Unlocking the Hidden, Data-Driven Potential of the Supply Chain
Stefan Asenkerschbaumer ()
Additional contact information
Stefan Asenkerschbaumer: Robert Bosch GmbH
A chapter in Digital Business Models in Industrial Ecosystems, 2021, pp 35-46 from Springer
Abstract:
Abstract Even though a digitalized supply chain can be a veritable driver of performance, industry is still doing far too little to unlock the potential that is hidden in a data-driven supply chain. Yet for any company that seizes this opportunity and systematically exploits the wealth of supply-chain data, an enduring competitive advantage beckons. The game-changer is an end-to-end supply chain, based on standardization and data transparency, that permits largely automated, AI-assisted, and highly efficient planning processes. In this respect, supply-chain planning and production scheduling go hand in hand as building blocks of the factory of the future, whose operations are digitalized and highly flexible. There are four fundamental elements for achieving this: Leadership and associates—empowerment The design of end-to-end processes The use of digital interfaces to manage partners Data security Combining cross-company and company-internal digitalization projects can play a major part in making processes more robust, conserving resources, enhancing flexibility, and making the supply chain future-proof.
Date: 2021
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:fuobcp:978-3-030-82003-9_3
Ordering information: This item can be ordered from
http://www.springer.com/9783030820039
DOI: 10.1007/978-3-030-82003-9_3
Access Statistics for this chapter
More chapters in Future of Business and Finance from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().