Online MBA Management Theory Handbook
What is Supply Chain Analytics - IBM - https://www.ibm.com/supply-chain/supply-chain-analytics
What is a supply chain control tower?
A supply chain control tower is a connected, personalized dashboard of data, key business metrics and events across the supply chain. A supply chain control tower enables organizations to more fully understand, prioritize and resolve critical issues in real time. Supply chain control tower collects all data and utilizes supply chain analytics to present the data to decision makers in various formats and decision related levels.
Descriptive Analytics
Diagnostic Analytics
Predictive Analytics
Prescriptive Analytics
Descriptive Analytics
Using Descriptive Analytics to Improve Supply Chain Visibility for Variability, Velocity, Volume, and Variety.
Diagnostic Analytics
Supply Chain Diagnostic: A Four-Step Process.
Insights on performing a supply chain diagnostics and improving supply chain planning.
Predictive Analytics
What Is Predictive Analytics?
As its name implies, predictive analytics is about predicting future trends such as sales demand, exchange rates and other important supply chain metrics. The technique relies on the application of statistical modeling and regression analysis to historical data to determine and understand trends and formulate future trends.
Supply Chain Predictive Analytics: What Is It and Who's Doing It?
Prescriptive Analytics
Prescriptive analytics: For supply chain planning processes that need recommendations for more efficient and data-based decision-making, prescriptive analytics is recommended. It can employ techniques like AI and machine learning. An example is a business that wants advice on a possible outcome and what suggested actions they should take.
Using Prescriptive Analytics for Supply Chain Planning
A smarter control tower should provide end-to-end visibility across the supply chain — particularly into unforeseen external events.
Supply chain executives are under enormous pressure to provide customers what they need — when and where they need it — while also optimizing supply operations and achieving cost-saving goals. This is especially challenging in times of unpredictable yet inevitable vulnerabilities and disruptions.
Types of supply chain control towers
Logistics/transportation control towers
Logistics/transportation control towers offer advance shipping notifications, delivery data and track-and-trace information — and visibility into inbound and outbound logistics.
Fulfillment control towers
Fulfillment control towers specialize in assisting package shipments, and are designed to help expedite orders while reducing the overall cost-to-serve.
Inventory control towers
Inventory control towers enable real-time insights into inventory management, with special emphasis on preventing inventory stock-outs and shortages.
Supply assurance control towers
Supply assurance control towers ensure there’s an adequate supply available, that more supply is planned for delivery, and other matters related to supply.
E2E supply chain control towers
E2E supply chain control towers are engineered to provide visibility across internal and external systems and processes, with applications for various departments or entities.
What is Supply Chain Analytics - McKinsey - https://www.mckinsey.com/business-functions/operations/our-insights/big-data-and-the-supply-chain-the-big-supply-chain-analytics-landscape-part-1
Supply Chain Analytics - Video Lectures - NPTEL
A good comprehensive essay
Big Data Analytics and Its Applications in Supply Chain Management
Deloitte on Supply Chain Analytics
Like in various others parts of business, analytics which is a combination of statistics and data processing power of computers has enabled the processing of supply chain related data to point out cost reduction or profit improving niches.
Deloitte consultants pointed out the following.
Parametric pricing: The new parts a manufacturer procures differ only in small, specific ways from earlier versions in number of cases. A company with good parametric price modeling ability can identify these parameters of change in new parts and use them to determine what the net price change should be. That expedites the negotiating process and helps a company avoid overpayment.
Commodities price volatility: Raw materials fluctuate in price and makes business planning difficult. Unexpected price jumps can damage margin. Companies can use analytics to develop macroeconomic models and come out with better predictions – and use options, futures and contract provisions to hedge.
