.

17. Is Big Data Alone All You Need
To Make Your Logistics
Procurement Business
Successful?

18. At xeneta, we have the industry business and technical expertise
needed to make sense of the ‘big data’ our platform aggregates
and presents.
We'll work with our customers to articulate and advise on their
strategic direction and answer business-critical questions based
on the facts we see coming from the data we hold: what
problems are you trying to resolve? What direction do you want to
go? What data do you need brought forward? While we’re it
people; we're business people first.

19. Is There A Place For Big Data In
Supply Chain Management?

20. Absolutely; in fact it's what makes
advanced scm possible. It's using big
data to start replacement inventory
moving before inventory is exhausted.

21. Final Thoughts On The Use Of
Big Data For Shippers And
Carriers

22. When properly used, big data will enable management to take a
gut-feel decisions and quantify it, which lets them take that good
idea and make it work.
It's important to remember that big data is used in assisting your
company in achieving it's business objectives, whether reducing
costs or improving efficiency, which is of obvious daily
importance to carriers and shippers, or increasing sales, which is
of interest to everyone.

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