Cover
List of Figures
List of Tables
Preface
Acknowledgments
CHAPTER 1: Demand-Driven Forecasting in the Supply Chain
1. 1. DATA
2. 2. ANALYTICS
3. 3. COLLABORATION—PEOPLE AND PROCESSES USING A COLLABORATIVE APPROACH
CHAPTER 2: Introduction to Cloud Computing
1. 1. VIRTUALIZATION
2. 2. BIG DATA
CHAPTER 3: Migrating to the Cloud
1. 1. IDENTIFY BUSINESS REASONS FOR CLOUD
2. 2. PERFORM CLOUD READINESS CHECKS
3. 3. APPLY THE R FRAMEWORK
4. 4. IDENTIFY CLOUD TYPE, CLOUD SERVICE, CLOUD VENDOR
5. 5. MIGRATION FACTORY
CHAPTER 4: Amazon Web Services and Microsoft Azure
1. 1. AWS (AMAZON WEB SERVICES)
2. 2. MICROSOFT AZURE
CHAPTER 5: Case Studies of Demand-Driven Forecasting in AWS
1. CASE STUDY 1: NEWS AND MEDIA COMPANY
2. CASE STUDY 2: OIL AND ENERGY COMPANY
CHAPTER 6: Summary
Glossary
References
About the Author
Index
End User License Agreement

List of Tables

Chapter 2
1. Table 1 AWS Cost Calculation Example
2. Table 2 Percentage of Companies Adopting at Least One Cloud Solution by Industry Sector 2013–2015
3. Table 3 Revenue Growth Attributed to Cloud Adoption
Chapter 3
1. Table 4 Cloud Readiness Check Example (ISG)
2. Table 5 AWS Cloud Adoption Framework
3. Table 6 Respondents' Views on Which Cloud Services Gave the Best Economic Return
4. Table 7 Preferred Choice of Cloud Services Provider
5. Table 8 Main Choice Factor for Cloud Service Provider
6. Table 9 Market Comparison of Top 25 to 100 Vendors by Origin
7. Table 10 Estimated EU Market Shares of Top 25 Public Cloud Service Providers
Chapter 4
1. Table 11 Key‐Value Data Store Example
2. Table 12 Document Data Model Example

