Transcripción completa de Engineering Resilient Supply Chains, AI Integration, and Leadership with Kerry McCarthy

worked my way up to my current role as fellow. 00:01:59.935 --> 00:02:03.597 Kerry, I want to take you all the way back to 20 years ago when you were that, 00:02:04.057 --> 00:02:10.761 first co-op student at LMI and now growing into this role of supply chain resilience fellow. 00:02:11.150 --> 00:02:16.447 You look back across two decades of systematic shifts from lean optimization 00:02:16.447 --> 00:02:19.341 to post-pandemic risk mitigation, 00:02:19.771 --> 00:02:25.175 how has your definition or LMI's definition of supply chain resilience evolved 00:02:25.390 --> 00:02:31.517 from this kind of nice-to-have efficiency metric into what is now a national 00:02:31.517 --> 00:02:33.690 security and business imperative? 00:02:34.119 --> 00:02:38.267 The shift in focus has been pretty wide, and it's really gone from that supply 00:02:38.267 --> 00:02:42.833 chain as a cost and just the cost of doing business and really efficiency focus 00:02:43.071 --> 00:02:44.986 to now really a strategic asset. 00:02:45.323 --> 00:02:48.607 And so what's really changed is our understanding of the consequences of really 00:02:48.607 --> 00:02:53.752 optimizing that too far in one direction, that just-in-time model to now just-right model. 00:02:54.112 --> 00:02:57.417 And really over the past two decades, we've seen a lot of natural disasters, 00:02:57.837 --> 00:03:02.018 political disruptions, cyber events, the pandemic, you name it, it's happened. 00:03:02.210 --> 00:03:07.446 And a supply chain really could appear highly efficient, but still be extremely fragile. 00:03:07.701 --> 00:03:11.187 So today, resilience is really much more about the understanding of where those 00:03:11.187 --> 00:03:15.707 vulnerabilities exist and having the options and decision-making power for when 00:03:15.707 --> 00:03:18.783 something goes wrong or preventing them from actually impacting the business. 00:03:19.485 --> 00:03:24.536 Really looked at a lot of visibility, a lot of analysis and trade-off analysis overall. 00:03:24.925 --> 00:03:28.300 And so for the private sector, this has become a lot more than just a business 00:03:28.300 --> 00:03:30.485 continuity. It's a competitive issue now. 00:03:30.839 --> 00:03:34.660 And then for the public sector, it's very much a national security issue where 00:03:34.660 --> 00:03:38.140 if you're not able to get the parts, you cannot deliver that operational readiness 00:03:38.140 --> 00:03:39.413 that the government really needs. 00:03:39.819 --> 00:03:43.140 So that really, the biggest evolution of resilience is change from the view 00:03:43.140 --> 00:03:48.650 of risk management to supply chain as the foremost area that really operates 00:03:48.650 --> 00:03:49.833 the business model overall. 00:03:50.355 --> 00:03:55.243 And so getting that optionality, which is just a take on flexibility, has been that key shift. 00:03:55.655 --> 00:03:59.110 And it's not just me. There's been a lot of recent reports on risk management, 00:03:59.110 --> 00:04:00.520 resilience, and flexibility. 00:04:00.845 --> 00:04:05.650 And what that's really shown here is that 74%, just based on a World Economic 00:04:05.650 --> 00:04:09.770 Forum report recently, now view resilience as a driver of growth. 00:04:09.770 --> 00:04:12.211 So it's not merely that risk management mechanism. 00:04:12.547 --> 00:04:16.550 We've moved really from how much does resilient cost us to asking, 00:04:16.550 --> 00:04:18.585 what does resilience enable us to do? 00:04:19.229 --> 00:04:22.793 So, Carrie, your focus is supply chain risk management, obviously, 00:04:23.055 --> 00:04:25.763 and the great work that you're doing there at LMI. 00:04:26.175 --> 00:04:29.856 In your published perspective, specific to resilient supply chains, 00:04:30.134 --> 00:04:35.048 as a strategic advantage, you note that resilience serves as both shield and 00:04:35.048 --> 00:04:38.348 signal, and you emphasize it must be done economically. 00:04:38.923 --> 00:04:43.190 Not every supplier or component or node can have redundancy built around it. 00:04:43.579 --> 00:04:46.220 There's obviously challenges and different reasons why. 00:04:46.806 --> 00:04:50.958 So how should leaders decide where to invest in resilience? And a second part 00:04:50.958 --> 00:04:53.430 to that question is, and where do they accept the risk? 00:04:53.929 --> 00:04:57.348 Yeah, I think most leaders recognize that resilience cannot mean redundancy 00:04:57.348 --> 00:05:02.741 everywhere. That's just not economically sustainable or even achievable in most cases. 