Harnessing Data for Intelligent Service w/ Denise MacDonell, Flash Global

00:13
Gerardo Pelayo Rubio
Good afternoon, everybody. I am Gerardo Pelayo, the Chief Research Officer at Service Council. I want to welcome you to another edition of our In Service podcast. We just got past our first hundred episodes, had a great time celebrating the. That milestone. I would invite you to revisit that episode. We had a couple of surprises embedded in there. And today is a great segue into the next 100 episodes that we hope to have.

00:51
Gerardo Pelayo Rubio
We’re going to be talking about harnessing data for intelligent service. And I’m really glad to have Denise McDonnell, she’s the chief Technology and Marketing Officer from Flex Global, to help me go through this. This conversation. Think about it together, and what does it mean for service organizations? We’ll get to know Denise in just. In just a second. But before, let me tell you a little bit about why I think this is such an important topic. As we go through a service event both during, before and after, there’s a trove of Information that gets generated, some of it is intentional because of the traceability that is required or in order to try to memorialize some of the data, the knowledge that gets generated in there. Some of it’s the transactional activities that go with it.

10:37
Gerardo Pelayo Rubio
The data that we are not going to use today, but we think it might be useful in the future. And as we start putting this together, two things come to mind. First off, complexity is high. How are we going to prioritize, connect, integrate all of this data into something that is relevant? And that leads to the second question, how much of that data are we actually leveraging? Are we actually utilizing today? And would we be able to do better if we did? So that’s going to be the core of our conversation. And one of the things that it relates to in terms of how at Service Council we think about the service experience is we rebuild this list of expanded five elements that drives the service experience around. Philosophy, the people, the platform, which is this integration of data, technology, processes and parts.

11:31
Gerardo Pelayo Rubio
So as we think about data and intelligence, the part that I’ll be pushing Denise on to pick her brain on is how does it relate to the processes and the performance of parts so that we don’t think just about a foundation, but that we’re thinking in terms of our workflows and impact that can be achieved. A bit of housekeeping before we get started. A reminder that today’s session is going to be recorded so you can go back and revisit it. You can share it with friends and all. It’s going to be available on all our usual social platforms and anywhere where you typically listen to your podcast and the other thing to our LinkedIn audience. We hear you, we see you and we invite you to take part in the conversation if there’s something that you want to deep dive on.

12:21
Gerardo Pelayo Rubio
If you have a comment, whether agreeing or disagreeing with the conversation, please let us know in the comments and we’ll try to infuse it into the conversation. Worst case scenario, we’ll be replying on the chat and make sure that we are closing the loop on that one. Without further ado, I want to spend most of the time on the conversation. Denise, I’ve had the pleasure to get to know you a little bit. I really like your approach to this topic. But for the audience that might be less familiar with you and with Flash Global, do you mind sharing a little bit of an introduction to yourself and what is it that Flash Global does?

13:03
Denise McDonell
Sure, sure. Well, first of all, thank you for having me. I’m excited to get into this topic with you here today. So I’ve been with Flash global for about 10 years, so just backdrop on me. I. I’m a mom of three. I live in Nova Scotia, Canada. So interesting fact about Nova Scotia is it’s another time zone off of Eastern Standard Time. So a lot of people don’t know that. And the best way to describe it is just if you know where Maine is in the United States, then just go a little bit further east from there. And that’s where I am, a beautiful, picturesque coastal community. So I’ve been with flash for about 10 years.

13:41
Denise McDonell
I’m the Chief Technology and Marketing officer, which is a very unique role for me and it’s a unique role in the industry to have an intersection between technology and marketing. However, as we start to get into this topic together, I do think it brings and affords me an opportunity to have a very unique perspective in terms of the way technology plays into where the market is going and then how that relates to how customer needs start to manifest in terms of Flash. Flash has been around a long time. Our business is the service supply chain and being able to deliver commitments and quality execution to our clients.