List of Illustrations

Chapter 1
1. Figure 1 Push and Pull—Sales and Operations Process
2. Figure 2 Digital Supply Chain—Interconnected
3. Figure 3 Supply Chain Control Tower
4. Figure 4 MHI 2018 Survey Results: Company Challenges
5. Figure 5 Example: Product Dimension Hierarchy
6. Figure 6 Example: Star Schema ‐ Forecast Dimensions
7. Figure 7 Traditional Data Flow—Supply Chain Analytics
8. Figure 8 Data Lake ‐ Data for Demand Forecasting
9. Figure 9 High‐level Lambda Architecture Design
10. Figure 10 Hybrid Modern Data Flow—Supply Chain Analytics
11. Figure 11 DDPP Model—Types and Maturity of Analytics
12. Figure 12 Microsoft AI Example—High Level
13. Figure 13 Microsoft AI Services Example
14. Figure 14 Demand‐Driven Forecasting and IoT
15. Figure 15 Demand Shaping—Personalized Recommendations
16. Figure 16 DDSC Benefits All Participants—BCG, 2012
17. Figure 17 Databerg and Dark Data
18. Figure 18 Random Walk Forecast Example
19. Figure 19 Sales and Seasonal Random Walk Forecast Example
20. Figure 20 SAS Demand‐Driven Planning and Optimization Example
21. Figure 21 Combining Cloud + Data + Advanced Analytics
22. Figure 22 Benefits of Demand‐Driven Supply Chain
Chapter 2
1. Figure 23 Time Line for Cloud Computing—Part 1
2. Figure 24 Time Line for Cloud Computing—Part 2
3. Figure 25 Traditional Server and Server Virtualization
4. Figure 26 Data Center Virtualization—Transformation
5. Figure 27 Virtual Machines Compared to Containers
6. Figure 28 Data Stored in Data Centers, 2016–2021, Cisco GCI
7. Figure 29 IT Systems to Benefit from Big Data
8. Figure 30 Big Data—Open Source Ecosystem
9. Figure 31 Cloud Computing—Five Characteristics
10. Figure 32 Black Friday—Traditional and Cloud
11. Figure 33 Cloud Price Index—451 Research Group
12. Figure 34 The Three Cloud Service Models
13. Figure 35 AWS Shared Responsibility Model
14. Figure 36 Microsoft Azure Portal Screenshot—IaaS Example
15. Figure 37 Microsoft Azure Portal Screenshot—PaaS
16. Figure 38 Cloud Service Model Growth 2016–2021
17. Figure 39 Enterprise SaaS Growth and Market Leaders, Q2 2017
18. Figure 40 Four Cloud Deployment Models
19. Figure 41 Cisco Global Cloud Index 2016–2021
20. Figure 42 Public versus Private Cloud
21. Figure 43 Cisco Global Cloud Index—Private versus Public Cloud
22. Figure 44 Top IaaS Platforms—Public Cloud
23. Figure 45 Importance of Cloud Benefits
24. Figure 46 Cloud Benefits 2017 versus 2016
25. Figure 47 Cloud Challenges 2017 versus 2016
26. Figure 48 Challenges Decrease with Cloud Maturity
27. Figure 49 IT Benefits of Cloud Computing
28. Figure 50 Costs and Benefits to Cloud Users
Chapter 3
1. Figure 51 Five Steps to the Cloud
2. Figure 52 Factors Preventing Enterprises' Use of Cloud
3. Figure 53 Economic impact of Cloud Computing in Europe
4. Figure 54 ISG Cloud Readiness Results Example
5. Figure 55 Example R Framework Migrating to Cloud
6. Figure 56 AWS Cloud Migration—6Rs
7. Figure 57 Considerations for Cloud Migration Examples
8. Figure 58 Cloud Migration Factory Approach
9. Figure 59 Cloud Vendor Benchmark 2016—Germany
10. Figure 60 The Race for Public Cloud Leadership
11. Figure 61 Cloud Migration Factory Methodology
Chapter 4
1. Figure 62 AWS Cloud Portfolio Categories
2. Figure 63 AWS EC2 On‐Demand Pricing Examples
3. Figure 64 AWS Global Regions for Public Cloud
4. Figure 65 Industrial Internet Economic Potential
5. Figure 66 AWS Cloud Service Portfolio
6. Figure 67 Microsoft Azure Cloud Portfolio Categories
7. Figure 68 Column Family Data Model Example
8. Figure 69 Data Flow Example
9. Figure 70 Industrial Internet Data Loop
10. Figure 71 Microsoft Demand Forecasting Example
Chapter 5
1. Figure 72 Example Methodology—Solution Assessment for Cloud
2. Figure 73 Supply Chain Optimization Solution Suite
3. Figure 74 Case Study—Deployment Example
Chapter 6
1. Figure 75 Connected Supply Chain Management
2. Figure 76 Demand‐Driven Supply Chain—Integration and Technologies
3. Figure 77 Modern Supply Chain and Technologies
4. Figure 78 Road to Modern Supply Chain Management

Wiley & SAS Business Series

The Wiley & SAS Business Series presents books that help senior‐level managers with their critical management decisions.

Titles in the Wiley & SAS Business Series include:

