"Big data" projects can produce impressive results, but they also require supply chain managers to learn a whole new vocabulary. If you know a terabyte from a petabyte or can summarize the differences between descriptive, predictive, and prescriptive analytics, you're in better shape than most. The rest of us need a little help getting up to speed.
To help flatten the learning curve, the industry group MHI has released a 20-page white paper on big data analytics and how it can add value to supply chain operations. Produced by MHI's "Solutions Community" industry group, the report, titled Adding Value to Manufacturing, Retail, Supply Chain, and Logistics Operations With Big Data Analytics, was written by academic experts Ishita Gupta and Manjunath Kamath of the School of Industrial Engineering and Management at Oklahoma State University.
While there is no single definition of "big data," the paper explains how it is generated by a host of systems and devices, such as transactional systems, log files, GPS devices, smartphones, RFID (radio-frequency identification) readers, surveillance cameras, sensor networks, the Internet of Things (IoT), and social media. The resulting flood of data comes in all forms—structured, semi-structured, and unstructured—and some of it is more trustworthy than others, the authors say.
To find out more and get familiar with the new terminology, download the white paper at www.mhi.org/solutions-community/white-papers. And by the way, a petabyte is equal to 1,000 terabytes (while a terabyte is 1 million million bytes).
