What is Big Data? Big Data Laws Why Big Data? Industries using Big Data Current process/SW in SCM Challenges in SCM industry How Big data can solve the problems? Migration to Big data for an SCM industry

1. Big Data
Topics Covered
•What is Big Data?
•Big Data Laws
•Why Big Data?
•Industries using Big Data
•Current process/SW in SCM
•Challengesin SCM industry
•How Big data can solve the problems?
•Migration to Big data for an SCM industry

2. What is Big Data?
IBM Says WIKI Says
Every day, we create 2.5 Big data is more than simply a
quintillion bytes of data — so matter of size; it is an opportunity
much that 90% of the data in to find insights in new and
the world today has been emerging types of data and
content, to make your business
created in the last two years more agile, and to answer
alone. This data comes from questions that were previously
everywhere: sensors used to considered beyond your reach.
gather climate information, Until now, there was no practical
posts to social media sites, way to harvest this opportunity.
digital pictures and videos, Today, IBM’s platform for big data
purchase transaction records, uses state of the art technologies
and cell phone GPS signals to including patented advanced
name a few. This data is big analytics to open the door to a
data. world of possibilities.

3. What is Big Data?
Real Time

4. What is Big Data?
Changes & Challenges
Big data is difficult to The challenges include
work with using most
relational database •capture
management systems •curation
and desktop statistics •storage
and visualization
packages, requiring •search
instead "massively •sharing
parallel software
running on tens, •analysis
hundreds, or even •visualization
thousands of servers".

5. What is Big Data?
The key platform capabilities include
Visualization and Hadoop-based Analytics: Store any
Discovery: Discover, understand, data type in the low-cost, scalable
search, and navigate federated Hadoop engine to lower the cost of
sources of big data while leaving processing and analyzing massive
that data in place. volumes of data.
Stream Computing: Continuously
analyze massive volumes of
streaming data with sub-millisecond
response times to take action in
real-time.
Data Warehousing: Store and Text Analytics: Analyze textual
analyze large volumes of structured content to uncover hidden
information with workload
optimized systems designed for meaning and insight in
deep & operational analytics. unstructured information.

6. What is Big Data?
Supporting platform services
Accelerators: Faster time to Application
value with pre-packaged Development: Streamline the
analytical and industry-specific process of developing big data
content. applications.
Information Integration and
Governance: Integrate, protect,
cleanse, govern, and deliver your
trusted information
Systems Management: Monitor Reference
and manage your big data system Architectures: Hardware,
for secure and optimized networking and system software
performance. blueprints to accelerate time to
value.

7. What is Big Data?

8. What is Big Data?
Examples
Examples include Big Science, web logs, RFID, sensor
networks, social networks, social data (due to the social data
revolution), Internet text and documents, Internet search
indexing, call detail records, astronomy, atmospheric science,
genomics, biogeochemical, biological, and other complex
and often interdisciplinary scientific research, military
surveillance, medical records, photography archives, video
archives, and large-scale e-commerce.

9. Big Data Laws

10. Big Data Laws

11. Why Big Data?

12. Why Big Data?

13. Why Big Data?

14. Industries using Big Data
•Banking •Energy and Utilities
•Risk and fraud management •Smart meter analytics
•Customer analytics •Asset management
•Transportation •Digital Media
•Logistics optimization •Real-time ad targeting
•Traffic congestion •Website analysis
•Healthcare •Retail
•Medical record text •Omni-channel marketing
analytics •Click-stream analysis
•Genomic analytics •Government
•Telecommunications •Threat prediction and
•Call detail record processing prevention
•Customer profile •Fraud and abuse
monetization management

15. Industries using Big Data
Big data = Big Return on Investment (ROI)
While there is a lot of buzz about big data in the market,
it isn’t hype.
Healthcare: 20% decrease in
patient mortality by
analyzing streaming patient
data
Telco: 92% decrease in Utilities: 99% improved accuracy
processing time by analyzing in placing power generation
resources by analyzing 2.8
networking and call data petabytes of untapped data

16. Current process/SW in SCM
•ERP and SCP
• WMS
•TMS
•MES

17. Current process/SW in SCM overcomes
Lack of visibility: Large corporations were left with too much inventory when the
recession hit and too little when demand picked up in 2009. “Users are looking at
applications like sales and operations planning, transportation management and
asset management applications that can be leveraged to track goods in motion,”
Eschinger says.
Enabling corporate strategy: Everyone wants to reduce costs, but increasingly
businesses are targeting supply chains to improve overall corporate viability,
especially customer service.
Total landed cost: Blame high transportation costs, increasing wages in emerging
markets and multi-channel sales and distribution strategies, but companies are
taking a more analytical look at what it costs to fill an online order versus a store
and what is the total cost to source in Mexico versus China.

