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Understanding Smart Supply Chain Data Analytics

Rafael Granato
by Rafael Granato on Feb 3, 2014 8:19:00 PM

There was recently an article on how IBM is driving value into supply chain data analytics to create a "smarter supply chain.” It provides the following example:

"The idea is to ‘embed analytics into the fabric of supply-chain processes.’ Traditionally, analytics has been performed within planning processes on a periodic basis. IBM now wants to take that capability a step further, building analytics into its execution function. It wants to produce reports and generate recommendations directly to users on a day-to-day frequency."

At PINC, we have been doing our part to make supply chain analytics companies smarter, as well.


Customers still try and plan for shipment arrivals over the day, to spread the load and minimize waits, but trucks hardly ever arrive at their appointment times, making such planning almost redundant. Daily or even hourly data is not current enough. At a site level, our yard management solutions use supply chain data analytics to combat this by selecting the optimal parking slot or warehouse gate in real-time as it is checked in at the gate. This form of reactive scheduling requires our cloud-based systems to have an accurate picture of all yard activities.

At a yard network level, our Transportation Suite services provide analytics based on past activity that centralized supply chain execution managers use to view shipments across the supply chain.

Our definition of the "smarter supply chain" encompasses both analytics to aid planning and real-time information to make supply chain analytics companies more reactive to real-time demands on the ground.

Click here to learn more about PINC’s proven “smarter supply chain” options.

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Rafael Granato
Written by Rafael Granato
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