Global supply shortages in 2020 and 2021 have highlighted the fragility of some supply chains, causing large scale stoppages and the inability to deliver vehicles as ordered. Improved visibility across the inbound supply chain and production is a daunting task – but will feed transformative risk management capabilities and minimize the financial impact of disruptions.
The efficiency of a mass-market production line must be transformed to deliver mass-customized products, on multiple drive trains, and without adding back the costs or inefficiencies so effectively squeezed out over decades of progress.
Automotive companies must find the right balance between agility, resilience, quality, service, and cost in today’s dynamic market. Supply chains have been traditionally split into silos for ease of management. It is simply too hard for human-oriented processes to manage the complexity and scale of end-to-end, granular supply chains. But this creates gaps in data, information, and visibility between silos.
A new, connected model is needed to compete in today’s digital economy. A digital fabric that connects data from disparate processes, to create a complete and accurate picture across the entire enterprise. Many are looking to machine learning and AI as the silver bullet to build and retain competitive advantage. But the truth is that automotive businesses must first create the right context and data environment for these technologies to deliver the intended business value.
In order to capitalize on flexible manufacturing by providing visibility over parts and component manufacturing, inbound and outbound logistics, and the next generation of connected factories to minimize risk and improve productivity, it is essential that you create a holistic 360° view and strategy of your data from development and manufacturing to sales and customer service.
In this brochure, we give you ideas on how to utilize data in manufacturing to win the race for the car of the future.