Four things robots can do for your distribution center


Posted by Brenna Sniderman on December 09, 2016.

As we think about advanced, smart technologies, the thing that comes to mind is: robots. Well, maybe just for me. But I think of smart robots that can learn from their surroundings, adjust and figure things out on their own. Robots that can learn from each other, move objects, and work relatively more safely alongside humans, each augmenting the other.

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If you can see it coming, you can fix it faster

Posted by Sam Pearson, on November 17, 2016

How aftermarket supply chain analytics can create an insight-driven advantage

For today’s supply chain to approach optimization, executives must be able to anticipate problems, not simply react to them. That’s a difficult proposition if companies don’t have windows into the right information at the right time. You can’t change something if you can’t see it coming. However, gaining that insight-driven advantage isn’t out of reach. In fact, as products are increasingly loaded with sensors and monitors, the aftermarket is becoming rich in data. It’s no surprise, then, that interest in using business analytics to extract insight is growing. Many manufacturers have found aftermarket analysis to be highly profitable. Now they can see what products or parts are making the most money, what products are being actively used by consumers, and where they might be failing.

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Cognitive consumer products: “Cool” won’t cut it


Posted by Ben Stiller on November 04, 2016

Many consumer products (CP) companies are looking to cognitive technologies—from natural language processing to robotics to machine learning—as a way to engage and capture today’s value-conscious, tech-savvy consumers. However, those who simply embed cognitive technologies in their products, hoping that the “cool” factor will win consumers over, are likely to be disappointed. Many consumers are indifferent—even skeptical—when a traditionally low-tech company touts high-tech advantages.

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Can we all agree to avoid these “I wish I would haves” about cognitive computing?


Posted by Paul Roma, on October 10, 2016

Cognitive computing is already huge, and it’s likely only going to get bigger. And so far I’ve already observed a few seriously risky views on cognitive computing. Why are they risky? Because if they take hold, they’re likely to lead many to say “I wish I would have” in the not-so-distant future. In this case, the implications of getting it wrong, or simply not getting on board fast enough, are serious. Don’t let yourself get caught saying these things a year from now.

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The era of the billion-dollar data lake is over as quickly as it started


Posted by Paul Roma, on October 7, 2016

Well, that was fast.

Remember all those massive, mega-billion dollar data lakes we all kept hearing about over the past few years? With the exception of the US government, we’ll probably never see their likes again. Many of the large organizations that were pursuing those data lakes (not to mention countless smaller ones) have largely changed course. Why? The answer is actually not so surprising, even if this particular outcome is.

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