Supply chain expert and SAP SCM/IBP Architect Odell Smith of My Supply Chain Group joins this week’s QuickHit to talk about how proactive companies will survive, how data helps them decide quickly on supply chain solutions, and what we can do to be better prepared next time. After a quick 5-year stint in engineering, Odell has been doing supply chain technologies for over 30 years. His company does mostly SAP products and advisory services and implementing technologies for the supply chain.
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Show Notes
TN: How are your clients looking at their supply chains? How do they use their data to better understand and plan their supply chains even with all the craziness and volatility? Can you give us an example?
OS: Our clients have had a variety of different issues. There are companies that even inside the same company, they’ve had one business unit with a huge spike in demand and another business unit will just drop off. One of our clients is one of the largest beer producers in the world. Their keg business that supports restaurants just evaporated all of a sudden. But their bottled beer just went through the roof.
So these companies are trying to see these demand patterns as they come in, but also be able to quickly respond to those. Everybody’s used to the monthly demand patterns. But being able to see such a rapid volatile change in these demand patterns and being able to see that with data in the systems, then being able to simulate how you’re going to respond and make intelligent decisions based on that data, has been a real game-changer. If this had happened 20 years ago, it would have been a much more difficult scenario to recover from.
TN: What kind of data are people using to make these decisions? Because we really don’t know what’s coming from the outside. All the governments say macroeconomic data. This hasn’t come in obviously. So how are people taking data in to understand how to adjust their manufacturing patterns?
OS: The operation’s focus is about trying to estimate what that demand pattern is going to look like and then be able to adjust from that, if you have a constant supply. But if you have an irregular supply, it’s also a problem.
Another huge issue here is we’ve off-shored so much stuff in the last 15 to 20 years. An example is one of our customers that is a large paper supplier. They bring in pulp from other suppliers. Everybody’s familiar with the toilet paper issues that we’ve had. These guys had all kinds of issues come up. They bring in product and then they manufacture that product. As they do that, their supply chains were disrupted by not being able to get their suppliers’ product through the ports. Their port activity was blocked. They knew that was going to be the case, and so they had to redirect some of that stuff that was coming in to run their manufacturing.
They also worked proactively with the ports. They knew that the port was going to be closed and they had to redirect that. We put in some cost optimization for them to be able to evaluate simulations to estimate where it looked like the best place to bring this raw material. And then of course, their manufacturing process itself had to change, because there’s a lot more demand now for toilet paper than there was for paper towels.
Nobody expected that demand shift. Everybody was unprepared for that. But being able to use data to make smart, intelligent, short-term decisions about how to correct for that new demand was something that they were able to put in place fairly quickly. For scenario planning, we were using SAP IBP to be able to make those right decisions.
TN: I started my career in a freight forwarder, customs broker, and all the physical logistics around it. And it was always interesting to me early in my career to see when people had cost-sensitive, time-sensitive, quality-based decisions, and you’re balancing all three. The types of decisions they made sounded like they didn’t really have any history to go by. They were just looking at expectations, and you’re just playing it day-by-day or week-by-week.
OS: If you have the tools and you have the data, then you can do that. Now, a lot of this data was manufactured data themselves because it was based on estimates. What are my options here? I’ve got three other ports to use, and there’s different costs of transportation going through those ports, plus there’s a risk. Will I be able to get the stuff processed through and time to be able to make it? And if I don’t, then what’s the downstream impact to me in my subsequent manufacturing process?
TN: All to get a roll of toilet paper to your corner store. What would you say manufacturing companies need to be thinking about? How can people be better prepared the next time this happens?
OS: One thing that came out of this is that this data is changing so rapidly. [Companies that can] access that data can see what worked, and what didn’t work from the last situation. There are going to be some things when you’re making these snap decisions, and you’re just trying to keep your business afloat. There are going to be some things that you learn in hindsight that were not the best thing to do. As long as you plan for that, and you know that that’s going to be the case, and you review that after the fact, and are prepared for that risk, know where that risk is, then it always helps you be able to respond better next time. If you don’t learn from those things, shame on you.
TN: Do most major manufacturing firms today have a good base of data and well-organized data to make some of those decisions? Or is it still kind of iffy?
OS: It depends. There are some that have really good data. But it has to be a decision by the company. The company has to decide to put the resources in place and to have that vision, that strategy of knowing that that data is important and that the data needs to be reviewed, audited, and cleansed.
Some companies are very proactive. Some companies are completely reactive. And when you get in a situation like this with this craziness, these [reactive] companies won’t make it. Proactive companies will make it. So it’s really a business mindset and putting a value on that data that makes it helpful.
TN: These major manufacturers that you work with, I think there’s a perception out there that a manufacturing firm has one ERP system. Do you work with any firms that have kind of one ERP system or are they dealing with half a dozen or more typically?
OS: There are companies that have been able to maintain that single ERP situation. But more than not, you wind up with mergers and acquisitions. And these M&A activity is just brutal on IT organizations because very seldom do you acquire somebody who has the very same ERP system and they are on the same version that you’re on. And then, there’s a product rationalization and a customer rationalization that has to take place. Those are all very difficult things to get past.
TN: Pointing out, so just people understand. It’s not as if you’re just taking data out, putting it in a big machine and then putting it out the other end to help make a decision. You’re taking data in from a lot of different sources. And you’re making sure that it’s somewhat normalized or understandable in the output. And then those managers within those companies are also seeing data in a number of different formats to make those decisions. So this isn’t linear. This looks more like a bunch of weeds over here and a bunch of mangled tree roots over there and you’re trying to make it as linear as possible. The complexity of these decisions, the complexity of these data, say logistics activities, are just fascinating.
So last question here Odell. You’ve seen these companies through the first phase or two phases of this. Do you see these companies back on a path to normalization now? Are there manufacturing and supply chain processes normalizing now?
OS: There are some that are beginning to get back on the horse and there are some that are just still severely impacted. Some of our customers are in the pharma industry. They’re just going nuts and they’re going to continue to go nuts for a while. It’s really a mixed bag of things. A lot of our customers manufacture products that are related to home. Everybody has been doing a lot more of that lately. Demands for those have still been really strong even though supply may have been impacted by some of the situations.
One of our clients is a company that has multiple legacy systems. One of the great things about these new cloud solutions is the ability to do that normalization, to be able to take data from multiple different ERPs, disparate ERPs, and bring it in for a total view for the executive team to make these quick decisions. A lot of our customers are doing really well, and so it’s great to see them coming out of this. It’s been a slow couple of months for people just to wrap their arms around the thing, and try to just fight fires. And then now we’re coming out of some of that and into recovery mode that looks good and strong.