Supply Chain Transformation Isn’t Failing Because of Technology

What if the real reason transformation stalls isn’t the tech, but the fact that everyone is making decisions with a different rubric?
And what happens when you start training AI on processes built 30 years ago?

In this episode of the Resilient Supply Chain Podcast, I’m joined by Don Mahoney, Global Head of Products and Innovation at SNP Group. Don has had a ringside seat to some of the world’s largest enterprise transformations, and he brings a sharp perspective on what actually drives supply chain resilience, business agility, and better decision-making when the pressure is on.

We get into why transformation is no longer a one-off event, but an ongoing capability, and why so many firms still get trapped between “lift-and-shift” modernisation that delivers weak ROI and greenfield ambitions that exceed what the business can absorb. You’ll hear how Don thinks about the sweet spot in the middle, why organisational change is often the real constraint, and why “your plan, my plan, our plan” matters far more than most people admit.

You might be surprised to learn that 80-something percent of enterprise data sits outside ERP systems, much of it unstructured, which makes data quality, visibility, and trust far more strategic than they look on a slide. We also break down one of my favourite lines in the episode: the shift from running a transaction machine to building a decision machine. That’s where the real value is.

🎙️ Listen now to hear how Don Mahoney and SNP Group are rethinking supply chain resilience, data, visibility, and transformation in an AI-driven world.

 If disruption hit tomorrow, would you know where your supply chain was most exposed? In 15 minutes my free scorecard helps you assess 27 resilience statements, calculate your score, and turn the result into three priorities and a 30 day action plan. You can download the scorecard free at tomraftery.com/scorecard.

Transcript

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Don Mahoney: 0:03

At some point in the, project they decided that they didn't wanna move forward with this. We were shocked. They were shocked that we didn't see it. The reason we didn't see it is they were making decisions in a five dimensional rubric and we were making decisions in one.

Tom Raftery: 0:23

Good morning, good afternoon, or good evening, wherever you are in the world. Welcome to episode 114 of the Resilient Supply Chain Podcast. My name is Tom Raftery. If you are leading transformation in supply chain, operations or IT that line about different rubrics should stop you in your tracks because too many major programmes still get treated as technology projects when they're really decision making projects. My guest today is Don Mahoney, Global Head of Product and Innovation at SNP Group. And in this conversation we get into why transformation efforts stall, why organisational change is so often the real constraint and why training AI on 30-year-old processes is a very efficient way to automate old mistakes. So if you wanted to understand how to modernise without dragging legacy thinking, data baggage, and misaligned priorities along with you, this episode is for you. And one quick note before we kick off the first bonus episode of Resilient Supply Chain+ went live last Friday. That episode looks at the war on Iran, its impact on global supply chains and why it underlines the need to reshore energy generation. Subscribe to Resilient Supply Chain+ to catch all the bonus episodes coming soon. Now back to today's episode. And Don, welcome to the podcast. Would you like to introduce yourself?

Don Mahoney: 2:04

My name's Don Mahoney and I am the Global Head of Products and Innovation at SNP Group. Happy to be here to walk through some hopefully interesting priorities.

Tom Raftery: 2:16

Okay, great. And Don, for people meeting you for the first time, how do you describe the work you do today? You know, what pulled you into the world of transformation, agility, and complex enterprise change.

Don Mahoney: 2:29

I joined SNP about a year ago after nearly 15 years at SAP. About half of the time I spent with SAP I was in a product management solution management area responsible for the solution portfolio for the global chemical industry. The second half of my career at SAP I had increasing responsibility for some of SAP's largest and most strategic customers, including companies like ExxonMobil. I then took over the Platinum Customer Unit, which was the top 18 or 20 or so largest customers, and then ultimately the strategic customer program of the 180 largest customers representing some 20% of SAP's business. I really had a ringside seat to what SAP's most strategic global customers were doing inside of their business, how they were looking to transform how they were managing the trade-offs between the business transformation on the one side, and the cost risk and organisational change management constraints on the other.

Tom Raftery: 3:30

Interesting. And what part of this work would you say energi

Don Mahoney: 3:35

It's two really. I really enjoy working with customers. The challenges that they face, the trust that they place in companies like SAP, and SNP to help them on their journeys. Every customer is different, even though so many of the elements of these transformations are, similar. The nuances, the priorities, the, the, the context is always a bit different. So the, customer interaction is, a big piece of it, but as an engineer by training and a product and innovation guy at heart I also love to be in the midst of innovation and, how we match the technologies available to the problems that our customers are trying to solve. I would say those two energise me the most.

