Podcast: Hershey and Nestle execs weigh in on AI, data for frontline workers, and candy
Key Highlights
- Involving operators in digital design reduces fear and drives smoother transformation on the plant floor.
- Pairing Lean with digital tools boosts sustainability by solving real frontline pain points.
- Data must be real-time and actionable to empower operators and improve shift performance.
- Connected worker tech succeeds when it removes “dumb work” and makes problem-solving easier.
We're about a week away from Halloween, and what could be scarier than the technologies that are disrupting manufacturing—artificial intelligence and connected-worker technologies. The 4th Annual Connected Worker Manufacturing summit in the Chicago suburbs this month gathered tech leaders from dozens of large manufacturers to discuss the impacts of data tools, wearable technology, tablets and other connected devices.
What does that have to do with Halloween? Well, there were a lot of food people there, including digital transformation executives at Hershey and Nestle, and we spoke to them about their efforts. Participating on this podcast are:
- Robert Schoenberger, editor-in-chief at IndustryWeek
- Logan McNear, digital manufacturing program lead for The Hershey Company's Lean Production System
- Mike Brauckman, head of focused improvement for Nestle
Below is an excerpt from the podcast:
RS: Logan, the Super Bowl for the candy industry, Halloween, is just a couple of weeks away here. Can you tell me a little bit about how important that is to Hershey, just the most general terms?
LM: When you think about candy and the economics around candy, it's there's the seasons are a big deal. And so we anchor on occasions and Halloween is a very big occasion for really anchoring on the sentimental value behind our product. That like it's more than just a candy on a shelf, but it's an experience that like we often look back on fondly as you grow up and that was your time to grab candy and you get to really indulge in something that you wouldn't normally get to. And that's something that we take pride in, being part of that moment.
RS: You've been talking today about some of the challenges that you've experienced doing Lean and the technology side of Lean within the factory. You mentioned during your presentation that you've seen a lot of the wrong ways of doing things. So kind of getting into the spooks and ghouls and ghosts section of Halloween. Can you share just any lessons you've learned from things that people shouldn't be doing when they think digital transformation and connected worker?
LM: I'll start with saying that digital is not scary and that's that's often the perception. And usually that anxiety comes with the lack of information. So just bringing people into the fold in the process and letting them be a part of the design really alleviates a lot of that scare. And we've taken an iterative approach where We know roughly the end that where we're going to, what our vision is, but we've left enough space for the people actually doing the work to help design the work. And that balance of having vision but also having flexibility is what's making our deployment go as well as it's been going.
RS: One thing I've seen about a lot of technology people when they talk about factory improvements is they often leave the people element out. But you're coming in from the lean side where, you know, respect for people, talking to people, that's a key element. Can you talk about bridging those two things? How you make sure that you're getting that, the personal connection?
LM: From a lean perspective, we're on year 10 of a lean transformation where we're going through and revisioning our systems and really reevaluating our requirements based off the context of today's world. In parallel, we had digital factory initiatives that were creating better data management systems, better tools that are on the floor. But it took the combination of both to really meet people where they're at, to understand what their pain points are and how to match those up with the solutions that ultimately you'll find that people are resourceful and they'll find a solution. But those solutions aren't sustainable if they're not supported with the greater organization's vision for what the future will hold.
RS: I remember from my college years learning that if you give people an incentive, they'll find a way to it. But it might not be in the best interest of the company. It can damage your equipment. It can be a safety risk, things like that. So having to get the incentive in, getting the control around it are two critical things.
LM: Yeah, and the incentive going beyond pure compliance, because I can check a box to make compliance look good, but am I really getting at the value that the system is intending on? So it's linking the utilization to the performance and getting a better picture of the whole package and making it seem fun. Making it interactive in a way that like it's not happening to you as an end user, but you get to be a part of the journey.
RS: Can you give me like an example something you've done on the shop floor to give that individual line worker more information or more control?
LM: I'll give a very specific one. I had a packaging operator that really leaned into the digital transformation for her specific unit. And when she was able to see previous performance on the shift before, she already had handoff information, but she lacked the data behind it. And to be honest, not the most technically savvy operator, but you don't need to be if we can present the data in a way that it can be actionable.
She's able to look at the previous shift, and she brags about how she'll see what stuff they're struggling with on the shift before, call out the maintenance personnel to fix whatever problem or get the necessary people there, and pride herself on having the best shift on her line across all shifts because she's able to use data to make that happen. So if we could just get like a piece of that from every operator that they're looking at data, they're connecting it to the problems on the floor and connecting it to the right people to solve those problems, Man, we'd be in a whole different era of production and a different level of digital engagement.
RS: One last question: What is your favorite Halloween product from Hershey?
LM: That's a tough one. I mean, the go-to is... It's the different Reese shapes we have between the pumpkin shape and the white chocolate ghost. But man, you can't go wrong with any of our products, I tell you.