00:05:02.967 --> 00:05:06.458 So the objective really is to understand where disruption matters the most and 00:05:06.458 --> 00:05:09.272 where to invest deliberately in those areas. 00:05:09.608 --> 00:05:13.748 I tend to think of that through kind of three questions. How critical is the item or capability? 00:05:14.068 --> 00:05:17.958 How vulnerable is that supply chain that supports it, and what is the consequence 00:05:17.958 --> 00:05:19.192 of that being disrupted. 00:05:19.506 --> 00:05:22.758 And I'm a huge advocate of doing pre-mortems, which is basically kind of doing 00:05:22.758 --> 00:05:27.138 a post-mortem analysis to identify what went wrong beforehand and kind of assume 00:05:27.138 --> 00:05:29.344 a failure and dissect what could go wrong. 00:05:29.808 --> 00:05:32.728 And so you can look at criticality again, you can look at vulnerability, 00:05:32.728 --> 00:05:36.896 you know, the sub-tier vendors, long lead times, and understand the consequences, 00:05:37.367 --> 00:05:41.587 really creating that huge fixture of everything that you need so that you can 00:05:41.703 --> 00:05:44.780 make those much informed investment decisions. 00:05:45.110 --> 00:05:48.686 A highly critical component with a single source, little inventory, 00:05:48.930 --> 00:05:53.688 and an 18-month recovery time deserve a way, way different level of attention 00:05:53.688 --> 00:05:57.475 than

a component where there are five qualified suppliers and substitute readily available. 00:05:57.864 --> 00:06:01.378 And coming up with that heuristic as an organization, understanding what's important, 00:06:01.378 --> 00:06:05.428 what's not important, and that mission thread is really the biggest decision 00:06:05.428 --> 00:06:06.618 for an organization to make. 00:06:07.042 --> 00:06:09.219 That's where kind of the economics become really important too. 00:06:09.729 --> 00:06:13.222 For each vulnerability, we really need to be looking at what does that mitigation 00:06:13.222 --> 00:06:16.283 cost? How much risk does it actually reduce? 00:06:16.620 --> 00:06:20.772 What capability does it preserve? Essentially, you're building that portfolio 00:06:20.772 --> 00:06:22.402 of resilience investments and 00:06:22.402 --> 00:06:25.529 then putting the resources that generate the greatest reduction overall. 00:06:25.820 --> 00:06:29.703 There's really much both a supply chain problem and an economics problem overall. 00:06:30.086 --> 00:06:33.389 And that's why it's talking about kind of the resilience of the shield and a signal. 00:06:33.738 --> 00:06:37.822 The shield is really building that ability to absorb and recover from that disruption, 00:06:37.822 --> 00:06:41.572 understanding all the options you have and which ones you can delay for later 00:06:41.572 --> 00:06:42.631 and which ones you can do now. 00:06:42.927 --> 00:06:47.172 And that signal is really both a signal to everyone else that you actually understand 00:06:47.172 --> 00:06:51.100 your supply chain well enough to know that you are vulnerable and that you do have options. 00:06:51.489 --> 00:06:55.402 And so from a national security perspective, that signal is also good to note 00:06:55.402 --> 00:06:58.780 because we're showing that we are willing to invest to make ourselves resilient. 00:06:59.152 --> 00:07:03.024 So the goal is not a risk free supply chain. That's never going to happen in this world. 00:07:03.459 --> 00:07:05.636 It's a supply chain where risks do matter. 00:07:06.158 --> 00:07:09.682 They're understood, prioritized, and managed economically. 00:07:10.326 --> 00:07:14.382 Really, really interesting stuff. Now, I want to switch gears a little bit to 00:07:14.822 --> 00:07:18.832 more of your personal leadership philosophy, which you framed up as the lead 00:07:18.832 --> 00:07:24.862 framework, which is learning, evolving, analyzing, and delivering alongside the golden rule of, 00:07:25.362 --> 00:07:29.252 listen first and use two ears and one mouth in that ratio. 00:07:29.252 --> 00:07:36.102 So How do you instill that discipline and that mindset in a cross-functional 00:07:36.102 --> 00:07:43.565 risk and analytics team when managing high-stakes crisis is such a critical response? 00:07:44.291 --> 00:07:49.371 Any good supply chain resilience effort is multifunctional in terms of the functions, 00:07:49.371 --> 00:07:53.590 so procurement, engineering,