Tom Raftery: 4:17

And let's zoom out to the bigger pattern behind all of this. How do you see the landscape of large scale enterprise systems changing, and what pressures are making the agility so hard for organisations right now?

Don Mahoney: 4:32

It sounds sort of trite, but the only constant is change and I think, maybe several years ago, companies looked at, transformations as a larger sort of episodic kind of event. And with the pace of change with the market dynamics and the technology convergence that we're seeing transformation is, almost becoming an ongoing activity as opposed to a, a single episodic event. So I think that's one, thing that we're recognising. The other is AI. You can't turn a corner without hearing someone talk about about AI and the importance of, data for data to be clean for the right elements of your data to be present. SAP has customers that have been on the platform, 30 plus years. On the one hand, the question surfaces, do you really want to be training your AI models on the way you did things 30 years ago? Probably not. Do you wanna get rid of all that data? Probably not. Right? So there's these challenges that are being introduced by AI picking the right range of data, ensuring data quality but also enriching data. it's said that, 80 some percent of a company's enterprise data sits outside its ERP systems and the vast majority of that is unstructured. I'm also seeing an increased interest on what to do with and how to manage the unstructured elements of a company's data landscape. This notion that transformation is an ongoing thing, Picking the range of your data and balancing your transformation against your cost risk and organisational change management constraints are there and then with AI, and the need for unstructured data to feed those models we're seeing that emerge as a priority as well.

Tom Raftery: 6:24

Okay. And where do you see the biggest mismatches between what organisations think is holding them back and what actually is?

Don Mahoney: 6:34

In our own work we see the two ends of an extreme when it comes to transformation. One is the so-called greenfield approach where arguably you're maximising your transformation impact because you are taking advantage of all the new business processes. You're wiping the slate clean and moving into a new platform. Completely. On the other extreme is, the brownfield lift and shift kind of a thing which promises maybe a, a simpler and more rapid transformation, but doesn't tend to bring the transformational ROI, that people expect. We see people getting trapped between those two extremes where the, brownfield fails to offer a positive ROI, 'cause you're spending a lot of money to move to a new platform, but you don't have the transformation business credits to pay for it. On the other extreme, the Greenfield is really a re-implementation. But for many companies a company's a set of risks and costs, and especially organisational change management that goes beyond what the company can absorb. And so where we see people getting held back is, is they're sort of trapped between these two extremes. Maybe sometimes not recognising that there's a hybrid approach that allows you to dial in, an appropriate level of transformation for your business to support a positive ROI and a strong business case while at the same time not violating the cost risk and organisational change management constraints that your company faces. And of course, we call that blue field, at SNP and it's the, selective transformation capability that allows you that flexibility in the middle.

Tom Raftery: 8:18

Dig into that Bluefield concept a little more for me. How does that work?

Don Mahoney: 8:22

Well, again it's the concept of keeping the best of what you have and transforming the rest, as opposed to an all or nothing. In the brownfield, again, you're lifting everything over, including the baggage of your decades of, legacy, operational history and so forth and, the data. With the greenfield you are, generally speaking, doing a brand new reimplementation. And so, what bluefield basically offers is a way to say, let's find that sweet spot. Let's understand what it is that is the best about what we've customised, what is the best about how we've operated. Let's make sure that we're moving that over and preserving it. Especially in the sense of providing continuity for our users, access to, important historical data that is important for reporting, for compliance reasons for running the business, but at the same time, taking the opportunity to shed the vast majority of the baggage from past decades that really doesn't have much application, is contributing to your technical debt, is contributing to unnecessary IT expense in terms of your footprint, and many other impediments that, drag you down. So that's really the idea is how do you, keep the best, transform the rest dial in an appropriate level of, ROI, without exceeding the cost, the risk and the organisational change management constraints that the company operates under?

Tom Raftery: 9:52

And for a solution like that are the biggest barriers, technical or people, or a healthy mix?

Don Mahoney: 10:04

For companies that are trying to do this on their own or with, let's say just the manpower or person days that they would apply to doing this themselves. the barriers are, quite substantial. SNP, we have over 30 years of experience doing this, having built content, guided procedures, automations, and so forth. So, we actually take a lot of the complexity out of what is otherwise a more complicated experience.

