World Economic Forum's Kiva Allgood on the Lighthouse Operating System

Kiva Allgood:

I mean the thought of being able to change a cell within hours in a production plant, for some people still they're like, nope, I'm going to test that over there for six months before I deploy it fully. That is the natural DNA of people and operations, right? So I think there's going to have to be a leap of faith.

Jeff Kavanaugh:

I'm here with Kiva Allgood, managing director.

Kiva Allgood:

Great to see you, Jeff.

Jeff Kavanaugh:

You bet. First of all, here at the conference, been a lot of good points of view, perspectives shared. What has been your big takeaway?

Kiva Allgood:

I think the biggest thing that has actually centered everybody is the need for collective action around some really critical topics. One being talent. How do we reshape and rethink and really communicate manufacturing in a way that excites youth? I think people don't recognize that everything around them had to be designed, someone had to come up and create. It took planning, it took purpose. And that's super meaningful. And if you want to save the planet, you can do it one product at a time and you can do it by making things and helping to move things in a more sustainable way. But we don't often talk about it in that light. So I think that was a core takeaway for me is that as a collective we have to really focus on kind of reshaping the way people talk about how things are made.

Jeff Kavanaugh:

Well I think it is the moment is upon us because the realizations out there, especially whether it's local manufacturing, thinking about volatility and risk. One tool to aid in all this is the Lighthouse, gone from the network to the operating system and now with Lumina, the tool. Could you talk just a little bit about what that means for the manufacturing world?

Kiva Allgood:

I've been in this space almost thirty years. I was former master black belt in supply chain on the factory floor, and we didn't have visibility into the full supply chain. We didn't have a digital twin for the plant, we didn't have software-defined factories. They were very insular. So I think as an industry, we often think about our plants and our thing, and we now have the opportunity to really create a community. And do what some of the more technical companies do, right? I'm older than Google is, so they started in the cloud and are doing everything in the cloud, but that's not native for people who make things because it happens on a site. And so the Global Lighthouse Network, it's been around for eight years, it is a way to really attribute greatness to the community that makes things. So it is a peer community, they apply, it is the best of the best, right? It is the fully automated, often using AI already. They've been using physical AI for decades. They have the highest productivity, they have the highest OEE. They're really, really nailing it on all the KPIs. But not everybody is there yet. And so what we've really started to look at is we have eight years' worth of data and best practices. How do we access that and allow people to learn from each other? And that's the Lighthouse community. And the Lighthouse Operating System is really kind of the first of its kind. If you think about Henry Ford's production system, then you had the Toyota production system. Since then, you've had Lean and Kaizen and a few incremental improvements that take your current and kind of process and make you better at one, two, three, sometimes four percent, maybe you get to ten. But how do you really leapfrog? And why do you have to start from where it was? And that's really what we've done with our digital AI tool, looking at eight years' worth of data and really thinking through how do we enable small and medium-sized enterprises and companies that aren't at a level five right now, aren't the best of the best, to incrementally improve.

Jeff Kavanaugh:

Well even some of the larger companies aren't at that level five.

Kiva Allgood:

Hundred percent.

Jeff Kavanaugh:

Just because you're large doesn't mean you're there.

Kiva Allgood:

No, actually and sometimes they're the ones that struggle the most to move the needle. And we heard that today, right? So if you think about the discussions that were had on how did COVID really change the way you run a supply chain? Well they had to throw the book out. We have to learn from that moment and why can't we move it with the same agility and speed when it isn't a crisis? So that's the challenge.

Jeff Kavanaugh:

Well, we've been honored to be part of the operating system, especially the learning organization part, and especially this next phase, going from developing it to pushing it out there. What do you think is going to be critical to its adoption?

Kiva Allgood:

I think people have to be open-minded. I think they have to want to be part of the community and the journey. And I still think that's the number one challenge that we face in our industry, right?

Jeff Kavanaugh:

Mindset and pulling your head up above the day to day.

Kiva Allgood:

Yeah, every person I speak with that has a Lighthouse Award and that has really embraced the philosophy said it is transformational for them, not incremental.

Kiva Allgood:

They had to hire different people that really could see the light that okay by going this far... I mean the thought of being able to change a cell within hours in a production plant, for some people still they're like, nope, I'm going to test that over there for six months before I deploy it fully. That is the natural DNA of people in operations, right? So I think there's going to have to be a leap of faith.

Jeff Kavanaugh:

They think not doing it that way is risky, but you've got to get across that doing it that way is more risky now.

Kiva Allgood:

Yes. You are not going to get to true agility and really I think if you think it a growth mindset and what you can do, and the fact that that we saw some innovators that are saying, hey, you should be able to produce different types of products in the same factory. You should be able to make the drone and make a this and make a that. And the answer is yeah, you should. You should be able to really start to think about manufacturing in the context of one. Like I'm going to make Jeff's medicine that he needs in the formula that he needs and then Kiva's medicine in the formula that she needs. And we're seeing that in other markets. So I think there's an opportunity, especially in the US, for us to stay focused and invest. And then we can scale.

Jeff Kavanaugh:

What I'm optimistic about is because there are some examples, some Lighthouse examples, of it being done this way, others can say, well, I don't quite understand how I'm going to get there yet, but I see it's done, and now I start to believe.

Kiva Allgood:

Yeah, but it has to be agile and the other thing is it's crowdsourced in a way, or group sourced.

Jeff Kavanaugh:

Maybe even open-sourced, as we talked about this morning.

Kiva Allgood:

And we do believe that. I mean I think that's a big challenge because sites often don't share data. I use this example. Almost every manufacturing plant has a compressor of some kind, right?

