As artificial intelligence becomes more common, the automotive industry will experience significant changes in terms of production and supply chain management.
There are a number of key traits supply chain planners and managers must exemplify in order to successfully administer and oversee complex supply networks.
A truly digitized supply chain combines technological innovation, strategy, and a rethinking of traditional methods of supply chain management.
The real value proposition in global supply chain logistic comes from integrating S&OE and S&OP into a unified platform rather than relying on each separately.
Today's manufacturing companies must understand a number of important factors that can derail their supply chain in order to address and combat disruptions.
The global manufacturing supply chain has experienced a number of significant developments and advancements during the last 10 years.
S&OE (sales and operations execution) is one strategy too many manufacturing companies deploy via the spreadsheet and can significantly hamper their operations.
Despite the debate, Big Data remains a powerful tool for manufacturing companies to increase the accuracy of their planning and production cycles.
There's much misinformation about how Industry 4.0 came to be and how companies can deploy Industry 4.0 as a core driver of modernized, intelligent production.
Digitization of the supply chain is critical for driving long-term, sustainable growth in terms of revenue, footprint, and development of internal processes.
Digitization helps companies function more efficiently and effectively by providing the responsiveness and agility necessary to avoid breakdowns in production.
Real-time insight into the supply pipeline via intelligent solutions can be the saving grace for companies in leveraging efficiency and productivity.
S&OE is an extremely important value proposition for manufacturing companies in reducing costs associated with their supply chain management.
Advanced analytics is a critical value proposition in reducing operational costs in a network with operations at various disparate points across the globe.
Industry 4.0 provides companies with a wide net in terms of troubleshooting or reducing instances of risk across a number of different kinds or brands.
With the help of Big Data, Industry 4.0, and advanced analytics, machine learning is poised to chnage the way OEMs coordinate production processes.
Industry 4.0 is built upon the concepts of end-to-end visibility, agility, and efficiency across each touch point of the automotive value chain.
