Podcast: Navigating manufacturing disruptions with smarter hardware and software solutions

Below is an edited excerpt from the podcast:

IW: I see you’re going to be speaking a little later today about hardware and how that’s really affecting manufacturing. I hope right now we can just kind of take a step back. We’ll get into the hardware in a bit, but let’s start more generally.

You know, we’re in a tough time right now for manufacturing—so many changes are happening very, very rapidly. When you think of how companies can turn to technology to address some of the concerns out there—like the lack of visibility into the supply chain, or the challenges they’re facing trying to match capacity with demand without knowing what demand even is—

What are some of the levers you think people can pull? What are some of the things they can be doing at this moment?

DG: Well, I think some of them—when you think about, I’ll say, the “no-brainers” today—I mean, it wouldn’t be a conversation if we weren’t talking about AI. Obviously, AI applicability. But hardware is really the necessity.

So how do you apply software to the advantage of leveraging hardware in that capacity?

AI to me is operational efficiency. So, the no-brainer to me is: how do you make things more efficient?

The competitive advantage is actually, how do you change the dynamic of your business? You cannot do that without hardware. Fundamentally, you cannot do that without hardware.

I think we’re looking at software automation more than we’re focused on how to utilize hardware brilliance. I keep talking about “hardware brilliance.”

It’s not just about operational efficiency—like how do I find a better widget, how do I find quicker, better, faster. It’s: how do I actually make my hardware smarter for me? And how do I actually make it make decisions for me on the fly?

And in order to make up for the capacity for that—accuracy, unplanned outages, beneficial decisions—how can I do that so I can free up capacity to create demand in the supply chain in a better, faster, quicker way?

So that when I have an unplanned outage, I’m not just spending minutes, days, weeks, or months down. I’m actually creating that uptime much faster—not without human interaction, but with a smarter return time.

That, to me, is where I think the advantage is coming. Because it’s not about supply and demand anymore. It’s about smarter supply and demand.

And I think that’s really where we need to get a little bit better—not just looking at software and AI, but hardware too. It’s the combination of those. And without hardware, candidly, the software and AI really aren’t going to matter.

IW: A lot of the focus I’ve heard over the past year has been on the software side. Like, get your ERP in place, get your ES. So we can do all these great things—predictive stuff, better data. But that better data has to come from somewhere.

If you’re not putting the sensors in your equipment, if you’re not taking advantage of advances in chips—I think you mentioned earlier that you’re going to be talking about AI chips, NVIDIA chips, things that are driving this huge market surge—what excites you so much about what’s going on in hardware?

DG: Just think—when you’re putting more and more of these IoT sensors in devices, you can learn more and more about their health.

Whether it’s the health of a hardware device, the health of a satellite device, the health of something that you typically wouldn’t have even thought about tracking the health of—I love to say that, because we used to just expect downtime to be downtime.