These days sources like Enterprise resource systems, RFID sensor
information, NFCs etc. are generating significant amounts of high quality
data for companies. Having access to better data than ever before, it is natural to expect that they would soon begin to use it for analysis, optimization, and make predictions
about their supply chains. The usage of analytics is not new to the supply chain industry. Application of
analytic techniques has been around for over 50 years (UPS was one of the
pioneers to kick start this). However the usage of advanced quantitative and
statistical techniques have plateaued for last several years; the application
of newer techniques has not really caught up in proportion to the rate/size of
the information that is being collected by enterprises.
There are several factors that make it difficult to make use of this data, specially the technical and computation challenges we need to overcome. However all of
this is set to change with the rise of Big Data and Cloud computing. So what
exactly is Big Data? “In information
technology, big data is a collection of data sets so large and complex that it
becomes difficult to process using on-hand database management tools. The
challenges include capture, storage, search, sharing, analysis and
visualization”1. With the evolution of Big Data technologies, supply chain processes can change dramatically based on sensing and pattern recognition capabilities from both structured and unstructured data.
To make best use of what Big Data can offer to the advancement of Supply Chain Industry, there are some other data quality challenges that need to be addressed. For instance “only 20 percent of a supply-chain data set is internal and 80 percent is contributed by external partners, all of these data transactions are distributed across multiple enterprise systems in different companies with no easy way to determine the single version of the truth”. Also, there is a need to improve overall analytical literacy across the industry as well, so that the industry can position itself to be able to make gains from Big Data.
To make best use of what Big Data can offer to the advancement of Supply Chain Industry, there are some other data quality challenges that need to be addressed. For instance “only 20 percent of a supply-chain data set is internal and 80 percent is contributed by external partners, all of these data transactions are distributed across multiple enterprise systems in different companies with no easy way to determine the single version of the truth”. Also, there is a need to improve overall analytical literacy across the industry as well, so that the industry can position itself to be able to make gains from Big Data.
What other
problems do you see for Supply Chain Industry in context of Big Data? Do you
think Big Data will make a huge impact to Supply Chain Industry in the next
couple of years?
References
1)http://sandhill.com/article/five-challenges-of-managing-big-data-in-supply-chains/
2)http://en.wikipedia.org/wiki/Big_data
1)http://sandhill.com/article/five-challenges-of-managing-big-data-in-supply-chains/
2)http://en.wikipedia.org/wiki/Big_data
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