Editor Note: Understanding the importance of this timely topic and to ensure that research is made available to the wider academic community, IGI Global has made a sample of related articles and chapters complimentary to access. View the end of this article to freely access this critical research.
As you know, when you order products online, or shop for necessities, you may notice longer wait times, the rising costs of meat and eggs at the grocery store, increased prices on raw materials, as well as news reports on the challenges of distributing the Covid-19 vaccine. The Covid-19 shutdowns and limitations have disrupted suppliers, the availability of raw materials, and specialized workforces: thus affecting businesses, supply chains, and their ability to provide goods and services. According to a report commissioned by The Association for Supply Chain Management (ASCM), USA, 50% of publicly-listed retail, pharmaceuticals, and consumer electronic companies reported that they do not have a clean end-to-end picture of their supply chains, showcasing the serve limitation of businesses being able to implement emergency protocols.
Additionally, Mr. Andrew DiEugenio, General Transportation Manager at Walmart, mentions how the pandemic affected typical consumer shopping practices, which in turn required adjustments to distribution schedule causing further modification to businesses’ supply chains and management.
In response to these challenges and changes, businesses are implementing AI and automation and outsourcing their supply chains. Additionally, international governments are passing legislation that mandates industries to review their supply chains to produce a longer-term plan to prevent future supply-chain issues. Understanding the current challenges and importance of supply chain management, Prof. Nenad Stefanovic, from the University of Kragujevac, Serbia, explains how big data can be implemented in strengthening supply chain management in his chapter, “Big Data Analytics in Supply Chain Management” sourced from the Encyclopedia of Organizational Knowledge, Administration, and Technology (IGI Global).
BIG DATA AND SUPPLY CHAIN MANAGEMENT
Big data analytics uncovers patterns in a wide variety of data and associates the patterns with business outcomes. Analysts use analytical techniques and tools to detect unusual, interesting, previously unknown, or new patterns in data. Big data is a result of interaction of four dimensions of scale (increasing data volumes, high velocity of data creation, increasing complexity of data types, and extreme time sensitivity of data diminishing its value if not treated at that moment) thereby posing different challenges to manage, not to mention applying analytics techniques to find new insights. Big data does not behave the same as other data. The challenges associated with analytics on big data require a different approach from traditional data analytics processes (Nguyen et al., 2018). Big Data Analytics in Supply Chain Management 2448 Big data analytics has to do more with ideas, question and value, than with technology. Therefore, the big data analytics methodology is a combination of sequential execution of tasks in certain phases and highly iterative execution steps in certain phases.
The big data analytics process lifecycle is a combination of sequential execution of tasks in certain phases and highly iterative execution steps in certain phases. Because of the scale issue associated with supply chain big data system, an incremental and agile approach is recommended, which include modifying and expanding processes gradually across several activities as opposed to designing a system all at once (Mohanty, 2013).
In other words, Jefferson is explaining that the object of hate – enslaved Africans – must be controlled and restricted by exerting educational, political and economic prejudice and bigotry or else the fear is that the person who is hated will one day take over and destroy the one who hates. This reasoning might help explain why homegrown terrorism became an extension of the personal hatred, racial prejudice, and bigotry stoked by the fear of reprisals.
In this section, an agile, iterative big data analytical process model to deliver supply chain predictive analytics solutions and intelligent applications efficiently is presented. The complete process model should encompass the lifecycle (phases, tasks, and workflows), roles, infrastructure, tools, and artifacts produced.
The proposed model is comprised of the following key components:
- A big data lifecycle.
- A standardized project structure.
- Infrastructure and resources for big data projects.
- Tools and utilities for project execution.
Figure 1 shows a proposed analytical lifecycle that can used to structure and execute various big data analytics projects (Ericson et al., 2017).
The lifecycle outlines the steps, from start to finish, that projects usually follow when they are executed. The process model includes the following stages that analytical projects typically execute, often iteratively:
- Business understanding
- Data acquisition and understanding
- Modeling
- Deployment
- Customer acceptance
The lifecycle defines goals, tasks, and documentation artifacts for each stage of the lifecycle. These tasks and artifacts are associated with project roles such as: project manager, solution architect, data scientist, project lead, IT manager, business analyst, DevOps specialist, application developer, tester, etc.
