The document discusses how automotive companies can gain a competitive advantage by leveraging big data analytics to better understand customer demand, monitor corporate performance, and identify new opportunities. It provides examples of how General Motors, Ford, and Toyota are already using big data from sensors in vehicles and other sources to improve products and services. The document argues that tapping large sources of data will help automotive companies find new ways to differentiate themselves and stay ahead in a highly competitive industry.

1. “Using Big Data to Gain a Competitive Edge”
February, 2015
SouthEast Asia Automotive Technology Sumit 2015
Prepared by
Gilbreth Brown
Enterprise Solutions Sales Manager - Asia Region

2. Who really wants to be in the automotive industry?
High
High
High
High
Low
“If GM had kept up with technology like
the computer industry has, we would all
be driving $25 cars that got 1,000 MPG.”
Bill Gates
Porter’s Five Forces of Industry Attractiveness

3. Macro-economic forces strongly shape the industry
Source: ycharts.com
The cost of this crisis? Approximately $50 billion.

4. Small, nimble competitors find ways to penetrate:
--
5.00
10.00
15.00
20.00
25.00
30.00
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
BMW
Daimler
FCA
Ford
GM
Honda
Toyota
Other
General Motors
Other:
Kia, VW, Hyundai, Jaguar, Lexus, Volvo, Suzuki, Isuzu,
Subaru, etc
Market Share, U.S. automobile industry, 2005 to 2014
Source: Wards Automotive, 2015

5. Even with market protection, this is a cut-throat industry
Proton’s market share now stands at 17%, down from
an all time high of 75% in the early 1990s

6. Forget profits – innovate, or join the ranks of forgotten:
In fact, according to Forbes, the average lifespan of a
successful S&P 500 Company was 67 years in the 1920’s.
Today it is 15 years.

7. The automotive industry is shifting fundamentally:
Competing in a static market is difficult enough, but how about impending market shifts?
Emission
Controls
Vehicle Life
Span
In-vehicle
electronics
/connectivity
Safety
Features
Faster product
development
Massive increase Innovation needed
Much longerConsumer
conscience
Lightening speed

8. So, how do we compete in this new world order?
Start by asking yourself these 3 key questions:
Truly understanding
consumer demand and
behavior; do we even
know our own customers
and market?
Clearly monitoring and
measuring, at a deep
level, our internal and
external corporate
performance relative to
the market
Have we
exhausted all
possible sources
of data that
might help us to
answer these
questions?

9. Market differentiation is getting very difficult:
Quality
Perceived value (pricing)
Distribution / Retail
Customer Service
Marketing / Branding
Almost all major OEM vehicle
manufacturers compete
excellently in these functional
areas.
These are also all areas where an
OEM can LOSE money; however,
are these potential game changing
(e.g., steal significant market
share) areas of effort?
When all other factors are equal,
customers often make a purchase
decision based on “salient
differentiators.”
Design & Engineering
“Must
Haves”
What is the role here for
data driven analytics?

10. Salient Differentiation: “stand out!”
A salient differentiator can be a feature, service, program or
ingredient. To be worthy of the term “differentiator” — to be
more than just a name slapped on a feature — it must be
meaningful to customers; that is, it must be both pertinent and
substantial enough to matter when people are purchasing or
using the product or service.
It must also be actively managed (and thus be able to justify the
investment of management time) over an extended period —
years or even decades — so that it does not become stagnant.”
Source: Massachusetts Institute of Technology

11. Examples of salient differentiation:
Co-branding Product Development Customer Service

12. Ok, how do I find my salient differentiator??
Here, we would like to introduce
the term “Big Data.”
Big data is a collection of
data from traditional and
digital sources inside and
outside an organisation that
represents a source for
ongoing discovery and
analysis that will enable us
to understand and predict.
Almost all of our
automotive clients are now
asking about analytical
opportunities in “Big Data.”

13. Big Data – what is it?
Gartner* talks about Big Data, in terms of the 3
V’s:
“Volume” (the amount of data)
“Velocity” (the speed of information generated and
flowing into the enterprise)
“Variety” (the kind of data available)
Others suggest 2 additional V’s:
“Veracity” and “Value.”
Big data is that data that is so big, and is so
unstructured, that is defies traditional
collection methods, software requirements,
storage needs, and interpretive analysis.
Big Data is…
• Unstructured
• Unsuitable for a database
• Multiple sources/formats
• May require AI to interpret
• Exceeds “normal” analysis
• Growing exponentially
• Available - everywhere

14. How Big is Big Data?
Currently, the number of mobile phones in use exceeds the world population (7
billion) ; do you personally know anyone who doesn’t use one?
Facebooks generates 500 Terabytes of new data every day (1 TB = 1,000 GB)
In 1993, total Internet traffic amounted to approximately 100 TB for the year. As of
June 2008, Cisco Systems estimated Internet traffic at 160 TB/s ; in other words, the
amount of Internet traffic per second in 2008 exceeded all of the Internet traffic in
1993.
90% of the world’s network traffic data was created in the last two years.
The number of cars connected to the Internet worldwide will grow more than
fourfold to 152 million by 2020 from 36 million today
The average vehicle on the road today has more computing power than the
computer that sent the first astronauts to the moon.

