Big data supply chains

Ninety percent of the world s data was generated in the last two years, and 80 percent of that data is nnstructured—presentations, e-mails, audio files, and video files—and will not fit neatly into transactional systems. The use of unstructured data for early market sensing could have prevented 60 percent of the major supply chain disruptions outlined in Chapter 1. In Kgure 6.10, we share an overview of the changes with big data supply chains. 

Big data supply chains and their impact on business will redefine supply chain applications, ft vdll enable sensing and predictive analytics that were previously only dreamed of by the early supply chain pioneers, ft will make traditional supply chain technologies obsolete, or legacy, applications. 

Supply chain risk management. The combination of structured and unstructured data on suppliers can improve the time to sense a supplier risk. The translation of this data for early warning is a big data supply chain opportunity. 

In big data supply chains, data increases in velocity, variety, and variability. The architectures to use this influx of new and very valuable data have names that the supply chain team is just now learning. Start with a cross-functional team to understand its importance and grow from there. 

The ability to sense and shape while listening and learning will define the supply chain of the future. Supply chain leaders are currently ushering in the era of big data, predictive analytics, and learning systems. The future rvill belong to those that understand the basics of what has happened in the past but can see the potential of the future. 

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