In this episode of the IoT For All Podcast, Brian Zakrajsek, Smart Manufacturing Leader at Deloitte, joins Ryan Chacon to discuss smart manufacturing and how manufacturers can get started implementing IoT technology. Brian discusses the benefits of smart manufacturing and highlights the increasing need for industry-specific IoT solutions. He also details what to think about before starting IoT implementation and how to ensure its successful adoption. We also cover the future prospects of smart manufacturing and Deloitte's smart factory in Wichita, Kansas.

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About Brian Zakrajsek

Brian Zakrajsek is a Smart Manufacturing Specialist Leader for Deloitte Consulting. He has 20 years of experience in manufacturing and heavy industry across engineering, project management, sales, leadership, and consulting. Brian is a lifelong learner and practitioner of digital transformation in manufacturing. He works in industrial analytics, data engineering, next-gen automation, advanced infrastructure, and cybersecurity across process, hybrid, and discrete industries.

Interested in connecting with Brian? Reach out on LinkedIn!

About Deloitte

Deloitte provides industry-leading audit, consulting, tax, and advisory services to many of the world’s most admired brands, including 80 percent of the Fortune 500. As a member firm of Deloitte Touche Tohmatsu Limited, a network of member firms, they are part of the largest global professional services network, serving clients in the markets that are most important to them.

Key Questions and Topics from this Episode:

(00:44) Introduction to Brian Zakrajsek and Deloitte

(01:14) Deloitte's approach to IoT solutions

(02:13) Impact of technology on manufacturing

(04:04) Role of IoT in manufacturing

(06:36) Benefits of smart manufacturing

(09:59) Challenges in implementing IoT

(10:18) Strategies for successful IoT implementation

(13:47) Challenges of data in IoT

(18:31) Outlook for smart manufacturing in 2024

(25:01) Learn more and follow up

(25:21) Deloitte's smart factory in Wichita

Transcript:

- [Ryan] Welcome Brian to the IoT For All Podcast. Thanks for being here this week.

- [Brian] Hi Ryan. Thanks for having me. 

- [Ryan] Absolutely. Let's kick this off and have you give a quick introduction about yourself to the audience. Also talk a little bit about what's going on at Deloitte in the, when it comes to IoT. 

- [Brian] So my name is Brian Zakrajsek. I'm a Specialist Leader with Deloitte's Smart Manufacturing Practice here in the US. We work with clients on any myriad of challenges across supply chain manufacturing, connected customer applications, and I sit at the intersection of how technology can enable that, including with IoT and industrial IoT technology.

- [Ryan] Does a company come directly to Deloitte and says, hey, here's what we're trying to achieve, and then you sit down, talk to them, understand their problem, understand their use case, and then help them find solutions that already exist? Do you all help build the solutions, or are you bringing in partners? How does that whole process work?

- [Brian] Yeah, I think you described many of the ways that that can happen, and it's probably all of the above, right? So I think, if you think about Deloitte in a classic sense, we probably have high-level, C-level executive relationships across finance or accounting or audit or some other consulting piece.

In a lot of situations, we're doing some type of supply chain work, and it'll naturally bleed into maybe a manufacturing or operations type scope. In some cases, the client has a perspective on what they want to do, and in some cases, we have a perspective and it, and we start to influence that way, but in every case, we're working collaboratively to figure out what that right solution is and what that path might look like. 

- [Ryan] What I want to do is I want to start off a little high level before we dive into the details here, but when we think about manufacturing in general, how has software and technology, before we get into the IoT discussion, how has just software and technology come into the manufacturing space and changed it for the better or maybe in some cases for, made, created challenges that potentially didn't exist before, but for the most part, I think there's a lot of benefits bringing in new technology to the manufacturing space. But from your perspective, how has just new technologies really changed the way manufacturing is done, how we think about manufacturing, becoming more software-defined? What does that all mean and look like from your side? 

- [Brian] Yeah, so maybe just a quick history lesson for those that don't work in the space. Classically, what we call manufacturing or operations technology was very siloed from like the IT technology, right? So there was a pretty strong divide between what ran the machines, ran the processes that existed down on the plant floor and what might run the business systems. Over time, software started to move farther down into the manufacturing levels. And we, a lot of people built around this concept called a Purdue model where we exchanged certain pieces of information vertically through the stack to execute workflows.

Where are we today? We have all of the same tools that folks are used to seeing. So, cloud, edge compute, serverless applications, analytics, AI, generative AI, really smart sensors, connected workflows. All of those have just continued to push into the market and are available in the industrial space.

So all of the sort of benefits that you think around efficient deployment of software, efficient deployment of new processes and agile change, those are the same things we want to do in manufacturing, right? 