and so forth, and the skill sets, 00:07:53.724 --> 00:07:56.516 policy, data engineers, subject matter experts. 00:07:57.004 --> 00:08:00.921 And that kind of lead mindset needs to apply to those cross-functional teams, 00:08:00.921 --> 00:08:04.039 because without that cross-functional expertise, you will fail. 00:08:04.631 --> 00:08:08.579 I'm an engineer by trade, so I have a very big engineering mindset. 00:08:09.049 --> 00:08:13.809 And so I think in a crisis, there's a natural tendency to move immediately into action mode. 00:08:14.163 --> 00:08:18.021 But what I have found is that the quality of that response really depends on 00:08:18.021 --> 00:08:21.830 what happens before the action or before that first step is taken. 00:08:22.179 --> 00:08:28.169 And it largely revolves around whether the team has had and done the reps on the critical thinking. 00:08:28.524 --> 00:08:32.081 And to really be able to listen carefully to one another, actually understand 00:08:32.081 --> 00:08:36.772 the problem, and quickly separate what we know from what we assume and what we need to go gather. 00:08:37.389 --> 00:08:41.307 In fact, one of the recent World Economic Forum reports that was just put out, 00:08:41.574 --> 00:08:44.247 it did actually highlight critical thinking as one of those key skills. 00:08:44.247 --> 00:08:47.357 And I talk about that with a lot of college students that, you know, 00:08:47.357 --> 00:08:50.740 in the era of AI, you cannot outsource your critical thinking to AI. 00:08:50.874 --> 00:08:54.927 And you really need to get those reps with the team, with each other prior to 00:08:54.927 --> 00:08:56.261 an event actually happening. 00:08:56.650 --> 00:08:59.437 And I think that remains really true in this space in supply chain, 00:08:59.437 --> 00:09:04.092 where there's a lot of gray area, a lot of uncertainty, and we really can't outsource everything. 00:09:04.225 --> 00:09:08.095 We actually have to collaborate as a team, and supply chains are run by humans at the end of the day. 00:09:08.513 --> 00:09:13.244 So kind of breaking down that lead concept, for me, learning really starts with curiosity. 00:09:13.487 --> 00:09:16.377 In a cross-functional team, we have the supply chain analysts, 00:09:16.377 --> 00:09:19.887 we have the engineer, we have the program manager, we have the data scientist, 00:09:19.887 --> 00:09:21.607 we have the UI, UX designer. 00:09:21.961 --> 00:09:25.487 They all see different parts of the problem. And so my job as a leader is not 00:09:25.487 --> 00:09:29.607 to just assume I have the complete picture. It's to make sure those perspectives 00:09:29.607 --> 00:09:32.881 are heard, particularly from the people closest to the issue, 00:09:33.182 --> 00:09:34.959 those people that are in the belly of the beast. 00:09:35.417 --> 00:09:39.504 And that's where the idea of two ears, one mouth, and that ratio really matters. 00:09:39.852 --> 00:09:44.407 The E, the evolving, means really being willing

to change the plan as new information 00:09:44.407 --> 00:09:48.107 becomes available. Again, in supply chain, we do not have a perfect picture. 00:09:48.107 --> 00:09:52.821 We have a maybe 480 resolution picture. We want to get to that 8K resolution. 00:09:53.285 --> 00:09:56.635 So during a disruption or crisis, the situation changes rapidly. 00:09:56.803 --> 00:10:01.747 And a good team really cannot become overly attached to that first hypothesis 00:10:01.747 --> 00:10:04.471 they have or that first course of action that their gut told them. 00:10:05.034 --> 00:10:09.371 We really need enough discipline to say, this is what we believed yesterday. 00:10:09.580 --> 00:10:11.983 This is what the data tells us today. Let's go explore it. 00:10:12.465 --> 00:10:16.225 We might do something differently. Trust your gut, but also be informed by information. 00:10:16.817 --> 00:10:21.659 Then we moved to the E, the analyzing side. That's really about bringing structure to the uncertainty. 00:10:22.053 --> 00:10:26.197 One of my favorite undergrad classes was a class called unstructured problem 00:10:26.197 --> 00:10:28.950 solving. It actually really taught me how to break down problems. 00:10:29.246 --> 00:10:34.935 It really taught me critical thinking and that thought process and problem decomposition. Does that art. 00:10:35.550 --> 00:10:38.901 You would not think an engineer would have with the science of engineering and 00:10:38.901 --> 00:10:42.435 really breaking the problem into sub-problems until you can actually define 00:10:42.591 --> 00:10:44.467 the actual problem that is at the end. 00:10:44.943 --> 00:10:48.955 And then there's delivering. At some point, analysis has to turn into action. 00:10:49.373 --> 00:10:52.321 Even analysis by itself that doesn't turn into action is useful, 00:10:52.321 --> 00:10:54.795 but it's not changing the supply chain landscape. 00:10:55.404 --> 00:10:58.452 In the supply chain world, it's critical not just to admire, 00:10:58.632 --> 00:11:01.767 sit back and admire that problem, but it's to get to a decision. 