The Analytic Hospitality Executive by Kelly A. McGuire
Analytics: The Agile Way by Phil Simon
Analytics in a Big Data World: The Essential Guide to Data Science and Its Applications by Bart Baesens
A Practical Guide to Analytics for Governments: Using Big Data for Good by Marie Lowman
Bank Fraud: Using Technology to Combat Losses by Revathi Subramanian
Big Data Analytics: Turning Big Data into Big Money by Frank Ohlhorst
Big Data, Big Innovation: Enabling Competitive Differentiation through Business Analytics by Evan Stubbs
Business Analytics for Customer Intelligence by Gert Laursen
Business Intelligence Applied: Implementing an Effective Information and Communications Technology Infrastructure by Michael Gendron
Business Intelligence and the Cloud: Strategic Implementation Guide by Michael S. Gendron
Business Transformation: A Roadmap for Maximizing Organizational Insights by Aiman Zeid
Connecting Organizational Silos: Taking Knowledge Flow Management to the Next Level with Social Media by Frank Leistner
Data‐Driven Healthcare: How Analytics and BI Are Transforming the Industry by Laura Madsen
Delivering Business Analytics: Practical Guidelines for Best Practice by Evan Stubbs
Demand‐Driven Forecasting: A Structured Approach to Forecasting, Second Edition by Charles Chase
Demand‐Driven Inventory Optimization and Replenishment: Creating a More Efficient Supply Chain by Robert A. Davis
Developing Human Capital: Using Analytics to Plan and Optimize Your Learning and Development Investments by Gene Pease, Barbara Beresford, and Lew Walker
Economic and Business Forecasting: Analyzing and Interpreting Econometric Results by John Silvia, Azhar Iqbal, Kaylyn Swankoski, Sarah Watt, and Sam Bullard
Economic Modeling in the Post Great Recession Era: Incomplete Data, Imperfect Markets by John Silvia, Azhar Iqbal, and Sarah Watt House
Enhance Oil & Gas Exploration with Data Driven Geophysical and Petrophysical Models by Keith Holdaway and Duncan Irving
The Executive's Guide to Enterprise Social Media Strategy: How Social Networks Are Radically Transforming Your Business by David Thomas and Mike Barlow
Foreign Currency Financial Reporting from Euros to Yen to Yuan: A Guide to Fundamental Concepts and Practical Applications by Robert Rowan
Harness Oil and Gas Big Data with Analytics: Optimize Exploration and Production with Data Driven Models by Keith Holdaway
Health Analytics: Gaining the Insights to Transform Health Care by Jason Burke
Heuristics in Analytics: A Practical Perspective of What Influences Our Analytical World by Carlos Andre Reis Pinheiro and Fiona McNeill
Human Capital Analytics: How to Harness the Potential of Your Organization's Greatest Asset by Gene Pease, Boyce Byerly, and Jac Fitz‐enz
Implement, Improve and Expand Your Statewide Longitudinal Data System: Creating a Culture of Data in Education by Jamie McQuiggan and Armistead Sapp
Intelligent Credit Scoring: Building and Implementing Better Credit Risk Scorecards, Second Edition by Naeem Siddiqi
JMP Connections by John Wubbel
Killer Analytics: Top 20 Metrics Missing from Your Balance Sheet by Mark Brown
Machine Learning for Marketers: Hold the Math by Jim Sterne
On‐Camera Coach: Tools and Techniques for Business Professionals in a Video‐Driven World by Karin Reed
Predictive Analytics for Human Resources by Jac Fitz‐enz and John Mattox II
Predictive Business Analytics: Forward‐Looking Capabilities to Improve Business Performance by Lawrence Maisel and Gary Cokins
Profit Driven Business Analytics: A Practitioner's Guide to Transforming Big Data into Added Value by Wouter Verbeke, Cristian Bravo, and Bart Baesens
Retail Analytics: The Secret Weapon by Emmett Cox
Social Network Analysis in Telecommunications by Carlos Andre Reis Pinheiro
Statistical Thinking: Improving Business Performance, Second Edition by Roger W. Hoerl and Ronald D. Snee
Strategies in Biomedical Data Science: Driving Force for Innovation by Jay Etchings
Style & Statistic: The Art of Retail Analytics by Brittany Bullard
Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics by Bill Franks
Too Big to Ignore: The Business Case for Big Data by Phil Simon
Using Big Data Analytics: Turning Big Data into Big Money by Jared Dean
The Value of Business Analytics: Identifying the Path to Profitability by Evan Stubbs
The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions by Phil Simon
Win with Advanced Business Analytics: Creating Business Value from Your Data by Jean Paul Isson and Jesse Harriott

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Library of Congress Cataloging‐in‐Publication Data:

Names: Sharma, Vinit, 1974‐ author.

Title: The cloud-based demand-driven supply chain / Vinit Sharma.