14:19
Denise McDonell
As we think about service part location around the globe and how you deliver on your service commitments and how high tech OEMs do that, I will definitely say from a background perspective, this is certainly one of the most exciting and nuanced businesses that I’ve worked in over the course of my career. Service supply chains are one of the most complex operational environments that I’ve experienced in any company. Every time something fails, you’re coordinating so many different things. Logistics, parts, technician, inventory, warehouse locations, your customer commitments, your service commitments. And that happens across the globe and it needs to happen instantaneously, you know, in a matter of hours where every minute counts. And so what’s exciting today is that all of these activities generate a tremendous amount of data and that data is unharvested in many cases.

15:17
Denise McDonell
And so I’m excited to talk about how we’re thinking about how you connect that data and how you turn that service from reactive into more of an intelligent, proactive process.

15:28
Gerardo Pelayo Rubio
That’s great, Denis, thank you. And in fact, your role, I would say it’s living proof of that integration of data towards an objective. So you’re walking the talk. Certainly segueing from what you said. I think it’s important to baseline a little bit what we mean by the underutilized data. I often say that the most fun part of my job is being able to connect the possible with the relevant. So let’s start by understanding what is that possible? Because when there’s a service event and we think of, hey, something got fixed, some issue got resolved, we tend to think about failure data as the one that tends to get generated and the one that can be leveraged towards future service events. But as both of us have sort of teased out, there’s a lot more data that goes around one of these experiences.

16:24
Gerardo Pelayo Rubio
And in the execution of a service supply chain. Can you talk a little bit about what is, from your experience, what is specifically some of the data that is potentially underutilized in most of these cases?

16:39
Denise McDonell
Sure, you’re right. Most of the time we really hone in and focus on the actual failure data, because that’s really where you’re trying to understand what happened with that particular device or product or what have you. But all of the surrounding activity that happens in order to service that service event does harm. It does afford an opportunity for a lot of other data that to your point, is underutilized data, such as your inventory movement itself. You know, was the inventory where it needed to be, that service inventory? Was it where it needed to be in order to deliver on the quality commitment of that service event? How was it routed to get to the service event? Were you expediting it or not? Are you paying more than you should be for transportation or not? How did you make those routing decisions?

17:28
Denise McDonell
How did the inventory get placed in the first place in the location where it was drawn from? How did you think about the dispatch timing, the timing of when a service event is necessary to begin? What we’ve observed is there’s a lot of things that can happen at the front end of a service event where time gets lost. Analyzing that and understanding, well, what data was missing that did not afford the service event to move into motion immediately. What was all that time spent doing before the service event could take action is a treasure trove of information. And then kind of what happens on the back end of the service event? So we focus on the failure, and then we sort of walk away from the defective activity that happens thereafter.

18:16
Denise McDonell
You know, the bringing back of that defective part, and what did that look like? What does that process look like? And moving that part perhaps back into the service life cycle, there’s a lot of information to the closure of the loop. So these are some of the things that we observe as underutilized data. Opportunities to really start to create insights. And when you start to connect that data, then you begin to see the patterns around cost, around service performance and inefficiencies that could create opportunity.

18:50
Gerardo Pelayo Rubio
That’s really helpful. And I’ll say one of the things I really liked about the way you described it is in most cases you were talking about the questions that you want to address, so not leading with the answers. But hey, we would like to know this thing. How much do we understand about this other part of the process? I absolutely think that’s the right way to start. You brought up the concept of connecting the data. I think most leaders, most people even would agree that at the high, at a high level, connecting data makes sense, should better off if we connect the data. Now the problem is that it takes some effort to actually do this and do this correctly. And where we see many of the service leaders are struggling is how much effort should I put into connecting my data?

19:43
Gerardo Pelayo Rubio
What am I going to get out of it at the other end? Now we know that the pain exists in our last State of AI and Service Technology survey, and we will be releasing the this year’s edition in under a month, by the way. But last results we got, 28% of service leaders said that an insufficient detailed data foundation was the greatest roadblock to scaling their AI efforts. So just as one of the examples of the technologies that has been dominating many of the conversations, it goes back to do I have the right data in the right structure? And that includes the connectedness.