RS: Next, I spoke with Mike Brockman, head of Focused Improvement at Nestle. At Nestle, he's had a lot of roles in the improvement side of things and was a master black belt. And keeping with the Halloween candy theme, he was part of the confectionery business over there earlier in his career.
MB: We do something called a connected worker blitz, which is essentially you've got the tech in place and you work with the operators to figure out how to use it, again, to minimize the amount of work, right? So you're already doing something for them to help them, you know, get rid of that transactional type work.
Knowing that you're coming next with this approach of, okay, now that we have that data in place, we're going to start to use it to solve problems. So what we gave you in terms of relief, if you will, is the tip of the iceberg. So to me, it's that focus. And I call it being obsessed with ECRS, which is eliminate, combine, reduce, and simplify. And just this idea of everything has to be less work. It has to be less confusing. It has to be less activity. It has to require less thinking, right? Because that's going to create an environment where at the end of the day, I want you to be proud of what you do when you come home and see your family. Not just this place is a paycheck, but if you get rid of the dumb stuff, so to speak, and can create that environment that's actually engaging and fulfilling.
RS: One observation I've had at a lot of plants is that if things have been done a certain way for a very long time, even if it's inefficient or problematic, workers adapt to it, and they get very good at the processes, even if the processes are not ideal. Do you see that ever being a barrier to that change when you come in with a change management?
MB: For the most part, the only barrier I see is that the people want to be heard. And sometimes you have to try something you know isn't going to work because they can't move on until they see for themselves, right? And I think that's part of change and that's part of bringing people along and we expect it, and we know that that's the way to address it.
RS: A lot of the topics that Mike discussed apply to any manufacturing process, not just food. So I asked him, what makes food special? What makes food different when it comes to applying new technologies?
MB: I would say what's different is precision. So I can't make a cookie identically every time. I'm not going to be able to do it. It's not worth the energy to do it. And so our processes have to have a little bit more tolerance, maybe, than, I don't know, say automotive, right? Like it needs to fit in a bag, not in a slot, precisely, that type of thing. So that, like I want people to be obsessed with process control, knowing I can't control it to the level that, you know, Aerospace could control it too.
RS: As quickly as some of these AI tools are developing, as quickly as some of these data tools are developing, you made a comment that people won't need to really worry about developing statistics. They'll just need to know which statistics to use.
MB: Yeah, I think it goes back to applying it. So I don't know if I'll get this quite right, but I'm either trying to compare something, I'm trying to correlate something, or I'm trying to demonstrate some sort of causality. Those are the things I want to do. And for me, the statistics is about making a picture. So I can take something abstract and make it visual for the people who are going to have to live with it. whatever that outcome is, right? But it's a way for them to see what's going on.
RS: I've seen a lot of these companies over the years develop these data lakes, or we'll collect every piece of data we can think of and use it later. Now is that later time. We now have the ability to process that a little more easily and intelligently.
MB: I think part of what we're finding, though, even with a data lake, is latency. I need real time. So if I need real time, then I need it in the PLC, I need it historized, right? I need some way to know exactly when something happens or doesn't, right? So I think that speaks back to whether or not you roll out your tech with an intent. Like I didn't do any work when it came to rolling it out, right? I had a different role in the organization.
And then when I stepped into this role, and realized what was possible, I'd been away for a bit and the team was showing me all the things they could do and I'm like, holy crap, you can do all of this. And we immediately started having, you know, creative time, if you will. And I even go as far as like performance objectives is I expect you to figure out how to save a day a week. Wow. Right. Figure out how to save a day a week. Learn how to prompt, right? Show evidence, right? Let people know, hey, I tried this out, you know?
RS: Brockman said he's gotten so comfortable with the tools that he's even tried his hand at creating the candies of the future with artificial intelligence.
MB: Right, say composition, I'm trying to control acidity, color, et cetera, and I don't have the technology to do what I need to do, and so I know that I need to, dye it is the wrong word, but supplement it with something darker. I'm just prompting the algorithm to say, okay, based on all of this, recommend a formula and a range that I could get my applications and marketing people to be willing to run consumer testing on, right? Rather than a bigger gasp, but let's be really precise. Let's try this.
About the Podcast
Great Question: A Manufacturing Podcast offers news and information for the people who make, store and move things and those who manage and maintain the facilities where that work gets done. Manufacturers from chemical producers to automakers to machine shops can listen for critical insights into the technologies, economic conditions and best practices that can influence how to best run facilities to reach operational excellence.
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About the Author
Robert Schoenberger
Robert Schoenberger has been writing about manufacturing technology in one form or another since the late 1990s. He began his career in newspapers in South Texas and has worked for The Clarion-Ledger in Jackson, Mississippi; The Courier-Journal in Louisville, Kentucky; and The Plain Dealer in Cleveland where he spent more than six years as the automotive reporter. In 2013, he launched Today's Motor Vehicles, a magazine focusing on design and manufacturing topics within the automotive and commercial truck worlds. He joined IndustryWeek in late 2021.