Description: Hoboken, New Jersey : John Wiley & Sons, 2019. | Series: Wiley & SAS business series | Includes index. |

Identifiers: LCCN 2018029740 (print) | LCCN 2018041782 (ebook) | ISBN 9781119477808 (Adobe PDF) | ISBN 9781119477815 (ePub) | ISBN 9781119477334 (hardcover)

Subjects: LCSH: Business logistics. | Supply and demand—Management. | Cloud computing—Industrial applications.

Classification: LCC HD38.5 (ebook) | LCC HD38.5 .S544 2019 (print) | DDC 658.70285/46782—dc23

LC record available at https://lccn.loc.gov/2018029740

Cover Design: Wiley

Cover Image: © Fly_Studio/Shutterstock

List of Figures

Figure 1	Push and Pull—Sales and Operations Process
Figure 2	Digital Supply Chain—Interconnected
Figure 3	Supply Chain Control Tower
Figure 4	MHI 2018 Survey Results: Company Challenges
Figure 5	Example: Product Dimension Hierarchy
Figure 6	Example: Star Schema ‐ Forecast Dimensions
Figure 7	Traditional Data Flow—Supply Chain Analytics
Figure 8	Data Lake ‐ Data for Demand Forecasting
Figure 9	High‐level Lambda Architecture Design
Figure 10	Hybrid Modern Data Flow—Supply Chain Analytics
Figure 11	DDPP Model—Types and Maturity of Analytics
Figure 12	Microsoft AI Example—High Level
Figure 13	Microsoft AI Services Example
Figure 14	Demand‐Driven Forecasting and IoT
Figure 15	Demand Shaping—Personalized Recommendations
Figure 16	DDSC Benefits All Participants—BCG, 2012
Figure 17	Databerg and Dark Data
Figure 18	Random Walk Forecast Example
Figure 19	Sales and Seasonal Random Walk Forecast Example
Figure 20	SAS Demand‐Driven Planning and Optimization Example
Figure 21	Combining Cloud + Data + Advanced Analytics
Figure 22	Benefits of Demand‐Driven Supply Chain
Figure 23	Time Line for Cloud Computing—Part 1
Figure 24	Time Line for Cloud Computing—Part 2
Figure 25	Traditional Server and Server Virtualization
Figure 26	Data Center Virtualization—Transformation
Figure 27	Virtual Machines Compared to Containers
Figure 28	Data Stored in Data Centers, 2016–2021, Cisco GCI
Figure 29	IT Systems to Benefit from Big Data
Figure 30	Big Data—Open Source Ecosystem
Figure 31	Cloud Computing—Five Characteristics
Figure 32	Black Friday—Traditional and Cloud
Figure 33	Cloud Price Index—451 Research Group
Figure 34	The Three Cloud Service Models
Figure 35	AWS Shared Responsibility Model
Figure 36	Microsoft Azure Portal Screenshot—IaaS Example
Figure 37	Microsoft Azure Portal Screenshot—PaaS
Figure 38	Cloud Service Model Growth 2016–2021
Figure 39	Enterprise SaaS Growth and Market Leaders, Q2 2017
Figure 40	Four Cloud Deployment Models
Figure 41	Cisco Global Cloud Index 2016–2021
Figure 42	Public versus Private Cloud
Figure 43	Cisco Global Cloud Index—Private versus Public Cloud
Figure 44	Top IaaS Platforms—Public Cloud
Figure 45	Importance of Cloud Benefits
Figure 46	Cloud Benefits 2017 versus 2016
Figure 47	Cloud Challenges 2017 versus 2016
Figure 48	Challenges Decrease with Cloud Maturity
Figure 49	IT Benefits of Cloud Computing
Figure 50	Costs and Benefits to Cloud Users
Figure 51	Five Steps to the Cloud
Figure 52	Factors Preventing Enterprises' Use of Cloud
Figure 53	Economic impact of Cloud Computing in Europe
Figure 54	ISG Cloud Readiness Results Example
Figure 55	Example R Framework Migrating to Cloud
Figure 56	AWS Cloud Migration—6Rs
Figure 57	Considerations for Cloud Migration Examples
Figure 58	Cloud Migration Factory Approach
Figure 59	Cloud Vendor Benchmark 2016—Germany
Figure 60	The Race for Public Cloud Leadership
Figure 61	Cloud Migration Factory Methodology
Figure 62	AWS Cloud Portfolio Categories
Figure 63	AWS EC2 On‐Demand Pricing Examples
Figure 64	AWS Global Regions for Public Cloud
Figure 65	Industrial Internet Economic Potential
Figure 66	AWS Cloud Service Portfolio
Figure 67	Microsoft Azure Cloud Portfolio Categories
Figure 68	Column Family Data Model Example
Figure 69	Data Flow Example
Figure 70	Industrial Internet Data Loop
Figure 71	Microsoft Demand Forecasting Example
Figure 72	Example Methodology—Solution Assessment for Cloud
Figure 73	Supply Chain Optimization Solution Suite
Figure 74	Case Study—Deployment Example
Figure 75	Connected Supply Chain Management
Figure 76	Demand‐Driven Supply Chain—Integration and Technologies
Figure 77	Modern Supply Chain and Technologies
Figure 78	Road to Modern Supply Chain Management