00:11:02.039 --> 00:11:05.561 And I do sometimes feel in the supply chain risk world and supply chain resilience 00:11:05.561 --> 00:11:09.471 world, we spend a lot of time binding the problems, but we forget that we have 00:11:09.471 --> 00:11:11.197 to deliver on those decisions. 00:11:11.685 --> 00:11:15.859 And really at the key of this, kind of that whole concept is humans must stay in the loop. 00:11:16.196 --> 00:11:19.401 There are a lot of different nuances to supply chain. I think leaders have to 00:11:19.401 --> 00:11:22.662 create that environment where people are comfortable challenging the assumptions. 00:11:23.045 --> 00:11:27.321 And in a crisis, I'd rather much someone say to me, I think we're missing something 00:11:27.321 --> 00:11:31.306 than just have that team quietly align over a flawed conclusion. 00:11:31.515 --> 00:11:35.213 And that requires trust and trust is built before that crisis appears. 00:11:36.075 --> 00:11:38.693 Keri, you mentioned a few things there that are interesting, 00:11:38.919 --> 00:11:42.373 different perspectives as part of the problem, having those different perspectives, 00:11:42.779 --> 00:11:44.469 and humans staying in the loop. 00:11:44.718 --> 00:11:49.891 You also mentioned AI and critical thinking, a lot going on in AI in these days. 00:11:49.891 --> 00:11:55.101 And let's talk about what LMI has done. So LMI was tasked with developing various 00:11:55.101 --> 00:11:58.761 tools for the Department of War to identify and mitigate supply chain risk for 00:11:58.761 --> 00:11:59.945 critical defense assets. 00:12:00.692 --> 00:12:05.351 Tell us how our advanced AI, machine learning, and multi-tier mapping moving 00:12:05.351 --> 00:12:10.054 supply chain risk management from problem solving to predictive risk mitigation. 00:12:10.793 --> 00:12:15.158 So traditionally, supply chain risk management has been a very reactive process. 00:12:15.303 --> 00:12:18.508 A supplier misses a delivery, a material becomes unavailable, 00:12:18.792 --> 00:12:22.815 a disruption occurs, and then really the organization begins trying to understand 00:12:23.059 --> 00:12:26.184 what happened, what programs are affected, what options exist. 00:12:26.184 --> 00:12:29.346 It's very much a look-back focused initiative. 00:12:29.793 --> 00:12:32.852 So really the first step in many good SCRIM programs is visibility. 00:12:33.421 --> 00:12:36.288 You really need to answer who is in my supply chain. 00:12:36.654 --> 00:12:39.214 I'm not going to go into detail on kind of the various methods, 00:12:39.214 --> 00:12:43.224 but one thing I'll say is it's largely people-driven to get the high-quality 00:12:43.224 --> 00:12:45.513 data that you need to make good decisions. 00:12:45.896 --> 00:12:48.514 And there is a trust factor within industry on sharing that data, 00:12:48.854 --> 00:12:51.886 and the relationships can't be just merely transactional. 00:12:52.473 --> 00:12:55.014 And there are ways to gather that data at scale, but at the end of the day, 00:12:55.014 --> 00:12:58.054 there still is some relationship you have to build with those suppliers to gather 00:12:58.054 --> 00:12:59.706 that in-depth data that only they know. 00:13:00.368 --> 00:13:04.674 But once you have that high-quality data, that is really where advanced AI, 00:13:04.674 --> 00:13:09.714 machine learning, can really move the needle on better decisions and move from 00:13:09.714 --> 00:13:13.253 a reactor problem-solving to a predicted risk mitigation area. 00:13:13.642 --> 00:13:17.224 I've done some recent projects looking at predicting on-time delivery based 00:13:17.224 --> 00:13:18.896 on a variety of different factors. 00:13:19.499 --> 00:13:23.151 What was interesting about that project wasn't that the prediction did really well. 00:13:23.400 --> 00:13:29.205 It was really focused on how we could enable those item managers

to triage problems 00:13:29.397 --> 00:13:32.926 that would mostly impact them and make them 5% better. 00:13:33.292 --> 00:13:38.094 Because 5% better at scale over a long period of time is a real difference in 00:13:38.094 --> 00:13:39.492 millions and millions of dollars. 00:13:39.927 --> 00:13:43.236 So you always don't have to aim for perfection. You have to aim for business 00:13:43.544 --> 00:13:46.858 decisions that make sense from kind of a cost analysis perspective. 00:13:47.525 --> 00:13:52.473 We also look at things like AI, large language models, that adds another really 00:13:52.473 --> 00:13:56.903 unique dimension because so much of our valuable supply chain data is locked 00:13:56.903 --> 00:14:00.639 behind unstructured data. It is on people's laptops. It's in notes. 