20:21
Gerardo Pelayo Rubio
Can you share perhaps some examples that you’ve seen that you’ve come across where the performance of the service value chain really starts to get to a level of high impact when you move from just data that exists in the organization that is understood and even trusted to actually data that is connected absolutely well,

20:49
Denise McDonell
You’re hitting on a very common problem, right? Because in terms of the fragmentation of the data, because when you think about again, the service event that we just described, there’s usually a number of systems. And those systems typically will sit in a number of different organizations that go into the execution of the event. Whether that is a customer support system, an order management system, a field service system, transportation systems, inventory. There are a lot, and I think it starts first and foremost the recognition that this data, once you can bring it together, will generate specific insights. And I’ll talk a little bit about like some of the key questions that you can ask that will generate insights. You have to first recognize it’s necessary and it is not.

21:39
Denise McDonell
And I do not make light of the fact that bringing that data together and having a company strategy, or even just a service operations strategy around how to do that is a mountain to climb. If that’s not where you are today, many companies are starting to move down the path of creating data warehouse environments and pulling some technology together to bring it together. And so you first have to have that on your roadmap. Right. Like that is a prerequisite. You have to decide that you want to bring that data together and have a plan to do it. But in terms of building the business case as to why you’d want to do it, the real insights that will come when you connect them together are things like a better understanding of whether you’re over servicing or under servicing against your commitments.

22:25
Denise McDonell
And I know that might sound strange because everyone wants to drive the highest level of customer satisfaction that they possibly can. But there’s a real business cost to that. There’s a real business cost to holding inventory idle that you’re not executing in the case that it might get utilized. Or someone who has paid for a two or three day SLA against a service event and you’re delivering it the next day or even the same day, there’s a high cost to that. So understanding like what do your service events and your service level commitments actually cost you as a business? And then why are for, you know, another example could be why are certain parts always being shipped expedited?

23:08
Denise McDonell
There’s a high cost to things like next flight out and expedited shipments that when you actually examine why you’re utilizing those expedited services, it could be as simple as understanding the closer placement that they need to be in or perhaps you are under investing in your inventory in terms of where it’s coming placed. So these are some of the things you can start to look at. On the positive side, when you bring this together, it also exposes opportunity that potentially you could drive more revenue. Right. You can identify where you’ve got customers that are wanting to consume those service parts faster than you’re getting to them. And you can data mine that to determine that you may have a market to actually uplevel your service commitments and make more money. So it’s not always just about cost, but it can also be about revenue.

23:55
Denise McDonell
And so these service supply chains, they generate tremendous amounts of data. And so here those are some of the things that you can ask yourself and ways to start to build the business case around looking at both cost and revenue.

24:08
Gerardo Pelayo Rubio
Yeah, and we’ll get back to that. The dual objective. I love that you touched on the growth. It’s a big trend that we’re seeing this year, by the way. But just want to double click one of the things just spoke about the how and one of the things we’ve noticed in the front line is that trusting data is very different to trusting the intelligence that comes out of the data. And I think that’s one of the jumps that connecting the data in relevant ways is able to achieve. Are there any pitfalls, any best practices that the, that you’ve seen out there to help with the effective consumption of the connected data?

24:50
Denise McDonell
Yes, consumption of the data, I think most of the time and what we observe today is that everyone’s looking at what has happened and they’re looking at it in terms of dashboards. And dashboards are a great way to see what has happened in the past and in order to start to see trending, in order to start to see past patterns and use those dashboards in a way that will allow you to then start to think about the future. But what really starts to pop, if you will, and the insights is when you start to translate those into specific areas where you’ve got anomalies like diving into that data to say, okay, I see the trend, I see the dashboard. However, this is anomaly. Now let’s dive deeper right now, let’s go deeper on that anomaly.

25:42
Denise McDonell
Or as a business being very clear about where your cost drivers are and where your cost objectives are. So that way you focus the insights in those areas. So for example, if your business is very focused on managing your inventory carrying costs, then you want to have the ability to see and predict your inventory carrying costs as it relates to the value of the inventory you’re holding in a particular location, how much money you’re spending to store the inventory in that location, how often that inventory has been moving, where it’s been moving to, and the types of service levels that it’s been consuming, because then you can start to manage that carrying cost at more of an aggregate level.

