scholarly journals LANL’s Digital Supply Chain Transformation with Ariba

2021 ◽  
Author(s):  
Christine Hipp
Keyword(s):  
Supply Chain ◽  
Chain Transformation

Mastering Change Management for Successful Supply Chain Transformation

2017 ◽  
pp. 841-873
Author(s):  
Ehap Sabri ◽  
Likhit Verma
Keyword(s):  
Supply Chain ◽  
Best Practices ◽  
Change Management ◽  
Customer Demand ◽  
Business Transformation ◽  
Chain Processes ◽  
Survival And Growth ◽  
Chain Transformation ◽  
Chain Business

Supply chain transformation is necessary for the survival and growth of an organization; the more effective the transformation, the more likely the company is to thrive. In response to the dramatic changes in the business landscape over the last few years, many companies are launching business transformation programs to drive sweeping changes in their supply chain processes. These transformations are required to match the ever-growing customer demand and drive competition in the market. The supply chain transformation can be evident in exploring new sourcing networks, establishing collaborative forecasting processes, optimizing networks and inventories, reducing supply chain complexities, improving margins, etc. In today's world, it is no longer an option whether or not to opt for supply chain business transformations. Instead, it is a strategic mandate in order to stay relevant in the industry. This chapter provides the analysis of the most common transformation failures and suggests a practical framework leveraging some of the best practices in change management.

Big Data Analytics Driven Supply Chain Transformation

2019 ◽  
pp. 106-124 ◽  
Author(s):  
Mondher Feki
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Future Research ◽  
Research Directions ◽  
Digital Platforms ◽  
New Frontier ◽  
Future Research Directions ◽  
Chain Transformation

Big data has emerged as the new frontier in supply chain management; however, few firms know how to embrace big data and capitalize on its value. The non-stop production of massive amounts of data on various digital platforms has prompted academics and practitioners to focus on the data economy. Companies must rethink how to harness big data and take full advantage of its possibilities. Big data analytics can help them in giving valuable insights. This chapter provides an overview of big data analytics use in the supply chain field and underlines its potential role in the supply chain transformation. The results show that big data analytics techniques can be categorized into three types: descriptive, predictive, and prescriptive. These techniques influence supply chain processes and create business value. This study sets out future research directions.

scholarly journals Driving Supply Chain Transformation Through a Business Process Oriented Approach

2010 ◽  
Vol 2 (4) ◽  
pp. 298-314 ◽  
Author(s):  
Changrui Ren ◽  
Miao He ◽  
Qinhua Wang ◽  
Bing Shao ◽  
Jin Dong
Keyword(s):  
Supply Chain ◽  
Business Process ◽  
Process Oriented ◽  
Chain Transformation ◽  
Oriented Approach

Case Study: Supply Chain Transformation in the Mercy Health System

2018 ◽  
Vol 21 (3) ◽  
pp. 28-33 ◽  
Author(s):  
Anne Snowdon ◽  
Betty Rocchio
Keyword(s):  
Supply Chain ◽  
Health System ◽  
Chain Transformation
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