Tom Raftery: 10:38

When organisations want to modernise without creating chaos, what principles help them move with, I dunno, purpose, instead of just moving data around.

Don Mahoney: 10:53

I think this is where it's important to get the business users involved. In many cases a transformation is often seen as an IT led exercise. And of course IT plays an incredibly important role in that. However, absent the guidance and the engagement of the business users it's gonna be very difficult, to navigate. I think it's also important to work very closely with the associated SI. We tend to focus mainly on the data leaving the SIs to work closely with the, customer on the business process transformation, making sure that there's strong alignment across the board between the company's business users, the SI who are helping to navigate the business process changes, and then your data transformation provider like ourselves, making sure that we're all on the, same page there. But definitely, employing some of the standards that maybe your SI would come to the table with as well. At SAP. I spent a long time in the chemical industry business unit, and we had developed a very substantial body of best practices for the chemical industry. We found that that was very useful for customers because it helped eliminate some of the internal bickering about which way we should do it. This team wants to do it this way, this team wants to do it that way. Well, there's a best practice out there, and why don't we ask, why not adopt the best practice first? And then only when there's a business case to justify some deviation from that do we engage in those kinds of conversations. So there are a number of best practices out there that, companies can avail themselves either through SAP and some of their industry solutions and the SI providers. And I think that can provide a lot of guidance for companies who are looking to, drive their transformation with a steady hand, and a clear roadmap for, getting to where they wanna be.

Tom Raftery: 12:46

So. Don in, in your experience, when companies modernise thoughtfully, you know, what changes first, would it be speed, risk reduction, data quality, workforce alignment, something else entirely?

Don Mahoney: 13:05

Yeah, I mean, it's, all of those. unfortunately data quality is one of those items that I think in my own personal estimation, doesn't get the attention that. It has deserved. I think a lot is invested in MDG and those types of applications getting the data hopefully in right for the first time. But this notion that you have the kind of telemetrics to stay on top of your data hygiene to make sure that it stays clean that it's optimised, that it's enriched and so, again, going back to the comments relative to AI, I think this is gonna become increasingly a priority for customers, whether it's there yet or not. I've mentioned a couple times in this conversation so far, the organisational change management constraints that companies often have. And I raised that because in my prior role at SAP especially as I had a, this front row seat to the transformation activities of many of SAP's largest customers it was the organisational change management constraints that often restricted and limited just how far a company could go. I had some experience with one project in particular where the customer was really evaluating their path forward in five dimensions. And those five dimensions included the strategy, the cost, the risk, the organisational change management, and the technology. Well, we were kind of restricted to the technology swim lane and the technology swim lane only. And at some point in the, project they decided that they didn't wanna move forward with this. We were shocked. They were shocked that we didn't see it. The reason we didn't see it is they were making decisions in a five dimensional rubric and we were making decisions in one. And of all those, I think we had strategic alignment. There may have been some mis. Not misunderstandings, but maybe differences of opinion about what the real cost was. They're in the best position to, evaluate their own risk, but what surprised me the most was how big a constraint the organisational change management was in the context of the entire project. And so, to me, that's, one that people really, really need to take a close look at, because if, you say, look, we've got our strategy sorted. We think we can manage the cost, the risks are reasonable. The technology can support it. But if you haven't looked deeply into the extent to which your organisation can manage the change and at what pace they can that can have very expensive consequences to a transformation especially if you get well into it and discover that it's really a significant limiter.

Tom Raftery: 16:30

Yeah. I've often said on the podcast that changing technology is easy, changing people, not so much so,

Don Mahoney: 16:37

Yes, that's very true.

Tom Raftery: 16:39

With that particular project in mind, Don how could you have done it differently to avoid coming to that kind of screeching halt?

Don Mahoney: 16:49

Yeah, I mean, it's only with the benefit of hindsight that we discovered, and I'm glad we did the assessment because, it really was important for us to go do some forensics about that. And it was only through the forensics that we discovered those five dimensions. And what I would do differently is make sure that all of the significant parties, in this case, SAP, the system integrator and the customer themselves, that all three of those were tied in to that five dimensional decision making rubric. And I know it's difficult for some customers to trust their partners enough to share the full details of that, but I think the consequences are so significant that failing to do so creates a much greater risk than any risk you might feel about, sharing certain elements of, that information. So making sure that all the parties understand your strategy, understand your perception of the full cost, understand your perception around risk. The limitations you have with organisational change management, and then of course the, the technology challenges and the technology roadmap, if all are on the same page with those five dimensions, I think things would've gone very you know, much more differently. And again, this notion that your plan is, my plan is our plan that all the parties to the project have the same understanding of those priorities would've made a huge difference in that particular project in hindsight.