M&A integration: When the merger is between two companies in the same industry, they may be using the same parts/materials in their operations, but may have different material numbers and most likely different purchasing prices. After merger, such parts can be identified using analytics so that buyers can rationalize their procurement and save money.
https://www2.deloitte.com/us/en/pages/operations/articles/supply-chain-analytics-how-hard-should-you-squeeze.htmlhttps://www2.deloitte.com/tw/en/pages/deloitte-analytics/solutions/process.html
2021
Supply Chain 4.0: Improving Supply Chains with Analytics and Industry 4.0 Technologies
Emel Aktas, Michael Bourlakis, Ioannis Minis, Vasileios Zeimpekis
Kogan Page Publishers, 03-Feb-2021 - Business & Economics - 312 pages
Supply Chain 4.0 has introduced automation into logistics and supply chain processes, exploiting predictive analytics to better match supply with demand, optimizing operations and using the latest technologies for the last mile delivery such as drones and autonomous robots.
Supply Chain 4.0 presents new methods, techniques, and information systems that support the coordination and optimization of logistics processes, reduction of operational costs as well as the emergence of entirely new services and business processes.
This edited collection includes contributions from leading international researchers from academia and industry. It considers the latest technologies and operational research methods available to support smart, integrated, and sustainable logistics practices focusing on automation, big data, Internet of Things, and decision support systems for transportation and logistics. It also highlights market requirements and includes case studies of cutting-edge applications from innovators in the logistics industry.
https://books.google.co.in/books?id=gXgWEAAAQBAJ
SIX TRENDS THAT WILL IMPACT PROCUREMENT IN THE DIGITAL AGE
September 9, 2019 Kumar Singh
https://supplychainanalytics.guru/2019/09/09/six-trends-that-will-impact-procurement-in-the-digital-age/
“Without the right tech investment, you aren’t optimized and you aren’t synchronized.”
Domo’s approach, is that organizations need to link supply and demand in order to understand the customer in the middle and ensure transparent reporting throughout.
2013
In 2013 the Journal of Business Logistics published a white paper calling for research into the possible applications of Big Data within supply chain management. Since then, significant steps have been taken.
https://www.forbes.com/sites/bernardmarr/2016/04/22/how-big-data-and-analytics-are-transforming-supply-chain-management/#cf32d3b39ad2
Predicting demand accurately in volatile conditions requires sophisticated math based forecasting that can include downstream consumption data such as point-of-sales data, and model the impact of sales promotions, price, and other factors on demand. Analytics provides the capability.
SAS identified the follow levels of analytics.
8 LEVELS OF ANALYTICS
Level 1: Standard reports
Level 2: Ad hoc reports
Level 3: Query drilldown (or OLAP)
Level 4: Alerts
Level 5: Statistical analysis
Level 6: Forecasting
Level 7: Predictive modeling
Level 8: Optimization
When a company’s supply-chain management is fueled with data-driven insights, it is more effective at controlling costs, thereby protecting profits.
SAS emphasizes:
1. Efficiency and performance gains require predictive, data-driven insights.
2. Analytics are the wave of the future for next-generation supply-chains.
SAS Case Study STEEL MANUFACTURER IMPROVES PERFORMANCE, PROFITABILITY
A large, Asian manufacturer of steel (19,000 employees working to produce 28.5 million tons of steel annually), provided analytics support to two of its process innovation (PI) programs using sas’s software. the PI programs had a goal of updating 30-year-old business practices to improve efficiency and competitiveness. First, the company used sas to extract, transfer, and transform its ERP and legacy data into a data warehouse. secondly, the company combined sas’s analysis capabilities with its six sigma Project tracking system. this combination allows managers to gather data on PI
projects, identify most-critical quality issues, and analyze them for root causes. By enabling daily and monthly monitoring, the company can resolve issues early on and improve overall manufacturing processes with the first PI phase, the company achieved a 50 percent reduction in lead times for standard hot coil production (from 30 days to 14 days), and a 60 percent reduction in inventory (from 1 million tons to 400,000 tons).
Further, by analyzing and then making necessary improvements to the manufacturing process, the company was able to reduce the scrap ratio on hot coil from 15 percent to 1.5 percent, leading to additional savings and resulting in a total ROI of over $15.5 million in less than two years.