- [Ryan] So if we bring in IoT now, what have IoT technologies done and what role do they play in manufacturing and what are the benefits that companies are seeing? And we talk about smart manufacturing a lot, but just if you were to explain to somebody, okay, now we've talked about the different, like just technology in general, how it has impacted the manufacturing space, how has IoT specifically come in and what kind of use cases and applications are really leading the way in this space?

- [Brian] I think there's three ways that IoT shows up in that manufacturing space. So first and foremost, there's this separation of what some people might call IoT versus what manufacturing would call industrial IoT. And so a lot of the traditional sensors, a pressure transmitter, a photo eye, a variable frequency drive, something that we use to control the process, has gotten really smart. A lot of diagnostics, a lot of ethernet connected devices and wireless connected devices. So being able to use that data outside of process control into additional analytics for predictive maintenance applications or asset optimization or downtime reduction mechanisms or even sustainability, environmental monitoring, those are all applications where we're using the same sensors and data, but just in different ways.

Number two might be this influx of like more close to what you would think of or what the general person might think of as an IoT device, right? In a lot of places, we want to put additional sensors onto the assets, additional vibration sensors, humidity monitors. And maybe we want to do that quickly for a proof of concept, or maybe we just want to be a little less disruptive to the 24/7 365 manufacturing life cycle. So a lot of hardened IoT devices are showing up in that space. 

And then I think the last one is also thinking about how manufacturers are creating IoT devices as their products, right? So, as they create products, how are they embedding that intelligence on their way out? How are they thinking about what used to be a dumb product maybe for lack of a better word, a non-intelligent product, so that they can understand how that asset is exposed to its logistics supply chain as it makes it to its customer, where its inventory is upstream and downstream with its suppliers, how the customers are interacting with it so that they can influence engineering and design back around.

Lots of like really cool use cases both from a product, wireless, and traditional sense. 

- [Ryan] The benefits that kind of come out of a lot of these different use cases, I imagine there are ones that are focused really on safety, sustainability, saving money, efficiency improvements. What are the, what other benefits are you seeing IoT technology and thus IoT solutions bring to these organizations? Not just, we talked about obviously visibility into things upstream and downstream, there's predictive maintenance, being able to understand the condition of certain machines and certain elements of a manufacturing process, but just what are you seeing as other benefits that companies are really coming to you and saying, hey, we want to improve our on the floor safety, we need to improve sustainability. How can IoT help that? So what are those things that most companies are coming to you looking for support in order to trying to achieve? 

- [Brian] Operational improvement and operations efficiency has always been like the primary leader, right? I would say that's, as companies have spent the last three decades maybe, let's say, using technology to automate, including automate the long tail of their processes and add these types of solutions to make their machines more efficient, increase the levels of quality along their lines, they're looking for other additions. You mentioned safety. There's an interesting use case that we set up with a large global manufacturer in the metals industry, and they were really concerned around the safety of their workers, right? The most valuable component of manufacturing. How they're working around big forklifts, large stacks of inventory and material that are set precariously, and are they staying maybe in the safe areas. And so one of the things we used, we used their existing camera sensors as an IoT device, applied some analytics on top of that, incorporated also with the forklift collision tracking solutions, to create a safety control tower, right? So now their EHS managers have perspective of how the workers are behaving day to day, but also how they're improving in the different areas over time. 

- [Ryan] That's super interesting. One of the things I think that's really exciting about IoT is when you come into a business who maybe has not deployed an IoT solution, and you deploy it, they start to see the benefits, it scales, there's oftentimes ways that you can utilize the existing infrastructure, the existing technology, and layer on other types of sensors and bake them in together in order to offer more benefits, more insights, more visibility. Is that something that you're seeing a lot in the manufacturing space?

- [Brian] We are, and I think my advice would be to just do that cautiously. I think if you have a COTS solution that's a SaaS product and it, it doesn't really affect the infrastructure, or the infrastructure connections happen at the enterprise or cloud level, cloud to cloud, then it's okay. I think once we start to get into existing physical infrastructure, there's always a conversation. We talked about that siloed nature of manufacturing. Oftentimes, clients are still on their journey to secure and segment and harden and converge their IT and OT environments and adding additional sensors, adding additional camera data flowing through, adding additional analytics workloads. It's just something you have to look for, right? Because protecting production uptime is critical. 

- [Ryan] So if I'm listening to this, and I'm in the manufacturing space, how can I get started implementing IoT technology? What kind of things need to be thought about ahead of time before any type of decisions and implementation starts? And then once you start to implement, what are the keys to success and the advice that you have for organizations embarking on their IoT journey?

- [Brian] Some of this will be classic like consulting 101, which is encourage folks to like really think about the business value and really think a little open-endedly around what would technology enable out of this, right? So that we can stay aligned to that business value and the technology adoption.