Jeff Kavanaugh:

And it's not proprietary. It's air. It literally is just air.

Kiva Allgood:

But why couldn't we take the data? Cause you're not going to get a large learning model and be able to use the full power of AI if you only have the information off of one unit. You need hundreds and thousands and thousands. But why not share it in a way that could actually then create some meaningful outcomes for these small and medium-sized businesses that are often running their businesses on an Excel sheet, right? They're not going to, they don't have giant ERPs. So I think we can enable them to do it differently and that could also showcase what open source can do for our community as well.

Jeff Kavanaugh:

One of the broad questions we're asking people is what's separating manufacturers who are successfully moving beyond the pilots to actually scale and transform?

Kiva Allgood:

Well, the data tells us that a unified IoT system is one of the largest enablers, especially for the larger companies. So if you've got a hundred plants and they're all doing their own thing, they often have the same equipment, they're often running similar processes, but if you don't have that insight and what I call full visibility down to tier one, tier two, and tier three, I think visibility into information is that foundational component. And the data that we have from the lighthouses prove that. A unified IoT stack doesn't mean it has to be exactly the same but it does need to speak the same language and it does need to enable you to look at have full visibility into your value chain from inputs to outputs.

Jeff Kavanaugh:

How are leaders measuring ROI, not just for productivity gains, but what is the next level of AI-enabled improvements they're seeing?

Kiva Allgood:

We're going to have to reinvent the investment matrix, right? And this is one of the things we've been stressing within the context of discussions with CEOs and chairmens about their board. If you're looking for a return on investment the same way you would on a capital allocation, you're not going to get it. So there's got to be an investment into the people and training them. And so if you're saying I'm going to restrict the funding or I'm not going to use it the way you would almost like an R&D line, not in a capital allocation line, then you're not going to be making the right decisions. You're going to move too slow.

Jeff Kavanaugh:

One of the areas in our research that's really popped up that sometimes is a hindrance is we are sharing all this, is cybersecurity risks. So what's top of mind for you in that area?

Kiva Allgood:

Physical systems in themselves, like, again, if you walk on a plant floor, some of that stuff was put in in the 2000s and it doesn't have any security on it at all. And that is also I think what is holding the community back a little bit because on-prem is the only secure way in their mind. And even today, when you buy new equipment, it gets quarantined for anywhere from 30 to 60 days until the IT people can make sure that it's not going to do something it's not supposed to do. So we've got to get to a way where physical systems, actual hardware that's going into a factory, can do virtual testing, that you have the ability that quarantine isn't the only way. I also think that we have to be more creative in with regard to software as a system in a factory. So if you define it that way, you have redundancy. You have the ability to really, from a software perspective, have more things that are site secure than not. Today, the number one issue in a plant is always a human. Whether they've clicked on an email or whether they've hit the wrong button, whether they've programmed the PLC wrong. So human error is still the biggest I would say risk. But I do think that there needs to be more thought put into how do you look at the factory as a system, as a cyber system in and of itself. And if it is getting connected, where? Edge compute, in my opinion, is going to play a bigger role. You can run agents on the edge. They don't all need to be in the cloud.

Jeff Kavanaugh:

Helps with latency, helps with…

Kiva Allgood:

Helps with a ton of different things and I think everyone thinks you've got to do this massive compute in the cloud all the time. You can run agents locally. It doesn't always have to go there. So I think people need to also embrace shared risk, right? Both the hardware side and the software side. And that's typically where a third party comes in and then that even adds in more risk, right? So I think the sales models are going to need to change and warranty models are going to need to change as well.

Jeff Kavanaugh:

Since you mentioned humans and source of error, let's talk about that. How do you see the relationship of humans and machines evolving at least in the next few years?

Kiva Allgood:

The rhetoric around, oh, there are going to be no humans in factories in the future is not true. So even if you take the Amazon example, even as they deployed technology, people were involved. We also heard from someone, you're working in a freezer all day long, like below cold, people last less than 18 days, right? There are jobs that people don't want to do. So automation and robotics have a role. But humans do too. And it's that insight and intelligence. Today if you train a robot on average it takes three weeks. That's still too long. Agility comes with the ability to have physical systems that can do things like humans, but the humans are always still going to be in the loop.

Jeff Kavanaugh:

It also forces a growth mindset because if you can get two, three, four X productivity, you don't lay somebody off, well then you have to grow into it. And so you're seeing examples of factories being able to do more and more with the same staff.

Kiva Allgood:

A hundred percent. And they're able to do more and more and they're diversifying and they're reducing the risk and increasing the agility and resilience. And those go together. If you just look at it as a single production or a single outcome, often you're limiting yourself.

Jeff Kavanaugh:

Last question, what gives you hope and optimism for the future of manufacturing?

Kiva Allgood:

The people, the community. I do think, every time we are able to bring this community together, they are very purposeful with regard to and optimistic on where the industry's going. I also believe that we just had another report on economic growth and the number one driver is IT, the number two is manufacturing, but within IT twenty-five percent of that is supply chain software. So I think there's a lack of understanding for how critical manufacturing is to growth and community. And it has a local impact. And that makes me optimistic because if we can continue to kind of share the love and bring people into that community, I think we'll be able to actually have even more impact locally.

Jeff Kavanaugh:

Got it. On that uplifting note we'll end. Thank you so much for your time.

Kiva Allgood:

Appreciate it. Thank you for being here. We appreciate you.

Jeff Kavanaugh:

Great. Again, Jeff Kavanaugh from the Knowledge Institute here at the World Economic Forum's Advanced Manufacturing Supply Chain Forum. Keep learning and keep sharing.