In part 3 of D4M International’s Year-End Review, we discuss the biggest battle regarding industry trends in 2024: balancing cost of installation and manufacturing value.
As we mentioned on last week’s episode, though the industry desire is there to adopt current industry trends such as AI/Machine Learning future, without the funds or training to do so can make the entry cost far too high.
In order to weight the pros and cons, D4M International breaks down the importance of standardization before customization, the changing corporate attitude towards integration/data sharing, and then conclude with the seven things you need to do in 2024 to be prepared for the digitization future.
Alan: So with all of the value that we’re looking at – for these mega trends that have been and are occurring and that we foresee even into 2024 – talk to me about, (again, since you all have very significant customer exposure discussions all the time) how can manufacturers strike a balance between adopting those innovative technologies and are going to do so much BUT ensure that it’s a practical and cost effective solution?
Alan: Raj, you’re talking about budgets. All this cool new tech also costs money. Data costs money. How are CIOs and organizations balancing innovation with practicality?
Raj: It’s a very interesting topic, Alan. I think, even though companies are now investing, it’s not going to be free, right?
Raj: The investment part of an implementation is always a challenge. And more and more of the top executives are finding that there is an increased cost pressure and they have to do this balancing act between how much they’re investing in the future versus how much they are really getting the value and also making sure that they are running their operation.
Raj: So, they are always in the mode of performing while we transform. So, they want to keep performing at the same time, keep transforming. For the next few years, it’s going to be this balancing act.
Raj: Recently, I heard one of the CEOs in a forum and when I was listening to a CEO who was talking about digitalization, they are saying that “with digitalization, they’re able to go to market they’ve never been before.” Not only that, they said they’re also able to sell products that they’ve never produced before.
Raj: That’s the end goal of digitization; for companies to go and penetrate markets they have never been and with products that they’ve never sold before. That’s the power of doing digitalization, but that doesn’t come easy.
Raj: It’s going to be a huge investment that they have to make, and they have to be extremely cautious of how much they are investing, what value they are getting, and they are really reaching the goals that they were expecting. All of these needs have to be very carefully analyzed. What more and more companies are doing is they are looking for incremental innovation.
Raj: So, if I look at S/4, many companies are now looking at going from ECC6 to S/4 to start with so that they can run their operations exactly the way they were doing before; after that, they can start adopting innovation in an incremental way.
Raj: Rather than doing everything together at one point, they are now breaking down their innovation ideas and seeing what makes the most sense.
Raj: So they go, start with that, stay with it until it’s more like an agile methodology, right? They start with a couple of innovations, get the value out of it, get more confidence that upper management is happy about it, then more investments come in and then they go do one at a time. That’s the concept of “let’s perform while we transform” type of thing.
Raj: And it’s becoming more and more prevalent in many organizations; because the budget is not unlimited. Every CIO has a limited budget and they have to carry on between running the operations and making sure that they are ready for the future.
Alan: It’s a balancing act.
Raj: Always a balancing act.
Eric: One example that I can bring in that respect, Alan, is a customer that we are working with in the middle of a merger/acquisition. This customer is planning to acquire three different companies so that their business is four entities that are working under the same enterprise. This company hired us to get their value of working together.
Eric: Now, in this instance, the utilization of the standardization in their applications is key to their success. We are working with them to determine what parts of their processes needs to be a standardized first, what should be the specific milestones to track value addition, functional additions, AND find a way to make them totally linked to it.
Eric: This linking is key!
Eric: Getting value is not about having the most productive traditional plants and being a part of the biggest and most popular companies; it’s being about the greatest value in the short period of time. And I think that’s what brings the practicality that you are bringing to the table to truly make these projects a success.
Alan: There’s a consumer -not so much a consumer trend, but perhaps a consumer trend, but organizations follow it too – where they talk about “a batch size of one”, and digitalization of manufacturing is allowing more and more companies to offer tailored product variations aligned to specific customer specifications. But certainly, that trend is driving then a lot of the digitalization of the manufacturing process.
Alan: Would you agree? Victor, what do you think?
Victor: What I think is that companies are mainly acting on/motivated by anticipation of upcoming industry trends.
Victor: Companies are focusing on what tech changes are coming in the next few years. Manufacturers know that various digitalization and customization trends are coming; they know that custom products/manufacturing will be a necessity for them to supply.
Victor: This is why, to me, digital twins in this personalized manufacturing future is a must.
Victor: For the uninitiated, a digital twin is a tool that gives the user a full overview of all processes of the factory. It makes sure that we have all the machines connected, it makes sure that we can anticipate when those machines are going to require some maintenance, and it finds out how many tasks your factory can perform AND/OR, how many variations of said tasks can we do.
Victor: So, let’s think about this; if we could do the necessary preparations to have complete control of the production schedule – and be in a position of complete control – we can say, “okay, we need to produce this type of product this year. Or this month or this week. How do we get these products out on time?”
Victor: We would know what machines to use for what projects and which ones to avoid, in order to supply all of these products to the customers – on time and on budget.
Victor: Not only that, but – since we would also know the efficiency/health of the machines on the floor – we take into consideration when certain machines are going to be down, require maintenance, or need to be replaced.
Victor: So, to summarize, in this custom future of manufacturing, you have to have connectivity, you have to have production, you have efficiency, low costs, BUT – above all – you have to have happy customers.
Victor: 25 years ago, one of my bosses told me, “If you want to be one of the best, you need to anticipate for the future. This anticipation is not always about your shortcomings either; you must anticipate both worst case scenarios but also the best future your company can have.”
Victor: “If you cannot anticipate both potential futures, you will fail.”
