eye for transport june big data_june12
DESCRIPTION
We don't have a big data problem. We have a big data opportunity. Our challenge is to change our mental models to embrace clouds, streams and lakes. Today, we are too encased in the world of relational database models and inside-out processes. Here I share my research on Big Data in Supply Chain and encourage the audience to participate in our 2014 study on the adoption of Big Data in Supply Chain.TRANSCRIPT
TM
The Big Data Opportunity
Supply Chain Insights LLC Copyright © 2013, p. 2
Supply Chains Don’t Play by the Rules
2
But, what if they
could?
Supply Chain Insights LLC Copyright © 2013, p. 3
Could the Answer Lie in….
Clouds?
Streams?
Lakes?
Supply Chain Insights LLC Copyright © 2013, p. 4
Big Data Supply Chains are Evolving
4
Challenges:
• Transactional• Time phased data
Structured Data
• Social• Channel• Customer Service• Warranty
• Temperature• RFID• QR codes• GPS
• Mapping and GPS• Video• Voice• Digital Images
Unstructured Data
SensorData
NewDataTypes
Volume
Velocity
Variability
Supply Chain Insights LLC Copyright © 2013, p. 5
Connecting the Extended Supply Chain
5
Trading Partner 1 Trading Partner 2 Trading Partner 3
Transactional Applications
Transactional Applications
Transactional Applications
Store
Supply Chain Insights LLC Copyright © 2013, p. 6
Evolving Supply Chain Architectures
6
Collaborative Layer
Collaborative Layer
Collaborative Layer
Enterprise Data Warehouse
Enterprise Data Warehouse
Supplier Signal Repository
Demand Signal Repository
Predictive AnalyticsKey:
Transactional Adapters and Intelligent Rule Sets
Trading Partner 1 Trading Partner 2 Trading Partner 3
Transactional Applications
Transactional Applications
Transactional Applications
Enterprise Data Warehouse
Store
Supply Chain Insights LLC Copyright © 2013, p. 7
Rethinking Analytics
DescriptiveConnect with reality, a single source of
the truth
PredictiveUnderstand the most likely future
scenario, and the business implications
PrescriptiveRecommendation of the best
alternative
CognitiveHighly automated optimization
solutions that get smarter over time
What happened?
What will Happen?
What should we do about it?
Learning Systems
Supply Chain Insights LLC Copyright © 2013, p. 8
Thinking Harder about the Problem
EngineInputs Outputs
• Deterministic Optimization• Stochastic Optimization• Simulation• Cognitive Learning Engines
Depth of Analysis
Scope• Single function within the enterprise• Multiple functions within the enterprise• Connection of trading partners on single functions• Connection of trading partners on multiple functions (make,
source, and deliver)
• Single signals (single numbers)• Time-phased outputs• Multiple signals with time-phased outputs• Patterns and probabilities
• Single signals (single numbers)• Time-phased inputs• Multiple signals with time-phased inputs• Patterns and probabilities
The Data Model of the Engine
Supply Chain Insights LLC Copyright © 2013, p. 9
Agenda
Study Overview
Data & Technology
Big Data
Master Data Management
Supply Chain Insights LLC Copyright © 2013, p. 10
Study Overview
Supply Chain Insights LLC Copyright © 2013, p. 11
Respondents Work at Companies with an Average of 20K Employees and $4B Revenue
Supply Chain Insights LLC Copyright © 2013, p. 12
13% of Respondents Lead the Big Data Initiative;7% Lead the Master Data Management Program
Supply Chain Insights LLC Copyright © 2013, p. 13
Agenda
Study Overview
Data & Technology
Big Data
Master Data Management
Supply Chain Insights LLC Copyright © 2013, p. 14
Business Pain
Supply Chain Insights LLC Copyright © 2013, p. 15
Data Sources
Supply Chain Insights LLC Copyright © 2013, p. 16
The Diffences
Supply Chain Insights LLC Copyright © 2013, p. 17
15% Already Have a Database That Equals a Petabyte
Supply Chain Insights LLC Copyright © 2013, p. 18
18% Have a ERP Live Instance That Is 6+ Terabytes;16% Have 11+ Unique IT Systems
Supply Chain Insights LLC Copyright © 2013, p. 19
Agenda
Study Overview
Data & Technology
Big Data
Master Data Management
Supply Chain Insights LLC Copyright © 2013, p. 20
Three-Quarters See Big Data as anOPPORTUNITY
Supply Chain Insights LLC Copyright © 2013, p. 21
Over One-Quarter Have a Big Data Initiative and Over One-Third Plan to Have One
Supply Chain Insights LLC Copyright © 2013, p. 22
Agenda
Study Overview
Data & Technology
Big Data
Master Data Management
Supply Chain Insights LLC Copyright © 2013, p. 23
One-third Already Have a MDM Program, with Nearly as Many Planning to Have One
Supply Chain Insights LLC Copyright © 2013, p. 24
Over Half Believe That Big Data MakesMaster Data Management EASIER
Supply Chain Insights LLC Copyright © 2013, p. 25
Big data offers new opportunities to solve problems, but we must first challenge our
traditional paradigms.
Summary
Supply Chain Insights LLC Copyright © 2013, p. 26
Could the Answer Lie in….
Clouds?
Streams?
Lakes?
Supply Chain Insights LLC Copyright © 2013, p. 27
You Help Us. We Help You.
Supply Chain Insights LLC Copyright © 2013, p. 28
Questions?
Supply Chain Insights LLC Copyright © 2013, p. 29
What’s Happening at Supply Chain Insights
www.supplychaininsights.com
Supply Chain Insights LLC Copyright © 2013, p. 30
About Lora Cecere
• Founder of Supply Chain Insights
• Invited to be a “LinkedIn Influencer”
• Invited to write a guest blog for Forbes
• Author of 2 books: Bricks Matter (2012) and Metrics That Matter (to publish Fall of 2014)
• Partner at Altimeter Group (leader in open research)
• 7 years of Management Experience leading Analyst Teams at Gartner and AMR Research
• 8 years Experience in Marketing and Selling Supply Chain Software at Descartes Systems Group and Manugistics (now JDA)
• 15 Years Leading teams in Manufacturing and Distribution operations for Clorox, Kraft/General Foods, Nestle/Dreyers Grand Ice Cream and Procter & Gamble.
Contact Information: • Email: [email protected]• Blog: www.supplychainshaman.com (6000 pageviews/month)• Forbes: http://www.forbes.com/search/?q=lora+cecere• Twitter: lcecere (4800 followers)• LinkedIn: linkedin.com/pub/lora-cecere/0/196/573 (7000 in the
network)
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