00:14:01.260 --> 00:14:05.813 Engineers, buyers, cargo managers, suppliers all describe essentially kind of 00:14:05.813 --> 00:14:08.765 the same problem, but in vastly different ways. 00:14:09.421 --> 00:14:14.889 We have used a lot of large language models to do a lot of semantic normalization 00:14:15.318 --> 00:14:18.830 across different notes, reports, and other text sources, 00:14:19.324 --> 00:14:25.033 turning that disparate observation data into structured signals that can be 00:14:25.033 --> 00:14:28.682 combined with quantitative data that someone will view in a dashboard. 00:14:29.192 --> 00:14:33.413 So recently, we've deployed some large language models to extract raw notes 00:14:33.413 --> 00:14:36.234 on millions of parts to understand what was going on. 00:14:36.768 --> 00:14:40.043 It was really insightful at the macro level as well as the micro level. 00:14:40.043 --> 00:14:43.253 So it gave leaders the information they needed to understand what was bubbling 00:14:43.253 --> 00:14:45.441 up, what was emerging, what required their attention. 00:14:46.078 --> 00:14:50.234 And the last part, which is not necessarily kind of AI or machine learning, 00:14:50.798 --> 00:14:53.334 is bringing all that data together to make a decision. 00:14:53.613 --> 00:14:58.216 And for that, LMI leverages a lot of modeling and simulation. 00:14:58.884 --> 00:15:03.013 Instead of simply saying this supplier is high risk or we have an issue over 00:15:03.013 --> 00:15:05.500 here, we ask a little bit more useful questions. 00:15:05.843 --> 00:15:09.244 Like, if this supplier goes down, what parts and systems are affected? 00:15:09.836 --> 00:15:12.083 What will that actually look like? What's our service level? 00:15:12.083 --> 00:15:13.076 What's our readiness rate? 00:15:13.575 --> 00:15:17.693 When do inventories begin to run out? What is the impact? How long would recovery 00:15:17.693 --> 00:15:22.201 take? What options do I have that I can pull? What are the levers available to me? 00:15:22.718 --> 00:15:25.568 And one of those mitigations, whether it's adding inventory, 00:15:25.789 --> 00:15:29.480 increased capacity, finding alternative source, re-engineering,

00:15:30.061 --> 00:15:32.847 doing a different material, provides that greatest benefit. 00:15:33.225 --> 00:15:37.473 It's one of our platforms we have in LMI, Raptor, really has been used to answer 00:15:37.473 --> 00:15:42.083 a lot of those questions at scale in both government and industry to optimize 00:15:42.083 --> 00:15:48.196 things like sparing, conduct trade-off analysis, and optimize investments in the industrial base. 00:15:48.823 --> 00:15:53.533 And one thing I want to point out, too, is as much as AI is really helpful in 00:15:53.533 --> 00:15:58.262 speed, you still need a supply chain professional to help make that decision. 00:15:58.936 --> 00:16:03.712 And the role of our tools that we have developed isn't to replace those humans, 00:16:04.043 --> 00:16:05.323 it's to get better decisions. 00:16:05.323 --> 00:16:10.593 And that's really the key metrics I focus on is not optimizing all the resources 00:16:10.593 --> 00:16:14.120 that are used to make it, but it's, am I providing better decisions? 00:16:14.254 --> 00:16:16.477 Am I providing better decisions faster? 00:16:16.936 --> 00:16:19.664 We shouldn't make mistakes faster. We should have better decisions faster. 00:16:19.989 --> 00:16:23.473 And so that's one of the things I always talk to my team about is getting better 00:16:23.473 --> 00:16:27.809 decisions with the data we have that improves incrementally over time. 00:16:28.244 --> 00:16:33.753 Not everything has to be a 30% improvement. 5% at scale is a big, big improvement. 00:16:34.455 --> 00:16:42.661 Now, Kerry, those are amazing kind of lessons to port over into the commercial side of the world. 00:16:42.661 --> 00:16:47.251 But I want you to reflect a little bit on some of these amazingly complex public 00:16:47.251 --> 00:16:50.031 sector entities that you've worked with, Department of War, NASA, 00:16:50.031 --> 00:16:55.041 Department of Agriculture, FEMA, et cetera, and talk about how some of their 00:16:55.361 --> 00:16:57.257 risk management strategies 00:16:57.687 --> 00:17:01.778 could apply in the commercial or private sector industries. 00:17:02.241 --> 00:17:04.674 And the things that they overlook and the things that they overlook. 00:17:05.423 --> 00:17:09.489 One of the biggest lessons from government logistics that I've kind of learned 00:17:09.489 --> 00:17:15.628 over the years is that you just cannot design a supply chain only around normal operating conditions. 