18. Current process/SW in SCM

19. Challenges in SCM industry

20. Challenges in SCM industry
Customer service Cost control Planning and Risk Management
Effective supply chain management is Supply chain operating costs are under Supply chains must periodically be
all about delivering the right product in pressure today from rising freight assessed and redesigned in response to
the right quantity and in the right prices, more global customers, market changes, including new product
condition with the right documentation technology upgrades, rising labor rates, launches, global sourcing, new
to the right place at the right time at expanding healthcare costs, new acquisitions, credit availability, the need
the right price. If only it were as simple regulatory demands and rising to protect intellectual property, and the
as it sounds. commodity prices. To control such costs ability to maintain asset and shipment
there are thousands of potential security. In addition, supply chain risks
metrics that supply chain organizations must be identified and quantified. SCC
can and do measure. Managers need to members report that less than half of
zero in on the critical few that drive their organizations have metrics and
total supply chain costs within their procedures for assessing, controlling,
organizations. and mitigating such risks.
Supplier/partner relationship Talent
management As experienced supply chain managers
Different organizations, even different retire, and organizations scale up to
departments within the same meet growing demand in developing
organization, can have different markets, talent acquisition, training,
methods for measuring and and development is becoming
communicating performance increasingly important. Supply chain
expectations and results. Trust begins leaders need a thorough understanding
when managers let go of internal biases of the key competencies required for
and make a conscious choice to follow supply chain management roles,
mutually agreed upon standards to specific job qualifications, methods for
better understand current performance developing future talent and leaders,
and opportunities for improvement. and the ability to efficiently source
specific skill sets.

21. Challenges in SCM industry

22. How Big data can solve the
problems?

23. How Big data can solve the
problems?

24. How Big data can solve the
problems?

25. How Big data can solve the
problems?
Digital Path to Purchase. The work ecommerce. Amazon‘s work on
that McCormick is doing on Digital Path to understanding demand insights of pantry
Purchase is breakthrough thinking. I shopping is exciting. They are an early
would start there. leader in Big Data techniques. I would have
them at the top of my list.
Listening. Text mining and ratings and Safe and Secure Supply Chains. The work
review information at Bazaarvoice is a Big at Eli Lilly on product serialization of
Data service. How could companies use pharmaceuticals has direct applicability of
this data? How could it help in sensing where we are headed on food safety. Food
early product failure? Only one out of ten and beverage companies need to learn
companies that I talk to have ever heard from this early work in Big Pharma.
of Bazaarvoice and the great work that .
they are doing.

26. How Big data can solve the problems?
Supplier Sensing. The work at D&B on supplier sensing Supply Chain Visibility. Let’s face it, we have been
is a great use of Big Data. I would include them in the talking about supply chain visibility and agile supply
list and work with them on how consumer products chains for many years, but it has just been talk. The
companies and retailers can sense supplier failure early use of rules-based ontologies and learning
and use it to build stronger supplier relationships. We systems to redefine supply chain visibility at Conair is
have talked about collaboration, but in reality, we have a new way to think about sensing supply chains.
pushed costs and working capital back into the chain While early, it is a great case study on how to use Big
increasing risk. The further back in the supply chain that Data techniques to solve a tough problem.
we go and sense supplier health, the weaker the players
and the greater the risk to the brand. The work at D&B
is a great start to better understand this.
Demand Insights. The work at Kraft on consumer Large-scale ERP. The race is on for global companies
insights, or the work at General Mills on downstream to better serve emerging markets. These markets
data are Big Data problems in the making. While both are fraught with disparate data that is often
companies today are using more conventional incomplete. These large consumer products
techniques, the size of the data is growing and insights companies are also the companies with BIG DATA
can be gained on where we are headed. ERP systems. What are best practices for companies
in the ERP Petabyte club? How does the data
change? How does it affect maintenance and
upgrade cycles? And the definition of business
analytics?

27. Migration to Big data for an SCM
industry

28. Migration to Big data for an SCM
industry

29. Migration to Big data for an SCM
industry

30. Migration to Big data for an SCM
industry

31. The End
Thanks
Prepared by
RedwanulHaqChoyon
+8801611-222447
email: redwan.choyon@gmail.com