Source: IW/SAS Supply-Chain Analytics Survey. Email survey: Between June 8 and June 15, 2010,
Penton Research e-mailed invitations to participate in an online survey to 37,629 IndustryWeek print subscribers. By June 30, 2010, Penton Research received 398 responses, a 1.1 percent response rate. Of those, 210 respondents that were involved in their companies’ supply-chain operations were considered qualified to answer the questions.
http://www.wipro.com/services/analytics/services/supply-chain-analytics/
https://www.forbes.com/sites/bernardmarr/2016/04/22/how-big-data-and-analytics-are-transforming-supply-chain-management/
Updated on8.8.2023, 20 July 2021, 9 September 2019, 14 April 2017.
2019
SIX TRENDS THAT WILL IMPACT PROCUREMENT IN THE DIGITAL AGE
September 9, 2019 Kumar Singh
https://supplychainanalytics.guru/2019/09/09/six-trends-that-will-impact-procurement-in-the-digital-age/
“Without the right tech investment, you aren’t optimized and you aren’t synchronized.”
Domo’s approach, is that organizations need to link supply and demand in order to understand the customer in the middle and ensure transparent reporting throughout.
Synchronizing the two creates collaboration, and collaboration starts with data. Domo offers a variety of simple, intuitive ways to get the right data to the right people, from live data dashboards with predictive alerts to internal reports delivered across the organization. Colgate-Palmolive’s Ann Tracy argued that collaboration is needed to study, analyze and apply data analysis. Data needs to be accessible across each function of the business—from senior leaders on down to more junior staff—and ultimately add value for the end user.
https://www.domo.com/blog/gartner-scc-diary-part-3-people-data-and-systems-arent-sustainable-without-each-other/2013
In 2013 the Journal of Business Logistics published a white paper calling for research into the possible applications of Big Data within supply chain management. Since then, significant steps have been taken.
https://www.forbes.com/sites/bernardmarr/2016/04/22/how-big-data-and-analytics-are-transforming-supply-chain-management/#cf32d3b39ad2
IWCR SAS Report on Supply Chain Analytics in 2010
Predicting demand accurately in volatile conditions requires sophisticated math based forecasting that can include downstream consumption data such as point-of-sales data, and model the impact of sales promotions, price, and other factors on demand. Analytics provides the capability.
SAS identified the follow levels of analytics.
8 LEVELS OF ANALYTICS
Level 1: Standard reports
Level 2: Ad hoc reports
Level 3: Query drilldown (or OLAP)
Level 4: Alerts
Level 5: Statistical analysis
Level 6: Forecasting
Level 7: Predictive modeling
Level 8: Optimization
When a company’s supply-chain management is fueled with data-driven insights, it is more effective at controlling costs, thereby protecting profits.
SAS emphasizes:
1. Efficiency and performance gains require predictive, data-driven insights.
2. Analytics are the wave of the future for next-generation supply-chains.
SAS Case Study STEEL MANUFACTURER IMPROVES PERFORMANCE, PROFITABILITY
A large, Asian manufacturer of steel (19,000 employees working to produce 28.5 million tons of steel annually), provided analytics support to two of its process innovation (PI) programs using sas’s software. the PI programs had a goal of updating 30-year-old business practices to improve efficiency and competitiveness. First, the company used sas to extract, transfer, and transform its ERP and legacy data into a data warehouse. secondly, the company combined sas’s analysis capabilities with its six sigma Project tracking system. this combination allows managers to gather data on PI
projects, identify most-critical quality issues, and analyze them for root causes. By enabling daily and monthly monitoring, the company can resolve issues early on and improve overall manufacturing processes with the first PI phase, the company achieved a 50 percent reduction in lead times for standard hot coil production (from 30 days to 14 days), and a 60 percent reduction in inventory (from 1 million tons to 400,000 tons).
Further, by analyzing and then making necessary improvements to the manufacturing process, the company was able to reduce the scrap ratio on hot coil from 15 percent to 1.5 percent, leading to additional savings and resulting in a total ROI of over $15.5 million in less than two years.