Tom Raftery: 18:24

And in successful projects, where do you see the biggest value unlock? Is it operational, financial emissions related, customer facing, all of the above, something else entirely?

Don Mahoney: 18:40

Yeah, I mean, it varies. I love to go back to a quote that Keith Sturgill, who was the former CIO of Eastman Chemical a number of years ago had mentioned to me and he said that his job as CIO in helping, in this case, Eastman to transform, was to help the business move from being a transaction machine to a decision machine. And I really love that analogy because it's not that transactions aren't important. They are, but they're important in the way that breathing is important. You need to do it, you need to do it well. but you certainly don't want to have to about breathing. And I think for many companies they've spent the last 30 years focusing on transactions. And so the extent to which a business transformation can help change the way employees work and change the way businesses within a company can transform from transaction focused to decision focused. That's where the biggest impact in these transformations can take place because the transactions can be automated. And to the extent that we've spent, I don't know, 80% of our time focused on the transactional elements with only maybe 20% or less focused on the, the optionality and the decision making that helps drive our business forward. If we can flip that, I think that's where the biggest impact comes is how do we help transform our businesses from transaction machines to decision machines. And I think the capabilities that are out there today, especially including AI, have made that a much more realistic promise than it's ever been.

Tom Raftery: 20:26

Okay, good. And so looking ahead, in that case, three, five, maybe even 10 years, where do you see the biggest shifts in how organisations will approach data, transformation, system landscapes, et cetera?

Don Mahoney: 20:41

Well, yeah, I mean, data's at the core of this and we're already starting to see the huge sucking sound of data coming in as people look at building out their AI capabilities. I think we're gonna see, a lot more of these announcements around data fabrics and so forth. SAP made an announcement in the collaboration with Snowflake I believe it was to federate, large swaths of data to support customers and their AI strategies. We're going to see a greater focus on the unstructured data side of the house as well. There's an amazing amount of content that is trapped in, documents and invoices and emails and PDFs and, all sorts of things. that until they're identified, analyzed some level of structure is, brought to them and brought into that context there's a huge amount of value that's going untapped. So I think we're gonna see, increasing focus on, the unstructured data. And as I said before data quality. While I think it's recognised out there, whether it's got the level of priority today that it, will need. Again when you're talking about bringing AI to a level of not just an advisor, but an actual agent that is doing the work and actually executing activities data quality is incredibly important.'cause again, if you've trained models on, poor data, they're gonna be, making bad decisions and taking, damaging actions. So, data quality's I think gonna become an increasingly important priority for companies as well.

Tom Raftery: 22:14

yeah, it makes sense. garbage in, garbage out, as they say. But with AI, it comes out much faster.

Don Mahoney: 22:19

Yes,

Tom Raftery: 22:19

All

Don Mahoney: 22:20

With bigger consequences potentially.

Tom Raftery: 22:23

So what opportunity do you think most companies are still overlooking as we look forward that three to five to 10 year landscape?

Don Mahoney: 22:32

Yeah, I I think a couple things just my observation, we have, I would say five years ago, maybe a little bit more, when the concept of enterprise systems in the cloud first started being, talked about companies in chemical industry, oil and gas, utilities, the concept that they would be running their business in the cloud was unthinkable. And it's been interesting to see how that sentiment has changed. But I think there are still companies who haven't yet fully embraced the possibility of the cloud and, what that offers. So in terms of where companies are potentially missing out I think being bold enough to understand that, this is where technology's going. And taking every opportunity to move in that direction where your business can support it, is an important area to look at. The other side of it is, looking at some of these, transformations and I'll cite, let's say SAP S4, HANA rise transformation, so forth, looking at them as more of a, technical transformation and not the business transformation opportunity that they really are. And so I think some combination of challenging your organisation to, maximise the extent to which you can move your business to the cloud, and incorporate as much business transformation as your constraints allow. I would say are, are two primary areas where, companies can really focus and, check themselves on whether they're doing enough to move in that direction.