Preface

It's time to get your head in the cloud!

In today's business environment, more and more people are requesting cloud‐based solutions to help solve their business challenges. So how can you not only anticipate your clients' needs but also keep ahead of the curve to ensure their goals stay on track?

With the help of this accessible book, you'll get a clear sense of cloud computing and understand how to communicate the benefits, drawbacks, and options to your clients so they can make the best choices for their unique needs. Plus, case studies give you the opportunity to relate real‐life examples of how the latest technologies are giving organizations worldwide the chance to thrive as supply chain solutions in the cloud.

What this book does:

Demonstrates how improvements in forecasting, collaboration, and inventory optimization can lead to cost savings.
Explores why cloud computing is becoming increasingly important.
Takes a close look at the types of cloud computing.
Makes sense of demand‐driven forecasting using Amazon's cloud or Microsoft's cloud, Azure.

Whether you work in management, business, or information technology (IT), this will be the dog‐eared reference you'll want to keep close by as you continue making sense of the cloud.

Acknowledgments

This book would not have been possible without the help and support from various colleagues, friends, and organizations. I would like to take this opportunity to thank Jack Zhang (SAS), Blanche Shelton (SAS), Bob Davis (SAS), and Stacey Hamilton (SAS) for supporting the idea and helping with moving it forward. A special thank you to Emily Paul (Wiley), Shek Cho (Wiley), Mike Henton (Wiley), and Lauree Shepard (SAS) for their help with turning the book into reality. Research from various organizations has been vital to the success of this book, and I would like to especially thank Carol Miller (MHI), Amy Sarosiek (GE), Emily Neuman (AWS), Frank Simorj (Microsoft), Heather Gallo (Synergy Research), Juergen Brettel (ISG Research), Kim Weins (RightScale), Michael Mentzel (Heise Medien), Owen Rogers (451 Research), and Suellen Bergman (BCG) for their help in including such content. Last, but not least, I would like to express a very special thank you to esteemed colleagues, supply chain gurus, and good friends Charles Chase (SAS) and Christoph Hartmann (SAS) for their expert help with this book.

A special thank you to the following organizations for their help: 451 Research, AWS, Boston Consulting Group, Cisco, European Commission, European Union, Experton Group, Gartner, GE, Heise Medien, IBF, ISG Research, McAfee, MHI, Microsoft, RightScale, SAS, Skyhigh, Supply Chain Insights, and Synergy Research.

Table 1	AWS Cost Calculation Example
Table 2	Percentage of Companies Adopting at Least One Cloud Solution by Industry Sector 2013–2015
Table 3	Revenue Growth Attributed to Cloud Adoption
Table 4	Cloud Readiness Check Example (ISG)
Table 5	AWS Cloud Adoption Framework
Table 6	Respondents' Views on Which Cloud Services Gave the Best Economic Return
Table 7	Preferred Choice of Cloud Services Provider
Table 8	Main Choice Factor for Cloud Service Provider
Table 9	Market Comparison of Top 25 to 100 Vendors by Origin
Table 10	Estimated EU Market Shares of Top 25 Public Cloud Service Providers
Table 11	Key‐Value Data Store Example
Table 12	Document Data Model Example