Source: IW/SAS Supply-Chain Analytics Survey. Email survey: Between June 8 and June 15, 2010,
Penton Research e-mailed invitations to participate in an online survey to 37,629 IndustryWeek print subscribers. By June 30, 2010, Penton Research received 398 responses, a 1.1 percent response rate. Of those, 210 respondents that were involved in their companies’ supply-chain operations were considered qualified to answer the questions.
http://www.wipro.com/services/analytics/services/supply-chain-analytics/
https://www.forbes.com/sites/bernardmarr/2016/04/22/how-big-data-and-analytics-are-transforming-supply-chain-management/
Supply Chain Analytics - Google Books
Supply Chain Analytics and Modelling: Quantitative Tools and Applications
Nicoleta Tipi · 2021
Supply Chain Analytics and Modelling presents a range of business analytics models used within the supply chain to help readers develop knowledge on a variety of topics to overcome common issues.
Supply Chain Analytics: Using Data to Optimise Supply Chain Processes
Peter W. Robertson · 2021
By describing the key supply chain processes through worked examples, and the descriptive, predictive and prescriptive analytic methods that can be applied to bring about improvements to those processes, the book presents a more comprehensive learning experience for the reader than has been offered previously.
Essentials of Business Analytics: An Introduction to the
Bhimasankaram Pochiraju, Sridhar Seshadri · 2019
This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners.
Logistics, Supply Chain and Financial Predictive Analytics:
Kusum Deep, Madhu Jain, Said Salhi · 2018
This book addresses a broad range of problems commonly encountered in the fields of financial analysis, logistics and supply chain management, such as the use of big data analytics in the banking sector.
Supply Chain Management in the Big Data Era -
Chan, Hing Kai, Subramanian, Nachiappan, Abdulrahman, Muhammad Dan-Asabe · 2016
Highlighting emerging strategies from different industry perspectives, this book is ideally designed for managers, professionals, practitioners, and students interested in the most recent research on supply chain innovations.
https://books.google.co.in/books?id=aN52DQAAQBAJ
Big Data Driven Supply Chain Management: A Framework for ...books.google.co.in
Nada R. Sanders · 2014
Despite these opportunities, many supply chain operations are gaining limited or no value from Big Data. In Big Data Driven Supply Chain Management, Nada Sanders presents a systematic five-step framework for using Big Data in supply chains.
Supply Chain Optimization through Segmentation and Analytics books.google.co.in
Gerhard J. Plenert · 2014
Then which planning and scheduling solution do you utilize? This book introduces the concept of segmentation as the planning and scheduling tool that facilitates the optimization of the supply chain.
Supply Chain Metrics that Matter books.google.co.in
Lora M. Cecere · 2014
Mistakes are hard to overcome. Supply Chain Metrics that Matter tells this story. The book links corporate financials to supply chain maturity. In the book, the author analyzes which metrics matter.
Encyclopedia of Business Analytics and Optimization books.google.co.in › books
Wang, John · 2014
Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.
Applied Predictive Analytics: Principles and Techniques for ...books.google.co.in › books
Dean Abbott · 2014
The ability to successfully apply predictive analytics enables businesses to effectively interpret big data; essential for competition today This guide teaches not only the principles of predictive analytics, but also how to apply them to ...
The Applied Business Analytics Casebook: Applications in ...books.google.co.in › books
Matthew J. Drake · 2013
The first collection of cases on “big data” analytics for supply chain, operations research, and operations management, this reference puts readers in the position of the analytics professional and decision-maker.
Networks Against Time: Supply Chain Analytics for Perishable ...books.google.co.in › books
Anna Nagurney, Min Yu, Amir H. Masoumi · 2013
This book can also be used by advanced undergraduate students and graduate students in the disciplines noted above to familiarize themselves with methodologies and supply chain network models and applications.
Supply Chain Network Design: Applying Optimization and ...books.google.co.in › books
Michael Watson, Sara Lewis, Peter Cacioppi · 2012
Using strategic supply chain network design, companies can achieve dramatic savings from their supply chains.
Global Business Analytics Models: Concepts and Applications ...books.google.com › books
Hokey Min · 2016
THE COMPLETE GUIDE TO USING ANALYTICS TO MANAGE RISK AND UNCERTAINTY IN COMPLEX GLOBAL BUSINESS ENVIRONMENTS Practical techniques for developing reliable, actionable intelligence–and using it to craft strategy Analytical opportunities to ...