The goal of the business understanding phase is to specify the key variables that are to serve as the model targets and whose related metrics are used determine the success of the project, and to identify the relevant data sources that the supply chain has access to or needs to obtain.
The second phase includes the three main tasks:
- Data ingestion from various supply chain data sources into the target analytic environment.
- Data exploration in order to determine if the data quality is adequate to answer the question.
- Solution architecture development of the data pipeline that refreshes and scores the data regularly.
The modeling phase addresses the following tasks:
- Feature engineering - Create data features from the raw data to facilitate model training.
- Model training - Find the model that answers the question most accurately by comparing their success metrics.
- Model evaluation - Determine if the model is suitable for production.
Deployment phase refers to deploying the models with a data pipeline to a production or productionlike environment for final user acceptance and application usage. The final phase includes system validation (confirming that the deployed model and pipeline meet the customer’s needs) and project delivery (hand the project off to the entity that’s going to run the system in production.
The model also includes the standardized project structure so that projects share a common directory structure and use templates for project documents. This makes it easy for the team members to find information about their projects. All code and documents are stored in a version control system to enable more effective and efficient team collaboration. Tracking tasks and features in an agile project tracking system allows closer tracking of the code for individual features. The standardized structure for all projects helps build institutional knowledge across the supply chain.
Interested in Reading the Rest of the Chapter? Access the Full Article Through IGI Global’s InfoSci-Demo Account, here.
Understanding the need for research around this topic, this research is featured in the publication, the Encyclopedia of Organizational Knowledge, Administration, and Technology (IGI Global). This Encyclopedia is a five-volume publication that offers over 190+ previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations.
It is currently available in print and electronic format (ISBN: 9781799834731; EISBN: 9781799834748) through IGI Global’s Online Bookstore at a 20% discount. Additionally, to ensure that the research community can easily and affordably access this content, this publication and all IGI Global titles are available on the individual article and chapter level (pay-per-view) for US$ 37.50 through IGI Global's InfoSci-Ondemand. Recommend this publication and view all of the chapters featured in this title on the book webpage . Additionally, this research and IGI Global’s full list of related titles is featured in the InfoSci-Books database. Request a free trial or recommend the InfoSci-Books database to your library to have access to this critical research.
Complimentary Research Articles and Chapters on Health Care Reform and Diversity:In response to the timeliness and importance of this topic, we have made all of the below articles and chapters complimentary to access. As such, please feel free to integrate these resources into your research and share them across your network. - “Defense Supply Chain Operations: Analytical Architectures for Enterprise Transformation”
Prof. Greg H. Parlier (North Carolina State University, USA & G. H. Parlier Consulting, USA) Copyright: © 2019 | Pages: 24
- “An Exploratory Study on Blockchain Application in a Food Processing Supply Chain to Reduce Waste”
Profs. Emily Anne Carey (Samsung Electronics, UK) et al. Copyright: © 2019 |Pages: 25
- “Blockchain for Supply Chain Management: Opportunities, Technologies, and Applications”
Prof. Nenad Stefanovic (Faculty of Technical Sciences Cacak, University of Kragujevac, Serbia) Copyright: © 2021 |Pages: 16
- “Improving Opportunities in Healthcare Supply Chain Processes via the Internet of Things and Blockchain Technology"
Profs. Raja Jayaraman (Khalifa University of Science and Technology, Department of Industrial and Systems Engineering, Abu Dhabi, UAE) et al. Copyright: © 2019 |Pages: 17
View All Chapters and Articles on This Topic The “View All Chapters and Articles on This Topic” navigates to IGI Global’s InfoSci-Demo Account, which provides a sample of the IGI Global content available through IGI Global’s InfoSci-Books (6,000+ e-books) and InfoSci-Journals (140+ e-journals) databases. If interested in having full access to this peer-reviewed research content, recommend these valuable research tools to your library. For Journalists Interested in Additional Trending Research: Contact IGI Global’s Marketing Team at marketing@igi-global.com or 717-533-8845 ext. 100 to access additional peer-reviewed resources to integrate into your latest news stories. | Interested in Affordably Acquiring These Chapters and Related Research?Purchase Individual Chapters and Journal Articles Through IGI Global's InfoSci-OnDemand for US$ 37.50 Each
|
Featured Publications Surrounding This Topic:
Receive a 20% discount on all titles and free shipping on orders over US$ 295* when you order directly through IGI GLobal's Online Bookstore. Additionally, benefit from instant, multi-user access with no DRM, perpetual access with PDF Download Options, and no hosting, archiving, or maintenance fees on all electronic titles.