26:28
Denise McDonell
So seeing a dashboard that tells me I haven’t moved inventory in two years from a particular location is an interesting data point, but it’s when you start to translate that into your overall business objectives and hone in on it in order to then take action is where the consumption becomes different.

26:47
Gerardo Pelayo Rubio
Yeah, you’re preaching to the choir there that there’s a difference between interesting and first off, is it good or bad? Like making sure about that and context matters a lot. The second underlying concept is challenging inertia because dashboards as you say, they give us comfort. We’re used to those, we know them. But what sometimes goes under the radar is that because we’re used to them, we keep asking the same questions rather than thinking about some of these untapped opportunities or challenging for a better way of doing things. And that makes it very hard to really leverage new streams of integrated data. So if I build on that, and some might call it data mining, but I tend to say that incremental improvements, which are great and necessary, but usually that is a better way of dealing with the questions that I have today.

27:54
Gerardo Pelayo Rubio
But if I’m able to ask new questions and I’m able to tackle them in an intelligent way, that is what actually leads to transformation and generating new streams of revenue. For example, as you mentioned earlier, are there any perhaps examples that you might be able to share from your experience on how this process of mining the data, once it’s connected, how has it revealed some blind spots for an organization or inspired some level of innovation?

28:26
Denise McDonell
Sure, sure. Well, I think I can give an example. I think there’s a couple of examples in here. One is the ability to really understand what your service performance actually costs. When you start to bring in performance information like performance data, and you bring in cost data and you bring inventory data, and you look at how you’re delivering your service to your end customer, you’re able to then start to think about and see how much does that service, event and service performance actually cost you. Right? So, for example, if your goal is to always be delivering 98% quality, commitment on time, delivery, getting the part there, the technician is able to address the event and get it closed in that SLA window. And that’s understanding what is the cost of that 98% to you across the entire componentry that makes up that cost.

29:24
Denise McDonell
And then being able to model what if I ratcheted that down half a percentage, would that really impact my CSAT that much? And how much additional cost could I take out of the entire service event process if I ratchet it down half a percent? So that’s part of that kind of data mining. And these are some of, that’s an example some of our customers ask us about. Right. I understand what my quality looks like, but what if I wanted to play with that a little bit or even what if I wanted to segregate that a little bit to a certain segment of customers? Another example of data mining would be on the reverse logistics side.

30:01
Denise McDonell
I love getting into conversation about what happens after the event because again, As I mentioned at the outset, it’s sort of the area that is a little bit forgotten because the urgency is all around getting the event handled obviously as it should be. And then there’s just, there’s not as much urgency on the back end. Right. Perhaps you may need to do failure analysis quickly, but you know, most of the time that’s not really the case. And so we see an opportunity with data mining where you can really start to use information at your disposal to determine what to do with that asset.

30:35
Denise McDonell
So for example, many customers and many companies, they’ll have global operations where they’ll have a defective part that comes back into a centralized location in a country and they need to make a decision what to do with that defective part. And typically a decision will be, well, let’s repair it, right? And nine times out of 10 means you’re exporting it out of that country, you’re moving it out of the country because you need to repair it. And nine times out of 10, unless you repair vendors in the same country. And so there’s a cost to exporting it, there’s a transportation cost to exporting it, there’s a cost to repairing it, there’s a cost to importing it back in and putting it back on the shelf.

31:13
Denise McDonell
If you’re able to analyze that cost profile and balance it up against looking at the inventory utilization across your network. Do I have a shortage of this part elsewhere or am I overstocked? Where is it in his life cycle? Is it about to go end of life? Those data points and mining those out will allow you to then make an intelligent decision in the moment that it makes more sense to scrap it in field than it ever would to ship it off to repair. And which would be the rote routine that most companies are in. Defect repair, defective repair. And so this is where I think a great example of data mining allows you to make an intelligent decision on the fly.