I would say one of the things that's happened over these last, let's say, five or 10 years is technology has evolved such that there are solutions we can put in place very quickly to understand and measure that value. But also doing a pilot is much different from scale. So as you pilot, think about what that technology stack, what that infrastructure needs to look like to support, and the human resources, the change management, the process change that happens, what does that really need to look like to support that long term? Because a four-week or eight-week pilot is quite a bit different from a fifty-site rollout across hundreds of thousands of assets. 

- [Ryan] You mentioned something at the beginning of this, of this answer about aligning value of, to the new technology. How can an organization best ensure they're doing that while maintaining that momentum in the transformation that they're trying to embark on?

- [Brian] Classic crossing the chasm, Geoffrey Moore advice. Like you, you have to commit to a strategic vision. There really will be wins, there will be losses, there will be value that comes, more slowly than you'd hope for. Oftentimes, the baseline can be challenging to measure, but it is important to, I believe, to have commitment to the initiative and just make sure that the reasons why you're investing in these technologies or these solutions are, have tight coupling, right, to the value. 

- [Ryan] The stakeholder buy-in is very important. You can do as much planning and prep as possible to get approval for a solution to be set up and deployed into the pilot stage. But once you show that ROI, getting that buy-in or having that buy-in initially is really important, so that you're able to take it from pilot to scale without too much of a gap or any additional roadblocks of now you have to go get approval for more budget, these kinds of things. So having, I think, all that set out and planned initially to say, hey, here's the ROI we're looking for when they come to somebody like you and say here's what we're trying to achieve.

So, you clearly know what their expectations are, and if you meet that, that's when you'll get to scale, which is where everybody wins. So, I think that's a very often overlooked part of the process of how long it can take once a pilot has shown success to then go back to potentially get approval to scale. Having that early on I think is very important to being able to see real success down the road.

- [Brian] Yeah, and I think what I'd add there, I think you were describing like a logical gated structure. I think we all know that humans are not, we're not logical people in the way that we make our decisions. So getting that broad buy-in, and awareness maybe might be a better word, early, right? And maybe championed by a specific portion of the business. Maybe it's the digital transformation team or operations team. But building awareness early and building that story early. Telling the story for some of these transformations as arguably more important than the logical business value early on, right? Small wins with a strong story can really accelerate that sort of initial launch of something from pilot to scale. 

- [Ryan] When you work with these organizations in the manufacturing space, and all this is really about getting access to data that they did not potentially have access to before, being able to take the data in, interpret the data, make better decisions, see improvements and all that kind of good stuff, what challenges are companies facing with the data element particularly in the manufacturing space? Are you seeing issues when it comes to acquiring data? Are you seeing more issues when it comes to how to utilize the data, getting the right data? Where is the biggest challenge that companies are, what is the biggest challenge that companies face when it comes to these IoT solutions they're trying to deploy in this sector? 

- [Brian] The challenge is not collecting the data. There's a lot of popular percentages that are thrown out, but in manufacturing typically low single digits or single digits or low double digits are, is the percentage of data that clients are capturing and actually making use of. The other 80 to 90% is being stored forever and not being used appropriately. Where we find the challenge is often in the, now that we want to use this same data in context with other data sources, right? Transactional data from the manufacturing execution system, time series data coming off a pressure transmitter, demand signals coming up from ERP and scheduling platforms, operator running the line coming from an HR system or a clocking system, bringing that data into context in a structured and modeled way is where a lot of manufacturers are going. So if you want to be able to build applications, build analytics quickly and, quickly and consistently, right, you want to have a logical, structured, sort of semantic data model of everything in context. 

Sounds like a big ask, and it is challenging, but it's doable, right? But the data is very heterogeneous, and it's, and it was done over a three or four decade installation period by an infinite number of people.

- [Ryan] And if you remove, if we speak outside of the data piece particularly, are there any other parts of the IoT journey you see companies really struggle with or any real challenges that exist from the early planning all the way to the scale phase that it's really important for our audience to understand before they can embark on this journey? Or maybe they're already going through their IoT adoption journey and it's just things they need to be aware of and think about outside of just the data piece. 

- [Brian] Most clients, regardless of industry, are somewhere along that journey already. They've, even if it's just procuring technology and trying things out. Big challenges that come across, the human and change management aspect cannot be understated. Manufacturing, number one challenge, all industries is stable, capable, quality workforce that does not have high turnover. And so manufacturing has extremely high turnover. And taking that already challenged workforce and layering on fractional obligations to innovate and transform is just not a good recipe. Thinking about humans, thinking about change management in the process of how you use that technology. We already talked a little bit about strategic alignment and like long-term vision out of that. I also, I do think that while we talked about data, re-evaluating your technology stack net large and thinking about what portions of the organization and the applications am I gonna build? Which ones am I gonna buy? Which systems are gonna connect? What personas need to use that? At a pretty early part of the scale, you want to have a good vision on how your current legacy tech stack or Frankenstein tech stack, and well-intentioned Frankenstein tech stack, is gonna modify to be able to support large-scale initiatives. 