Business Analytics: Progress On Applications In Asia Pacificbooks.google.co.in › books
Jorge L C Sanz · 2016
Business Analytics: Progress on Applications in Asia Pacific provides a useful picture of the maturity of the Business Analytics domain in Asia Pacific.
Big Data Analytics in Supply Chain Management: Theory and ...books.google.com › books
Iman Rahimi, Amir H. Gandomi, Simon James Fong · 2020
Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain ...
Handbook of Quantitative Supply Chain Analysis: Modeling in the E-Business Era
David Simchi-Levi, S. David Wu, Zuo-Jun (Max) Shen · 2004
The Handbook is a comprehensive research reference that is essential for anyone interested in conducting research in supply chain.
Towards Supply Chain Risk Analytics: Fundamentals, ... - Page ibooks.google.co.in › books
Iris Heckmann · 2016
– PAGE I
In this thesis, Iris Heckmann develops a profound conceptual basis of supply chain risk analytics.
Data Science for Business: What You Need to Know about Data ...books.google.co.in › books
Foster Provost, Tom Fawcett · 2013
This guide also helps you understand the many data-mining techniques in use today.
Modeling the Supply Chain books.google.co.in › books
Jeremy F. Shapiro · 2007 · No preview
The book also shows how competitive advantage in supply chain management can be most fully realized by developing and applying optimization modeling systems.
Logistics Management: An Analytics-Based Approachbooks.google.co.in › books
Tan Miller, Matthew J. Liberatore · 2020 · No preview
Data Strategy: How to Profit from a World of Big Data, ...books.google.co.in › books
Bernard Marr · 2017
Data is revolutionizing the way we work and it is the companies that view data as a strategic asset that will survive and thrive. Data Strategy is a must-have guide to creating a robust data strategy.
Big Data Analytics in Supply Chain Management: Theory and ...books.google.com › books
Iman Rahimi, Amir H. Gandomi, Simon James Fong · 2020
Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain ...
Industry 4.0 Data Analyticsbooks.google.co.in › books
Rajesh Agnihotri, Samuel New · 2016 · No preview
This book's comprehensive, one-of-a-kind coverage, journeys from the birth of digital data during Industries 3.0, to the latest practices, trends, and emerging developments in Industries 4.0.
Our Quick Notes On Supply Chain Analyticsbooks.google.com › books
Vivek Sood · 2020
Do not be deceived by their short nature - these notes are only 22 pages or so. But these are 22 pages of potent dynamite that will supercharge your thinking in the right direction.
Data Science for Supply Chain Forecasting - Page ibooks.google.co.in › books
Nicolas Vandeput · 2021
– PAGE I
This second edition adds more than 45 percent extra content with four new chapters including an introduction to neural networks and the forecast value added framework.
Supply Chain Optimization, Design, and Management: Advances ...books.google.co.in › books
Minis, Ioannis, Zeimpekis, Vasileios, Dounias, Georgios · 2010
Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods presents computational intelligence methods for addressing supply chain issues.
No image available
Supply chain analyticsbooks.google.com › books
3G E-learning LLC, USA · 2017 · No preview
Behind Every Good Decision: How Anyone Can Use Business ...books.google.co.in › books
Piyanka Jain, Puneet Sharma · 2014
Readers will learn how to:• Clarify the business question• Lay out a hypothesis-driven plan• Pull relevant data• Convert it to insights• Make decisions that make an impactPacked with examples and exercises, this refreshingly ...
Inventory Optimization: Models and Simulationsbooks.google.co.in › books
Nicolas Vandeput · 2020
In this book . . . Nicolas Vandeput hacks his way through the maze of quantitative supply chain optimizations. This book illustrates how the quantitative optimization of 21st century supply chains should be crafted and executed. . .
Creating Value with Big Data Analytics: Making Smarter ...books.google.co.in › books
Peter C. Verhoef, Edwin Kooge, Natasha Walk · 2016
This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics.
