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This thesis, through a thorough literature and content review, discusses the various ways that data analytics and supply chain management intersect. Both fields have been around for a while, but are incredibly aided by the information age we live in today. Today's ERP systems and supply chain software packages use

This thesis, through a thorough literature and content review, discusses the various ways that data analytics and supply chain management intersect. Both fields have been around for a while, but are incredibly aided by the information age we live in today. Today's ERP systems and supply chain software packages use advanced analytic techniques and algorithms to optimize every aspect of supply chain management. This includes aspects like inventory optimization, portfolio management, network design, production scheduling, fleet planning, supplier evaluation, and others. The benefit of these analytic techniques is a reduction in costs as well as an improvement in overall supply chain performance and efficiencies. The paper begins with a short historical context on business analytics and optimization then moves on to the impact and application of analytics in the supply chain today. Following that the implications of big data are explored, along with how a company might begin to take advantage of big data and what challenges a firm may face along the way. The current tools used by supply chain professionals are then discussed. There is then a section on the most up and coming technologies; the internet of things, blockchain technology, additive manufacturing (3D printing), and machine learning; and how those technologies may further enable the successful use of analytics to improve supply chain management. Companies that do take advantage of analytics in their supply chains are sure to maintain a competitive advantage over those firms that fail to do so.
ContributorsCotton, Ryan Aaron (Author) / Taylor, Todd (Thesis director) / Arora, Hina (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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As a Marketing and Business Data Analytics student, it has become increasingly apparent through coursework and professional experiences that the landscape of e-commerce and data-driven marketing is changing. Many companies flounder and are barely keeping up with the fast-developing world of e-commerce, while others are thriving and becoming “E-Commerce Giants”.

As a Marketing and Business Data Analytics student, it has become increasingly apparent through coursework and professional experiences that the landscape of e-commerce and data-driven marketing is changing. Many companies flounder and are barely keeping up with the fast-developing world of e-commerce, while others are thriving and becoming “E-Commerce Giants”. What do they do that make them successful?
Through research from case studies and professional interviews, it can be shown that those who fail and become victim to the e-commerce giants are those who do not allocate enough budget and resources to allow e-commerce to succeed; they do not correctly utilize data throughout the creation of their e-commerce site nor their marketing, have a vast lack of knowledge, and ultimately do not adapt to trends in e-commerce.
E-commerce giants are those who lead in the world-wide e-commerce revolution. They have entered a market and have caused/are continuing to cause instability for those who have not adapted or changed. These e-commerce giants do not have to be “giant” in size; rather, they are making giant changes that allow them to be successful within the industry. They are the prime examples of how e-commerce and data-driven marketing can be successful.
My research shows in order to successfully practice e-commerce, companies must adapt the best practices shown by these giants: owning your data, developing a strong budget for data-driven marketing, investing in the technology and people needed to implement a sound strategy, training employees in basic data, utilizing data in all aspects of marketing, creating an easy online experience that using AB Testing, hosting post mortem meetings to identify successes and failures, understanding your customers, creating the appropriate customer segmentation, nixing the “one fits all” strategy, and never getting too comfortable. If a company is stagnant, they are behind.
ContributorsSirois, Natalie Rose (Author) / Giles, Charles (Thesis director) / Fette, Donald (Committee member) / Department of Marketing (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05