Tom Raftery: 24:13

Okay. And so in that scenario for supply chain and transformation leaders listening to this episode, what's one practical step they can take to build more agility and resilience into their organisations?

Don Mahoney: 24:28

Well, again, I mean, I'm speaking with a, a bias on, data, but data sits in, so many different places in a typical company. and for a lot of the companies that we speak with, they have a rich history of mergers and acquisitions and divestitures and so forth, which just adds, even more fragmentation to their landscapes. When you're looking at that data. If there are opportunities to consolidate, to cleanse, to optimise, to enrich, that to me would be one of the single most important things a company can do to bring business agility. to the table because when you have to make a decision, and yet the data sits in different silos, and it takes you a week to reconcile it and, get to the answer, that's not very agile. When your information is incomplete and you have to fill the gaps with, uncertainties and, and best guesses, that's not very agile. I think, as companies can do a better job of consolidating, enriching, optimising and transforming their data landscapes the ability to act with agility and resilience is, markedly improved.

Tom Raftery: 25:45

A left field question for you, Don. If you could have any person or character, alive or dead, real or fictional, as a champion for enterprise transformation, successful enterprise transformation, who would it be and why?

Don Mahoney: 26:06

Interesting. maybe let me start with some of the attributes and then I'll, I may be able to back into a, a particular figure. We need to be visionary again because I think if you're only looking at the technical aspects of moving to a new platform, it's really not going to get you where you need to be. So visionary. We need to be persistent. These things are never without their problems never without their frustrations, as we talked about before, as difficult as the technology pieces are, sometimes the people pieces are even more challenging. So, you know, persistent but also practical and pragmatic. I've seen some companies bite off, too much only to discover they have to trace things back and proceed against a reasonable path. So, I don't know what historical figure has, has been, Visionary, persistent, and yet practical and pragmatic. I don't know. John F. Kennedy got us to the moon. maybe something along those lines.'cause it had to be practical enough to be realistic visionary enough to be bold and certainly required a lot of persistence to get there.

Tom Raftery: 27:13

Love it. We're coming towards the end of the podcast now, Don, is there any question that I didn't ask that you wish I did, or any aspect of this we haven't touched on that you think it's important for people to think about?

Don Mahoney: 27:27

Yeah, I think, I mean, we, we talked about, a lot of the ambitions, a lot of the constraints. We talked about the importance of your plan is, my plan is our plan. The sharing of, the full range of decision rubrics that are, important. Being bold being persistent. Yet being practical and so forth. I think we've covered a, lot of the, important terrain, involved. The only thing I would, say too is that in order to warrant the trust that's necessary to be able to share the full decision rubric, you've gotta pick your partners in the process. And so, there's a lot of shiny objects out there. There's a lot of companies that are coming on the scene with, some new capabilities and definitely should be examined. At the same time, it's important to, look at those companies who've been around for a long time, who've persisted with you through the ups and downs of, the market and who's consistently been, helping to deliver value. So, understanding and, and taking the time to pick the right partners I think is a, is another element. But we covered a lot of, a lot of good terrain.

Tom Raftery: 28:32

Okay, Don, if people would like to know more about yourself or any of the things we discussed on the podcast today, where would you have me direct them?

Don Mahoney: 28:41

Well, snp group.com is our website, and so a lot of information can be found there. I can be reached directly at don dot mahoney@smpgroup.com and I'm happy to either field questions or direct people to the folks who can. I'm also on LinkedIn. You can just look me up by my name and SNP and you can find me there.

Tom Raftery: 29:05

Fantastic. Great, Don, that's been really interesting. Thanks a million for coming on the podcast today.

Don Mahoney: 29:09

Thank you. Enjoyed it.

Tom Raftery: 29:11

Okay. Thanks everyone for listening to this episode of the Resilient Supply Chain Podcast with me, Tom Raftery. Every week, thousands of senior supply chain and sustainability leaders tune in to learn what's next in resilience, innovation, and transformation. If your organisation wants to reach this influential global audience, the people shaping the future of supply chains, consider partnering with the show. Sponsorship isn't just brand visibility, it's thought leadership, credibility, and direct engagement with the decision makers driving change. To explore how we can spotlight your story or your solutions, connect with me on LinkedIn or drop me an email at Tom at tom Raftery dot com. Let's collaborate to build smarter, more resilient, more sustainable supply chains together. Thanks for tuning in, and I'll catch you all in the next episode.