31:54
Gerardo Pelayo Rubio
It is. And to those listening on the recorded session already, I would encourage you to go back and re listen to the last two minutes of what Denise just said. I think it’s pure gold. Because one of the things that we hear about quite often in the industry is, hey, I want to move away from being a transactional service organization and really start to manage the customers and manage the assets. And what you walked us through, in my view, it’s an example of that of thinking broader. But you cannot just be ambitious. You need the tools to do that. And in this case those tools is the connected data. So I, I Was really enjoying it as we’re putting it all together. I enjoyed it so much that I’ll ask you a follow up on that because service innovation is.

32:47
Gerardo Pelayo Rubio
It was in fact the number one focus area that service leaders called out last year in our service agenda. 47% of them included it in their top three activities for the year. And on paper it sounds nice, but what does it really mean to move from this transactional relationship towards intelligence driven management of customers and assets? How do you communicate that? It’s not always that easy. So if you took a step back from what you just shared, is there any element that organizations tend to miss as they want to make this jump? Any pitfalls to avoid, any pre requirements to be successful in this transformation?

37:12
Denise McDonell
Sure, sure. I mean if you think about the way that service supply chains typically work, it is a very transactional set of activities, right? And so traditionally it has been very transactional. Something fails, you ship apart, you ship a 10 technician, you fix it, right? That’s, that’s sort of the standard routine as I mentioned earlier in the example. Like that’s a great example of where you can evolve it from being just a transactional set of activities to seeing it as a holistic system. Because truly that’s ultimately where I think customers want to go, companies want to go is they want to look at this as a holistic system. And that includes even to the point of the way that the relationships work with your end customers who are the ones that are experiencing the service effect.

37:57
Denise McDonell
A great example of that is some of our customers are starting to look at the way their customers consume that delivery. You know, so for example, there are some customers who look at their profile of installed base clients and they notice that some customers are purchasing, you know, next business day service event contracts, but then always escalating to say but I need it today because I’m going to be able to have people on sale site today to let the field technician in. So I know I bought next business day, can you get it to me today? And then you’re able to look at the data, you’re able to see that data and you’re able to see consistently this is what happens with that customer.

38:37
Denise McDonell
This is a great opportunity to go have a conversation and say hey, you know what, you should actually be purchasing a four hour SLA because we’re going to have to stop executing that service for that. You know you need it, right? You need it in that same day. And here’s where all the data is telling us that you need it. And so that’s where you move beyond this just being a transactional moving apart, shipping apart, fixing apart to kind of relating it to your client, looking at their environment, mining the data of the customer experience, correlating that to the execution activities and then creating a relationship with that data. So it’s not Just relationship in terms of how you execute against the event, but it’s also the experience your customer receives.

39:20
Gerardo Pelayo Rubio
Yeah, and I would, I, I would add one comment in what you said just to emphasize the point. Anybody can design a new service contract, right, and can imagine it and say, hey, let’s move our customers towards that. That doesn’t mean that it’s going to be profitable. That doesn’t mean that the customers need it or will like it. So what you just spoke about it, how to do that responsibly, how to do that in a way that, where you feel confident that this is the right thing to do, not just that you’re convincing the customer, but you have the intelligence to know that this is the right thing to do. And you know, many of the examples of benefits that we’ve been talking about have to do with efficiency, having the right inventory, not having too much excess capacity.

40:09
Gerardo Pelayo Rubio
From that perspective, thinking about the logistics costs, including the reverse logistics and all of that is great and hugely necessary. But you touched on growth earlier and I’m really glad you did because in this year’s service agenda, we’re still collecting data on that. But over three in five service leaders have identified their fundamental mandate for 2026 as growth over efficiency, over resiliency, over modernization. How is it that some of the enablers that we’ve been talking about in order to move towards these intelligence driven service organizations, how can they be applied towards supporting this growth strategy? If you can share your thoughts or any examples that you have around that.

40:56
Denise McDonell
Sure. Well, first of all, I love that your survey is showing that’s what service leaders are thinking about because it really does start there. Service leaders need to be thinking about their business as an opportunity for growth and not just as a cost center in the organization, which is, you know, traditional thinking. So that’s exciting. I think with some of these topics that we’ve discussed here. In terms of the data that the service area generates, when you start to understand that service data more deeply, when you start to recognize the value that can be harnessed from it will allow the organization to think more intelligently about designing better service offerings. To your point earlier. Right. It allows you to really hone in and think where are these service offerings and how do I design them that are best for us and for the customer?

