Using Big Data as a Supply Chain Asset

It's becoming a commonly-held belief that big data brings with it new opportunities to improve your supply chain, but what do you have to do to turn the idea of big data being a supply chain asset into reality?

Industry executives from EMS provider Jabil Circuits and 3PL provider Transplace provided some answers in a webinar from eft Supply Chain and Logistics Business Intelligence, Data: The Biggest Weapon in Supply Chain and Logistics.

One of the most obvious and essential starting points is building a strong foundation, said Fred Hartung, Jabil's VP of supply chain solutions and global logistics. This is the base level through which all the data passes, how it's filtered, cleansed, verified and ultimately used and distributed.

“The most important part of this is to architect the platform,” he said, adding that companies need to invest a considerable amount of time and resources in getting this piece right as early on as possible. “This is hard work,” said Hartung. “Companies may get two or three years into this, and if they haven't done it properly or haven't really decided what problem they are trying to solve or took shortcuts to get there, they'll end up spending millions of dollars only to hit a brick wall and will have to start over again.”

Key elements for the platform architecture include factoring in mobility, workflow support, connecting to the Internet of Things, advanced analytics, exception management, content management, and some other baseline activities, he said, while things such as visualization capabilities and the ability to take in and validate data are basic table stakes.

Getting the platform design right is not just about experimenting with analytics and how data will be collected, said Hartung. It's also about choosing and understanding which operating system to use, how it accepts and processes structured and unstructured data, and evaluating APIs that allow companies to effectively and efficiently hook into other data streams.

And, it will be an expensive investment, he said, as high as $30 million, Hartung said. “But as you move forward, it will become a critical piece of managing your supply chain. If you don't take a direction like this or buy something or partner with someone who can provide this platform for you, you have the potential of running into trouble.”

With the right systems and algorithms in place, the big data outcomes can produce cascading results, all of which can be used to enhance supply chain operations, he said. Some of the improvements are packaged into concepts such as predictive and prescriptive analytics, which will likely be things we'll be seeing more of in the near-term, and cognitive analytics, which are still several years away. Predictive analytics help companies understand what is happening now and how events may unfold.

Prescriptive analytics gives companies information about steps they can take and what the opportunity or impact will be if certain actions are taken, said Hartung, while cognitive analytics involve greater machine learning to improve the accuracy of predicted and prescribed events and potential outcomes.

Tom Sanderson, CEO at third-party logistics and transportation management solutions provider Transplace, said big data is being used right now in the digital supply chain, and it will evolve and become more second nature. “While we are using historical supply chain data from a few hours, a few days or a few months ago to get a picture of what's happening, we also need to look at what's happening right now. We want to start making decisions not only on historical data, but to take advantage of GPS sensors and other real-time data to make even better decisions.”

Factoring in that kind of data could help companies with spot pricing, deciding whether or not to act on something now or wait to see if the price improves, putting out a bid to collect a wider range of information or evaluating whether internal pricing targets match what's happening in the market, he said.

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