00:17:16.110 --> 00:17:20.999 In many public sector missions, the question is not simply what is the most 00:17:20.999 --> 00:17:22.635 efficient way to operate. 00:17:22.948 --> 00:17:27.609 It is, can the mission still succeed when transportation is constrained? 00:17:27.609 --> 00:17:30.396 Demand surges in a way you did not have imagined. 00:17:30.785 --> 00:17:35.469 A supplier fails. Infrastructure is damaged that you depended on or information is incomplete. 00:17:35.916 --> 00:17:41.259 And so that concept of expecting disruption is really ingrained in that public 00:17:41.259 --> 00:17:43.161 sector supply chain design. 00:17:43.521 --> 00:17:47.875 And I think that mindset really leads to a few important lessons for commercial supply chains. 00:17:48.322 --> 00:17:51.659 The first is to really focus on consequence, not just probability. 00:17:51.659 --> 00:17:54.428 We like to talk about, hey, this is a 45% probability. 00:17:54.788 --> 00:17:57.986 But if you really focus on the consequence to your organization, 00:17:58.438 --> 00:18:05.085 you now have a same level and mindset to focus on what it actually means to you as an organization. 00:18:05.468 --> 00:18:09.149 Organizations naturally spend time on risks that are most likely to occur. 00:18:09.619 --> 00:18:13.079 But really, some of the most important risks that we've seen were not something 00:18:13.079 --> 00:18:15.459 you would plan or that we even widely imagined. 00:18:15.946 --> 00:18:19.919 And so they're that low probability, high consequence. So government organizations 00:18:19.919 --> 00:18:24.039 are really forced to ask those questions. What happens if a critical capability 00:18:24.039 --> 00:18:27.701 becomes unavailable? What are we going to do about it? What do we do to prevent that? 00:18:28.061 --> 00:18:34.058 What do we do to combat that in a way that gives us options to implement a different mitigation? 00:18:34.621 --> 00:18:38.359 Commercial organizations can benefit from that same discipline. 00:18:39.049 --> 00:18:42.846 The second area that I see is common mode failures, essentially. 00:18:43.426 --> 00:18:47.411 You may believe you have redundancy in the supply chain because you have two 00:18:47.411 --> 00:18:49.115 or three or four suppliers. 00:18:49.422 --> 00:18:52.122 But really, at the end of the day, it often looks like an hourglass. 00:18:52.372 --> 00:18:57.594 That same three or four suppliers often depend on the same sub-tier manufacturer, 00:18:57.809 --> 00:19:02.447 same port that it all goes through, same geographic region, the same critical material. 00:19:02.853 --> 00:19:06.963 And so you actually may not attribute redundancy at all. What you've done is 00:19:07.108 --> 00:19:09.088 you've created this illusion of redundancy. 00:19:09.343 --> 00:19:12.263 So the government is really focused on mapping its supply chain, 00:19:12.495 --> 00:19:17.070 understanding its bottlenecks, and attacking those bottlenecks to make investments. 00:19:17.604 --> 00:19:23.801 The government you've seen recently is making large investments in unlocking 00:19:23.801 --> 00:19:29.022 that capacity and making investments to benefit both industry and the government 00:19:29.254 --> 00:19:31.089 and ultimately its customers. 00:19:31.460 --> 00:19:35.751 So what I've seen is a very interesting kind of mindset of really focusing on 00:19:35.751 --> 00:19:39.535 that same core idea of identify the bottlenecks. 00:19:39.756 --> 00:19:44.109 Use the term Herbie, if you will,

which is based on an old book, The Goal. 00:19:44.411 --> 00:19:48.655 So understand that limiting factor and ruthlessly attack that and then move on to the next one. 00:19:48.852 --> 00:19:52.011 And you'll solve one problem at a time and one problem at a time until you get 00:19:52.011 --> 00:19:53.756 to that end state that you're looking to achieve. 00:19:54.069 --> 00:19:57.251 I think there's a great quote from General Eisenhower, which I think is really 00:19:57.251 --> 00:20:01.790 relevant here too, which is, plans are nothing, planning is everything. 00:20:02.254 --> 00:20:05.341 And at the end of the day, the plan usually goes out the door the moment something 00:20:05.341 --> 00:20:09.391 happens. It's all the pre-work, it's all the cognitive thought that has gone 00:20:09.391 --> 00:20:12.825 through that, that planning process that's really, really critical. 00:20:13.400 --> 00:20:17.291 This is something the Department of War has spent decades working on, 00:20:17.291 --> 00:20:21.695 on that planning process that I think commercial industry would definitely benefit. 00:20:22.449 --> 00:20:26.576 Carrie, over the years, you've done a lot of metric and analytics work, 00:20:27.012 --> 00:20:30.739 whether that was analyzing metrics with the government or conducting research on disaster recovery. 