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Big Data and its
Applications in
Supply Chain
Management
Maggie Zhang,
Zibin Guan,
Venkata Malapati,
Darpan Shah,
Reasons for SCM Domain
At the beginning:
 You may not like Supply Chain at all.
 You may have terabytes Data but with
no Science and even no Sense at all.
 So, there are some opportunity of using Data
Science and Big Data to improve Supply
Chain just like how they improve people’s
lives.
Big Data Changes the World
Real Issue In SCM
 Retailers 'Stress from Amazon
 Fears of going out of business (Toys’ R Us and Sears)
 Fight with Amazon.
 Achiever: Global giant retailer – Walmart’s
President and CEO Doug McMillon said:
“Our Omni-channel initiatives are contributing to comp sales
growth and providing customers with new levels of shopping
convenience, to help deliver a more compelling store
experience, we continue to bring digital capabilities to our stores
to deliver a seamless experience for customers, however they
choose to shop.”
Walmart’s Big Data in SCM
 Walmart Grocery
 Promise of the same low prices
 Pick up at any preferred store
 Special parking space with Orange sign
 Promotion codes
Walmart’s Big Data Storage
What Retailers want
 How much cost Big Data can enable the
business to save when inventories flow from
all over the world to consumers’ hands
 How the inventory flow channel can be
optimized for the business to have cost
advantages.
Big Data 4 Vs in SCM
Volume & Velocity
 608 million packages (18.5
pps)
 51 billion in shipments (162
sps)
 9.49 billion items (306 ips)
 180 million items
(Thanksgiving, 417 ips)
 Data Network (customer,
manufactory, carriers, e-
business)
 Location
Variety & Veracity
 Carriers, location,
customers, etc.
 Analyzing
 Ranking
 Ranking System
 Information
Asymmetry
 Outlier detection
Cost Saving in SCM Pipeline
Existing Solution
 EDI
 UPS’ ORION
 1) Data Transfer - Velocity
2) Data Security - Veracity
3) Data Integration – Variety
4) Data Storage - Volume
Our Ideas
Solutions
 Use Micro Server and Micro Services
concepts to solve data storage issues.
 Use necessary skills to ensure Cloud Security.
 Implement GPS calculating Algorithm to
calculate the cost and provide the APIs in
order to deploy the application to different
corporations.
 Visualization of Interfaces
Thank you!

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Big Data Applications in Supply Chain Management

  • 1. Big Data and its Applications in Supply Chain Management Maggie Zhang, Zibin Guan, Venkata Malapati, Darpan Shah,
  • 2. Reasons for SCM Domain At the beginning:  You may not like Supply Chain at all.  You may have terabytes Data but with no Science and even no Sense at all.  So, there are some opportunity of using Data Science and Big Data to improve Supply Chain just like how they improve people’s lives.
  • 3. Big Data Changes the World
  • 4. Real Issue In SCM  Retailers 'Stress from Amazon  Fears of going out of business (Toys’ R Us and Sears)  Fight with Amazon.  Achiever: Global giant retailer – Walmart’s President and CEO Doug McMillon said: “Our Omni-channel initiatives are contributing to comp sales growth and providing customers with new levels of shopping convenience, to help deliver a more compelling store experience, we continue to bring digital capabilities to our stores to deliver a seamless experience for customers, however they choose to shop.”
  • 5. Walmart’s Big Data in SCM  Walmart Grocery  Promise of the same low prices  Pick up at any preferred store  Special parking space with Orange sign  Promotion codes
  • 7. What Retailers want  How much cost Big Data can enable the business to save when inventories flow from all over the world to consumers’ hands  How the inventory flow channel can be optimized for the business to have cost advantages.
  • 8. Big Data 4 Vs in SCM
  • 9. Volume & Velocity  608 million packages (18.5 pps)  51 billion in shipments (162 sps)  9.49 billion items (306 ips)  180 million items (Thanksgiving, 417 ips)  Data Network (customer, manufactory, carriers, e- business)  Location
  • 10. Variety & Veracity  Carriers, location, customers, etc.  Analyzing  Ranking  Ranking System  Information Asymmetry  Outlier detection
  • 11. Cost Saving in SCM Pipeline
  • 12. Existing Solution  EDI  UPS’ ORION  1) Data Transfer - Velocity 2) Data Security - Veracity 3) Data Integration – Variety 4) Data Storage - Volume
  • 14. Solutions  Use Micro Server and Micro Services concepts to solve data storage issues.  Use necessary skills to ensure Cloud Security.  Implement GPS calculating Algorithm to calculate the cost and provide the APIs in order to deploy the application to different corporations.  Visualization of Interfaces