6 Ways Big Data is enhancing the global supply chain

This is an excerpt of the original article. It was written for the September-October 2017 edition of Supply Chain Management Review. The full article is available to current subscribers.

September-October 2017

When it comes to the next generation of supply chain management, the future just may be now. That’s one of the conclusions reached by Greg Gorbach, an analyst at the research firm ARC Advisory Group, after surveying supply chain executives, including subscribers to Supply Chain Management Review, on the digitization of their supply chains. In “The Great Digitization of Industry,” Gorbach notes that while it may take years for the widespread adoption of new technologies such as machine learning, additive manufacturing, smart factories and advanced analytics to become commonplace, digitization across verticals is happening faster than many of us…

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Defined as the massive volume of structured and unstructured data that can’t possibly be processed using traditional software or database strategies, Big Data is affecting every corner of the business world. It’s no surprise, really, seeing that more data has been created in the past two years than in the entire history of the human race. By 2020, roughly 1.7 megabytes of new information will be created for every second for every human being and, at that point, the digital universe will be 44 zettabytes strong (up from a current 4.4 zettabytes).

As supply chain managers scramble to wrap their arms around the reams of information now at their fingertips, a growing number of software providers are making the task more manageable and useful. In other words, simply having the data at your avail isn’t enough; it’s about taking that information and transforming it into actionable insights that help drive operational efficiencies across the supply chain.

“Supply chains are more complex than ever, and with these complexities come many challenges,” says Shannon Vaillancourt, president at RateLinx. “Big Data allows companies to diagnose the issue so they truly understand what is causing it.” Of course, capturing the data and then using it to make good decisions are two entirely different things. To help fill that “gap,” Vaillancourt says software developers are focusing on the 5 Vs of Big Data: variety, velocity, veracity, volume and value.

Vaillancourt says the final “v” is extremely important and often overlooked. “Companies need to be looking for software that turns all of their data into value—or, actionable,” he points out. “Actionable data is created through analytics; it’s the analytics that tells the user what to do, and ultimately what action to take.”

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