00:20:31.284 --> 00:20:35.040 For commercial supply chain executives, many that are listening today, 00:20:35.394 --> 00:20:36.880 they might be overwhelmed by data. 00:20:37.095 --> 00:20:41.862 What key performance indicators truly signal whether an enterprise is genuinely 00:20:41.862 --> 00:20:43.811 recovering or just treading water? 00:20:44.488 --> 00:20:47.432 So there are a lot of standard metrics out there for resilience, 00:20:47.432 --> 00:20:50.621 time to recover, time to survive, time to impact. 00:20:50.987 --> 00:20:54.502 Well documented out there. But I think it's an interesting thing as a leader, 00:20:54.502 --> 00:20:58.911 though, to determine whether you are just generally recovering or treading water 00:20:59.166 --> 00:21:01.244 is look at your time, your time as a leader. 00:21:01.738 --> 00:21:05.972 If everything is still in crisis mode, if you're spending those days in reactive 00:21:05.972 --> 00:21:10.222 meetings, chasing shortages, figuring out what to expedite, solving that same 00:21:10.222 --> 00:21:14.222 problem over and over and over again, you are in survival mode at that point. 00:21:14.222 --> 00:21:15.548 You are not really improving. 00:21:15.861 --> 00:21:18.259 You're just spending your time reacting to the fire of the day. 00:21:18.613 --> 00:21:22.192 And so to me, recovery piece is moving in the direction where you spend more 00:21:22.192 --> 00:21:24.917 time on preparation, on looking ahead. 00:21:25.300 --> 00:21:30.092 Your emergencies, shorter recovery times, more options are available to you. 00:21:30.092 --> 00:21:31.610 They're documented, they're captured. 00:21:31.906 --> 00:21:35.796 That could look like more buffers or different suppliers, better visibility. 00:21:36.005 --> 00:21:40.092 And really, at the end of the day, less dependence on this heroic intervention 00:21:40.092 --> 00:21:44.654 that I often see in supply chain and supply chain management and supply chain risk overall. 00:21:45.008 --> 00:21:49.105 And so really, for me, the interesting kind of self-reflective one is, 00:21:49.430 --> 00:21:52.466 am I spending less time reacting and more time preparing? 00:21:52.832 --> 00:21:56.552 If the answer is yes, you're probably recovering. If every day feels like a 00:21:56.552 --> 00:21:59.589 fire drill, you're probably just getting better at fighting fires. 00:21:59.990 --> 00:22:04.032 And so those are kind of the non-traditional metrics that I look at to really 00:22:04.032 --> 00:22:08.877 determine from a leader perspective, is the organization recovering or are you just treading water? 00:22:09.600 --> 00:22:14.767 Carrie, these are great traits and leadership skills that you're sharing with our listeners. 00:22:15.074 --> 00:22:19.225 So you're a board member of the Supply Chain Risk Leadership Council and also 00:22:19.225 --> 00:22:21.529 on our Corporate Advisory Board here at the center. 00:22:22.023 --> 00:22:24.769 You work across academia, government, and industry. 00:22:25.314 --> 00:22:29.772 Share with our listeners, what are some of the current blind spots in industry-wide data sharing? 00:22:30.173 --> 00:22:33.342 And how can cross-sector collaboration build upstream visibility? Carrie? 00:22:34.012 --> 00:22:37.025 Supply chains require collaboration at the end of the day. 00:22:37.397 --> 00:22:40.430 And for that to actually happen, there needs to be that with them, 00:22:40.430 --> 00:22:42.616 you know, what's in it for me mentality. 00:22:42.882 --> 00:22:46.238 Because at the end of the day, we collaborate, but there are also competitors in there. 00:22:46.654 --> 00:22:50.180 And there are a lot of issues and concerns about data being used against you, 00:22:50.180 --> 00:22:52.518 anti-competitive concerns, all rightly so. 00:22:52.813 --> 00:22:55.700 But I do believe most companies want to share that information, 00:22:55.700 --> 00:22:59.634 but it needs to focus on that minimal information required to make a decision. 00:23:00.047 --> 00:23:03.890 We all want all the data and all the time. I want to know exactly when your 00:23:03.890 --> 00:23:07.482 order is going to be late. I want to know exactly where you're making investments. 00:23:07.849 --> 00:23:11.878 A lot of that is obviously very sensitive information. So sometimes it's just 00:23:12.080 --> 00:23:15.534 about having that conversation about a business continuity plan. 00:23:15.727 --> 00:23:20.741 And rather than a deep assessment of one, it's asking how long it will take to double production. 00:23:21.067 --> 00:23:23.510 Not necessarily knowing that you need to double production, but how long.