Victor: This is why you must anticipate both outcomes to create the factory you would like to have. Figure out what your factory’s best is in terms of production. So, if producing 50 pieces an hour is your best? Great! But, eventually your machine is going to break; so, you need to make sure that you anticipate in the correct timing to fix/replace those parts of the production line in order to not disrupt the full production.
Victor: To conclude, that’s what I’m seeing right now; companies need to understand that any single model – any single process – requires the participation of multiple entities, people, or software and to make sure that everything works together in a fine way.
Victor: We cannot just focus on a tool; we need to review the full process.
Alan: It’s like you were saying, the ideal situation for any production plant is understanding what plates are spinning, which direction they’re spinning, and when they’re going to stop.
Alan: I’m an industrial engineer by training and, when in my first job as an engineer, I was doing some process simulation work – (god, that was so many years ago, we were probably using abacuses.) [laughs]
Alan: All those years ago, I took classes on simulation and eventually ended up selling simulation software. The technology for simulation has evolved and morphed so much since then.
Alan: Getting back to the discussion, all simulations need data to function. What all those simulation models need is to be as accurate and close to what is going on in real life so that you can anticipate what’s going to go on.
Alan: Once you have that, then – suddenly – now you’re anticipating it. And, if/when disruptions happen, the system more rapidly course corrects and moves in the direction that you need to, in order to continue to provide your product to your customers.
Alan: It’s really an amazing, synergistic thing that’s happening as digitalization continues to evolve. But more and more data just means that we can do what we would typically do ourselves only so much faster. And there’s so much value in that!
Chuck: And it’s similar to integration, right? People didn’t realize the value of integration until they had it. Same thing!
Alan: And that’s all about access to data! That’s right!
Chuck: It’s the access to data that’s changing; single source of data. So, you no longer have a duplication or worry about data getting out of sync. But, today, it’s about data, right?
Chuck: And wherever the data is generated, if you can bring it together with other data, there’s power there! There’s value there! There’s a potential return there that – in the past – people may not have thought about or understand the impacts of that.
Chuck: So, I think we’re in a similar mode today where if we can get this data and that data together, what can we do with it? That’s a more accepted question today than it was back when we had organizations that were built in silos, and they didn’t care about the next silo. “Who cares about your data, because I have my data,” right?
Chuck: And so that those walls have been broken down through integration. But now, we’re moving to the next phase of that conversation about data.
Alan: Let’s generate more and use it all together to make fast decisions! Yeah. Good stuff. Good stuff.
Eric: I can see in 2024, at least for D4M, a few tech/business elements that will be delivering a lot value.
Eric: The first components is bringing our customers to the next level of baseline infrastructure within S/4HANA. S/4Hana will be a crucial element in 2024 one because, as Raj said, not because only the technology, it’s because it will initiate the next baseline in manufacturing in order to improve faster.
Eric: The second one is about helping our customers to identify what element should be tackled first, 2nd and 3rd, etc to the transformation of their manufacturing plant (or, perhaps, that’s specific to the plant).
Eric: And then, the third component is that the advanced planning systems. Integration with the manufacturing execution systems will allow your company to first collect the data on the constraints of your shop floor operations, and then plan accordingly for those operations on the shop floor.
Eric: I think that those are the elements that D4M will be working on a lot in 2024.
Eric: I don’t know, Raj and Victor, do you see something additional to that those elements?
Victor: In my case, I can tell that change management will still be one thing that needs to be taken care of. The human side of things – be that HR or employee skill set – are necessary across the full process.
Building skills is going to be super important, and then avoiding bad practices through proper training will be important.
Victor: Not to continue stressing this, but if there was any component I would add, Eric, (other than improving best practices through training) it would be – as I said before – cyber security. That’s going to be a must for the future of digitalization in production plants; especially, in Mexico.
Raj: I agree with you, Victor, in terms of the training. I’ve heard a lot of companies are investing too much money in digitalization, but along with digitalization you also need change management. It’s not just the technologies or the products, that allow a company to adapt to industry trends, right? It’s the culture around the organization – the people, the training, everything.
Raj: A friend of mine once gave an iPhone to his grandpa. But his grandpa didn’t know how to use that iPhone; it’s the same thing!
Raj: You can have all the best technologies in a company, but if the company is not ready to adopt it, and they are not trained or culturally ready to change, every investment that we do is going to be a waste of resources.
Chuck: That’s a good point, Raj and Victor! If you expand that to my thinking around, “don’t throw the baby out with the bath water”, don’t let the future technology take your eyes off the steps necessary to get there. A company must first start out crawling before it can walk just like your company has to walk before it can run.
Chuck: We still have customers that have multiple ERP systems within the same company and – let’s face it – that standardization (which we do very well driving templates throughout an organization) makes a much simpler environment to gather data on, right? If you keep a complex environment where you’ve got five, six, seven, eight, nine, 10 different ERP systems now to accumulate that data to get value out of an AI scenario, it’s going to be a lot more expensive.
Alan: AND be a lot more difficult to accomplish.
Chuck:. Correct! So, there’s still going to be more template driven activity. I believe, because, everyone looks at the European market and goes, “oh, that’s old stuff,” right? “That’s standard stuff. It’s easy stuff.” Yes and no; it’s fairly comprehensive in the magnitude of the operations within an organization and it’s not necessarily standardized OR easy to standardize across an organization.
Chuck: So, I still think there’s going to be some crawling that needs to occur – and walking – before I can become really effective And – to me – that’s a part of the education that is happening out there; where people like, “oh, I want to do AI right now! I don’t care how our plants are running!”
Chuck: Okay, but you’re running 7 ERP systems; that’s going to be expensive. So, maybe there are some steps to do beforehand. Raj, you talked about taking a pragmatic approach. There’s going to need to be some of those smaller steps or earlier steps taken for the benefit of an AI or a machine learning language.
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