Supply Chain Analytics - Simple Steps to Win, Insights and ...books.google.com › books
Gerard Blokdijk · 2015 · No preview
The job can be accomplished by having a roadmap and experiences from previous Supply Chain Analytics changes. This is where this book is your guide and roadmap.
Supply Chain Analytics Data a Complete Guide - 2020 Editionbooks.google.com › books
Gerardus Blokdyk · 2019 · No preview
You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in.
Analysis and Algorithms for Service Parts Supply Chainsbooks.google.co.in › books
John A. Muckstadt · 2004
This book provides a broad overview of modeling approaches and solution methodologies for addressing service parts inventory problems found in high-powered technology and aerospace applications.
Supply Chain Planning and Analytics: The Right Product in ...books.google.com › books
Gerald Feigin · 2011 · No preview
This book smartly focuses on the three interlinked processes that compose effective supply chain planning: demand planning, sales and operations planning, and inventory and supply planning.
Supply Chain 4.0: Improving Supply Chains with Analytics and ...books.google.com › books
Emel Aktas, Vasileios Zeimpekis, Michael Bourlakis · 2021 · No preview
This edited book considers the latest technologies and operational research methods available to support smart, integrated, and sustainable logistics practices focusing on automation, big data, Internet of Things, autonomous vehicles and ...
No image available
The Effect of Supply Chain Analytics on Business Decision-makingbooks.google.com › books
2020 · No preview
Supply chain analytics -- Decision-making -- Data-driven decisions -- Supply chain management -- Big data -- Big data analytics.
Inventory Analytics: Prescriptive Analytics in Supply Chainsbooks.google.com › books
Horst Tempelmeier · 2020
The book has been written for students of Supply Chain Management and Operations Management as well as for practitioners who are confronted with inventory management in their daily work.
Supply Chain Analytics Complete Self-Assessment Guidebooks.google.com › books
Gerardus Blokdyk · 2017 · No preview
This book is for managers, advisors, consultants, specialists, professionals and anyone interested in Supply Chain Analytics assessment.
Supply Chain Analyticsbooks.google.com › books
Aegli Marathefti · 2011 · No preview
Supply Chain Analytics Complete Self-Assessment Guidebooks.google.com › books
Gerardus Blokdyk · 2017 · No preview
This book is for managers, advisors, consultants, specialists, professionals and anyone interested in Supply Chain Analytics assessment.
Managing Supply Chain Analytics - Guiding Organizations to ...books.google.com › books
Tino T. Herden · 2020 · No preview
Advanced Analytics for Green and Sustainable Economic ...books.google.co.in › books
Zongwei Luo · 2012 · No preview
"This book focuses on the development of innovative techniques and tools that answer urgent questions in the global trend of sustainable economic development, providing researchers and business managers with a valuable resource for the ...
Übungsbuch Supply Chain Analytics: Operations Management und ...books.google.com › books· Translate this page
Hans-Otto Günther, Horst Tempelmeier · 2020
Dieses Übungsbuch ergänzt das von denselben Autoren verfaßte Lehrbuch "Supply Chain Analytics - Operations Management und Logistik".
Operations Rules: Delivering Customer Value through Flexible ...books.google.co.in › books
David Simchi-Levi · 2010
In Operations Rules, David Simchi-Levi identifies the crucial element in a company's success: the link between the value it provides its customers and its operations strategies.
Artificial Intelligence. An International Perspective: An ...books.google.co.in › books
Max Bramer · 2009
Artificial Intelligence (AI) is a rapidly growing inter-disciplinary field with a long and distinguished history that involves many countries and considerably pre-dates the development of computers.
Data Science for Executives: Leveraging Machine Intelligence ...books.google.co.in › books
Nir Kaldero · 2018 · No preview
If you're ready to meet the challenges of this new revolution, this essential guide will help you take your business to the next level.
Supply Chain Analytics with SAP NetWeaver Business Warehousebooks.google.com › books
Amol Palekar · 2012 · No preview
Updated on8.8.2023, 20 July 2021, 9 September 2019, 14 April 2017.
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