00:23:23.510 --> 00:23:26.599 It gives the insights without necessarily having to share that data. 00:23:26.912 --> 00:23:28.322 It's also shared accountability. 00:23:28.736 --> 00:23:32.560 So sharing data back so that network effect of sharing is realized is really 00:23:32.560 --> 00:23:36.770 the key thing I see in building that cross-sector collaboration. 00:23:37.204 --> 00:23:41.500 So it's, I give you information, what can I get back? What can you give me insights 00:23:41.500 --> 00:23:43.410 on that I myself don't know? 00:23:43.730 --> 00:23:47.500 This is especially relevant with small organizations. We like to think of the 00:23:47.500 --> 00:23:50.450 big organizations as having all this information. 00:23:50.699 --> 00:23:54.925 But at the end of the day, it is still a mom-and-pop shop. It's a 50-person 00:23:55.159 --> 00:23:59.093 metal-bending fabrication organization that's doing a lot of work. 00:23:59.511 --> 00:24:02.830 They do not have the capacity. They do not have the people to kind of really 00:24:02.830 --> 00:24:03.981 know what's in their supply chain. 00:24:04.353 --> 00:24:06.890 But they can give some data out, but there needs to be kind of some puts and 00:24:06.890 --> 00:24:10.773 takes and shared collaboration and shared accountability on actually resolving that. 00:24:11.232 --> 00:24:14.710 And that's where I see a lot of the collaboration that I see in Supply Chain 00:24:14.710 --> 00:24:18.396 Risk Leadership Council, which is an organization focused just on supply chain risk. 00:24:18.859 --> 00:24:23.364 Got a lot of great organizations, Fortune 50, Fortune 500 organizations. 00:24:23.776 --> 00:24:27.776 It's a great organization to share information on approaches, 00:24:27.921 --> 00:24:33.105 on strategies, on tools and techniques that we all can learn from. 00:24:33.412 --> 00:24:36.670 And so we don't necessarily have to give up our unique information, 00:24:36.670 --> 00:24:40.030 but we can share with our process, our technology that we're using, 00:24:40.030 --> 00:24:43.383 where we think we have to move the needle. So that's a great forum that I've seen. 00:24:43.819 --> 00:24:46.840 And the same thing with the Penn State Center for Supply Chain Research, 00:24:46.840 --> 00:24:49.403 another great organization to learn from each other. 00:24:50.076 --> 00:24:54.262 So I can share my mistakes with the broader community and I can learn from others as well. 00:24:54.941 --> 00:24:59.707 Cross-collaboration through Penn State Center for Supply Chain Research and 00:25:00.084 --> 00:25:04.229 Supply Chain Risk Leadership Council are great ways to share process. 00:25:04.688 --> 00:25:08.410 And there are a lot of sector organizations that focus on sharing the data, 00:25:08.410 --> 00:25:10.493 the minimal data available overall. 00:25:11.164 --> 00:25:14.003 Building that upstream visibility does require some vulnerability, 00:25:14.276 --> 00:25:20.100 requires some identification of the minimal data you think you require to actually 00:25:20.100 --> 00:25:22.333 make a decision and not asking for the world. 00:25:23.015 --> 00:25:27.554 Gary, I love your thinking on that topic. As we sign off today, 00:25:27.664 --> 00:25:30.567 we will do this the way we ask all of our guests. 00:25:31.084 --> 00:25:34.610 And the question that we love to leave people with is if you are driving down 00:25:34.610 --> 00:25:38.940 your highway of life and there's a billboard on that horizon that sums up your 00:25:38.940 --> 00:25:40.871 career, your motto on life, 00:25:41.230 --> 00:25:45.010 something that you want to leave behind for others who are coming down that 00:25:45.010 --> 00:25:48.503 highway behind you, What does your billboard say, Kerry? 00:25:49.221 --> 00:25:53.912 If I could only have six words, it would be, be curious, keep learning, keep moving. 00:25:54.535 --> 00:25:59.429 There's a quote that I really enjoy from Walt Disney, and I'll leave you with this. 00:25:59.713 --> 00:26:03.150 The way to get started is to quit talking and begin doing. 00:26:03.880 --> 00:26:07.898 Great advice. Great advice. Thank you very much for sharing that and everything 00:26:07.898 --> 00:26:11.248 else today. It's been really, really helpful, and I'm sure our listeners will 00:26:11.248 --> 00:26:12.517 appreciate it immensely. 00:26:13.104 --> 00:26:16.518 It's been a pleasure. Outstanding. Kerry, thank you so much. 00:26:16.518 --> 00:26:20.122 Again, a pleasure to have Kerry McCarthy, Fellow of Supply Chain Resilience 00:26:20.395 --> 00:26:23.965 with LMI and also a CSCR Corporate Advisory Board member. 00:26:24.882 --> 00:26:29.448 Thank you for listening to Unpacked, insights hosted by the Penn State Smeal Center for Supply, 00:26:30.508 --> 00:26:33.689 For more information about support opportunities, research engagement, 00:26:33.834 --> 00:26:35.528 our professional development portfolio, 00:26:35.868 --> 00:26:39.508 and to explore valuable networking and benchmarking insights shared through 00:26:39.508 --> 00:26:46.908 CSCR's dynamic forums, please visit smeal.psu.edu forward slash CSCR.