- [Ryan] Yeah, that was a question I was gonna ask you is if you've seen challenges with organizations that have existing infrastructure, their legacy system set up, trying to bring in IoT technology, if that becomes a real problem and what they should be thinking about and how to approach that. 

- [Brian] There's good approaches to abstracting the underlying complexities of those systems. It's an additional layer of technology, it's an additional layer of programming, but oftentimes these are low-code efficient interfaces to move data to different places. And again, we talked about that context issue. Is it a long-term fix? No. But a lot of times investing in the abstraction layers or these sort of new consolidated architectures that'll maybe be event-driven or hub-and-spoke model can help just minimize the pain on the connectivity and data manipulation side. 

- [Ryan] With where we are right now in 2024, what do you or what's the outlook look like from your side of things as we get further into this year with smart manufacturing? Do you see, obviously I think there we're both very bullish on the growth that's gonna be seen there, but do you see new, I guess, use cases and applications of the technology? What are you most excited about? Where do you think the space is going? Just generally speaking. 

- [Brian] All of the areas that have traditionally been popular are still continuing on from a client or industry perspective? We are seeing, there was a bit of a lull earlier in this year across the demand and some cautiousness, but we've seen a pretty large uptick in folks that are interested in a number of different transformational paths inside of manufacturing.

I think from a technology standpoint, the speed at which AI and the buzz of generative AI still continues very strongly. I think the adoption in the cloud is well along, and I think the maturity into manufacturing is also accelerating at a pretty rapid rate. I'm bullish, and I guess I probably should be, right?

- [Ryan] Yeah, I think the more successful deployments and, of applications, the better it's gonna be for the industry. I think a lot of times that is required for companies to get over the hump of any hesitation of bringing in IoT technology or other technologies in general, right? I think the advancements that we're seeing in AI to be able to take that data and do more with it is going to be a big supporter in the adoption of IoT solutions, since that's how the data is collected.

- [Brian] I really, I believe that the convergence of some specific technologies, AI with the IoT technologies with cloud with some of the DevOps and DevSecOps workflows that folks have, all of those together help make a lot of these transformative use cases move at a speed that wasn't previously available. 

Shameless pitch and maybe just a quick example, Deloitte has been investing quite a bit in our product engineering segment. We've acquired some companies that do IoT-type device development, all the way from design, mechanical engineering, electrical embedded software, and then we've coupled it up with our traditional experience in cloud and analytics and like maybe more traditional IoT broad networks. And I think the ability to create products that fit the market at speed is also like a really powerful enabler, right, as you start to see these capabilities come together. 

- [Ryan] I think that's where the industry is now, where people have gotten past any concerns or hesitations about the technology for the most, for, in the last five, 10 years, it's really been about pushing the technology. And now it's about showcasing solutions of that technology, how it's all put together so that companies that are in these different sectors have solutions available to them that are very specific to solving the needs of their business, their industry, and so forth. And I think now that we're at that stage, companies that are investing the time to build those vertical-specific solutions to make them available to their customers I think is how we're gonna see adoption really start to spike in a lot of different industries for sure. 

- [Brian] A hundred percent. And I, and the ability, I would say, five years ago if you would've asked me, I probably would've been more of a proponent of buying an off-the-shelf system and just using the configured features that were available. I'm like way on the other side now because of the ability to integrate, the ability to rapidly prototype those abstraction layers, the efficiencies that have happened at, the partnerships that have happened across some of the different standards bodies and ecosystem players in the market, right? It's, it truly is enabling speed in order to stand new solutions up and build new solutions. 

- [Ryan] Yeah, I think the maturity of the technology too just, when we got started, the big thing was just about educating people on the different technologies, what they are, how they're different, what role they play in a solution and to some people, IoT is still very fragmented.

But as more companies start to piece all of the pieces, all the things together, all the different components together to build solutions that are seamless or feel like they're end, or they're off the shelf, but we know there's still a level of customization that's required, but they're very much tailored to a particular problem in a particular industry. I think that's how companies can connect the most with bringing IoT in. If you're just trying to say, hey, we have this horizontal platform that can do anything, we'll customize it for your needs, that doesn't really do a good job of selling that. That organization knows what your problem is, understands your space, and has built something to solve that problem, and it's been tested and proven, which is where people are now. I think most companies are showcasing their technology in real-world solutions solving real-world problems, and that's what companies can connect and relate to, to say, okay, now I can see how this technology's gonna benefit my business or my customers, for instance.

- [Brian] And it's a bit of a self-fulfilling prophecy that we've seen. And we, I've seen the same thing here where we had a lot of op