15. Big Data – what do we do with it?
• Discovery of useful, possibly
unexpected, patterns in data
• Non-trivial extraction of implicit,
previously unknown and
potentially useful information
from data
• Exploration & analysis, by
automatic or
semi-automatic means, of large
quantities of data in order to
discover meaningful patterns
What is data mining?
Less than 5% of the world’s oceans have been
fully explored; what opportunities await us in the
exploration of big data?

16. What opportunity does it hold for an auto OEM?

17. Ok, who is using Big Data now? General Motors
“Currently General Motors is in the middle of the IT-transformation, where instead
of doing only 10% of the IT work in-house, 90% of it will be done in-house by the
end of 2015. They are hiring 12,000 IT personnel and the objective is to have
10,000 of its IT personnel work on new developments by 2018.
They have also developed their own, $ 130 million, data centre that runs on
Hadoop. It has almost 37,000 servers and an 8 Terabyte fibre optic data connection
to their other data centres. Another $ 258 million data centre is also being built in
the same area. In total, GM plans to spend $ 546 million on their new data centres,
planned in Warren and Milford.
The new data centre already has 3 Petabytes of data on site, consisting of product
development, procurement, logistics, quality, manufacturing, customer care, sales,
marketing, finance, and other kinds of data.”
Source: Datafloq.com

18. Ok, who is using Big Data now? Ford Motor Company
Source: Datafloq.com
Ford recently opened a lab in Silicon Valley to improve its cars with big data. In order to
progress their cars regarding fuel consumption, safety, quality and emissions, Ford
gathers data from over four million cars with in-car sensors and remote application
management software. All data is analyzed in real-time giving engineers valuable
information to notice and solve issues in real-time, know how the car responds in
different road and weather conditions and any other forces that could affect the car.
Ford is also installing numerous sensors in their cars to monitor behavior. They install
over 74 sensors in cars including sonar, cameras, radar, accelerometers, temperature
sensors and rain sensors. As a result, the Energi line of plug-in hybrid cars generate over
25 gigabytes of data every hour. This data is returned back to the factory for real-time
analysis and returned to the driver via a mobile app. The cars in its testing facility
even generate up to 250 gigabytes of data per hour from smart cameras and sensors.

19. Ok, who is using Big Data now? Toyota Motor Company
Source: Datafloq.com
May 23, 2013: Toyota announced today what it calls the “Big Data Traffic Information
Service,” a giant mashup of data harvested from currently 3.3 million of telematics users
in Japan, and 700,000 Toyota customers equipped with a Digital Communication
Module (DCM), a sensor module that constantly monitors and transmits vehicle
data. Combined with other telematics data, the system powers navigation and
information services. Unlike other systems, Toyota’s on-line platform can also be used
by local governments and businesses.
Being a Japanese system, the Big Data service is heavy on disaster management and
relief functions. As long as the cellphone data network has not been wiped out, the
system provides routes to and locations of evacuation sites, even the possible heights of
a tsunami, should one strike. The system can communicate with on-board systems,
smartphones, tablets etc. The system is relatively low-cost. An annual subscription by
users costs $25. Disaster information is free of charge. Commercial users can book the
platform and 100,000 transactions for $2,000 per month.

20. Conclusion & Summary
Let’s review where we have come from, and where we are going:
Highly
competitive
pressure Downward
pressure
on profits
Innovate,
or be
forgotten Finding our
salient
difference Tapping
large sources
of data to
find a
competitive
advantage
Big
Data
Cloud
While its good to know why a
customer bought your vehicle, its
even better to know why they did
not!

21. Pentana Solutions
Pentans Solutions is an information and technology solutions provider to the
automotive industry:
40 years in the business
400 + employees
$110million per annum, with 10% redirect back to R&D
120 countries; strong presence in Asia – Philippines, Thailand, Malaysia, Singapore
Products we offer:
Dealer management systems
Distribution and importation systems
Full ERP back end packages; warehouse management solutions
Electronic catalogs and aftersales parts solutions
Work shop systems
Data compilation and distribution