41:50
Denise McDonell
It will allow them to think about expanding this levels into new markets. I can tell you that we are observing with hyperscaler and data center growth in the AI space, there’s Definitely a different expectation that some of these hyperscaler companies in Amazon Meta, the large data center providers, Microsoft, their expectations are very different than maybe perhaps some of the other companies in the data center space. And thinking about how you customize your service levels when you’ve got those as your customers is something that the data will allow you to start to harness. This is really timely in today’s market. And then I think also optimizing your network to support a faster response.

43:44
Speaker 3
She says this sucks and she’s sorry.

43:50
Gerardo Pelayo Rubio
It’s okay. I, so I, I think also optimizing your network like that, that’s the phrase that she, that I last heard.

44:02
Denise McDonell
Yes.

44:02
Gerardo Pelayo Rubio
So if she does come back, we’ll just pick it up from there.

44:06
Speaker 3
Okay. So, yeah, she’s in the middle of nowhere. And you know, I’ll tell you, for her to have to like go into the city to go to Costco, to go the doctor It’s a three hour drive into the city. So when she travels it’s like, okay, she’s all over, she’s going to Germany next week, then she comes back into Canada and then, you know, you got to do all that stuff coming back in the country customs, and then she has to hop in her car and drive three hours home. I don’t know how she does it, but she’s in a beautiful area.

44:44
Gerardo Pelayo Rubio
Yeah, yeah. As she was describing it. So here she’s back in. We’ll do this quickly.

44:49
Speaker 3
Okay.

44:50
Gerardo Pelayo Rubio
All right. Dennis. Last thing I heard was, I think when you also think about optimizing your resources, so we’ll just take it whenever you’re ready, take it from there and keep going.

45:03
Denise McDonell
Okay. So lastly, an opportunity is to optimize your networks to support faster response. So it does dovetail into the hyperscaler example and where we’ve seen that’s like not just an opportunity to increase your service levels, but also when you do that, then you can optimize your network in order to make sure that you’ve got the right inventory placed in the right locations specifically against each one of those service contracts and those new services levels. And so it’s an overarching or perhaps foundational element to support that growth. So in my opinion, the organizations that will win as we start to think through service as a revenue opportunity is those that treat it as a strategic asset, not just an operational necessity.

45:49
Gerardo Pelayo Rubio
Again, fully agree. And I, I would simply add that what you talked about was the direct, that most of what you talked about was the direct benefits Which I appreciate. There’s even a lot of indirect benefits. Like we think about customer retention, we think about the ability to command a premium and then that starts feeding into the revenue, the recurring revenue and the profitability conversation at an organization for sure. Really insightful, Denise. I’ve greatly enjoyed today’s conversation. Before I let you go, is there anything that you’d like to share about yourself? Any passion project that you have coming up?

46:27
Denise McDonell
Oh, sure, I don’t know that I have a passion project coming up, but I will say myself and my family were very outdoor people and so we embrace every season when we you live on the east coast of Canada, you definitely experience every season. So we just put away our snowmobiles for the winter and we’re bringing out our side by sides and our dirt bikes and so we’re getting really excited to get back onto some of the mountain adventures we like to camp when we head out on our side by sides and dirt bikes. And so we’re getting excited about that. So I’m really excited for spring to come so we can get back on our machines.

47:07
Gerardo Pelayo Rubio
That, that, that sounds really fun. You could also be working for the tourism industry of Nova Scotia on your free time. I, I, I, I, I, I, I feel motivated to go after talking to so.

47:21
Denise McDonell
Oh, it’s a beautiful place. You should come visit.

47:23
Gerardo Pelayo Rubio
Yes Yes. I, I tell you do a good job at with the pitch. Denise really enjoyed the conversation. Once again, thank you for stopping by to our audience. Thank you for listening. Once. Once again, reminder that today’s podcast was recorded so you can revisit it on all of our social platforms and we hope to continue seeing you in the next events. Have a great rest of the week.