|
| | Technology Optimization and Change Management for Successful Digital Supply ChainsProf. Ehap Sabri (KPMG LLP, USA & University of Texas at Dallas, USA)
Copyright: 2019 | Pages: 323 | ISBN: 9781522577003 | EISBN: 9781522577010
This title is a pivotal reference source that provides vital research on the application of digital business transformation programs to improve strategic, tactical, and operational supply chain processes. While highlighting topics such as maturity models, predictive analysis, and communication planning, this publication explores the limited literature in the field of digital supply chain optimization and business transformation, and complements it with practical and proven tactics from the industry. |
| |
|
|
| | Research Anthology on Supply Chain and Logistics Management: Concepts, Methodologies, Tools, and Applications (4 Volumes) Information Resources Management Association (USA)
Copyright: 2020 | Pages: 2,148 | ISBN: 9781799809456 | EISBN: 9781799809463
This 4-volume Research Anthology is a vital reference source of 100+ chapters on the effective management of risk factors and the implementation of the latest supply management strategies. It also explores the field of digital supply chain optimization and business transformation. This text covers a range of timely topics such as inventory management, competitive advantage, and transport management. |
| |
|
| | Handbook of Research on Interdisciplinary Approaches to Decision Making for Sustainable Supply Chains Profs. Anjali Awasthi (Concordia University, Canada) and Katarzyna Grzybowska (Poznan University of Technology, Poland)
Copyright: 2020 | Pages: 674 | ISBN: 9781522595700 | EISBN: 9781522595724
This title provides interdisciplinary approaches to sustainable supply chain management through the optimization of system performance and development of new policies, design networks, and effective reverse logistics practices, and features research on topics such as industrial symbiosis, green collaboration, and clean transportation. |
| |
|
| | Digitalization of Decentralized Supply Chains During Global Crises Prof. Atour Taghipour (Normandy University, France)
Copyright: 2021 | Pages: 330 | ISBN: 9781799868743 | EISBN: 9781799868767
This title provides new approaches of digitalization of decentralized supply chains and industries to help researchers, educators, consultants, and practitioners deal with global crises and improve the global performance of supply chains. Important topics covered include blockchain, internet of things, 3D technologies, and Industry 4.0 technologies within the context of digital supply chains. |
| |
|
| | Demand Forecasting and Order Planning in Supply Chains and Humanitarian Logistics Prof. Atour Taghipour (Normandy University, France)
Copyright: 2021 | Pages: 313 | ISBN: 9781799838050 | EISBN: 9781799838067
This title is a collection of innovative research that focuses on demand anticipation, forecasting, and order planning as well as humanitarian logistics to propose original solutions for existing problems, and highlights topics including artificial intelligence, information sharing, and operations management. |
| |
|
Disclaimer: The opinions expressed in this article are the author’s own and do not reflect the views of IGI Global.
About IGI Global: Founded in 1988, IGI Global, an international academic publisher, is committed to producing the highest quality research (as an active full member of the Committee on Publication Ethics “COPE”) and ensuring the timely dissemination of innovative research findings through an expeditious and technologically advanced publishing process. Through their commitment to supporting the research community ahead of profitability, and taking a chance on virtually untapped topic coverage, IGI Global has been able to collaborate with over 100,000+ researchers from some of the most prominent research institutions around the world to publish the most emerging, peer-reviewed research across 350+ topics in 11 subject areas including business, computer science, education, engineering, social sciences, and more. To learn more about IGI Global, click here.
*20% discount is only available through IGI Global’s online bookstore and is not intended for booksellers or wholesalers. Free shipping will be automatically applied to shopping cart orders over US$ 295.00 or more before tax, which can include a combination of print and non-shippable products (i.e. e-book, e-journals, and articles/chapters). It is only available when you order directly through IGI Global’s Online Bookstore and is only valid on standard U.S. and international shipping. There will be additional charges for express shipping and limitations may apply.
Newsroom Contact
Caroline Campbell
Assistant Director of Marketing and Sales
ccampbell@igi-global.com
(717) 533-8845, ext. 144
www.igi-global.com/