1 00:00:00,677 --> 00:00:04,480 Prasad Mahajan of Optilogic, thanks for joining me today. 2 00:00:04,881 --> 00:00:10,355 Prasad works for Optilogic that does network optimization and network 3 00:00:10,355 --> 00:00:14,178 design that a lot of people need for managing their supply chain. 4 00:00:14,678 --> 00:00:18,726 And then Prasad, if I'm not mistaken, you had some experience with Uber 5 00:00:18,726 --> 00:00:22,182 Freight and maybe with Transplace that was before Uber Freight. 6 00:00:22,983 --> 00:00:26,818 And for me it took me a while to get comfortable with network 7 00:00:26,818 --> 00:00:29,410 optimization, what is it, how do you do it? 8 00:00:29,851 --> 00:00:33,567 And then in the last couple of years I've gotten some practice with 9 00:00:33,567 --> 00:00:37,340 Coupa and some training in Coupa and just going through super rudimentary 10 00:00:37,766 --> 00:00:42,552 analysis and it taught me how much of supply chain I didn't know, 11 00:00:42,552 --> 00:00:45,224 me coming from a real estate background where I feel like I really 12 00:00:45,224 --> 00:00:49,771 know real estate well, where the amount of constraints there are and like 13 00:00:49,771 --> 00:00:52,783 a managing the software, like it took a moment for me to just 14 00:00:52,783 --> 00:00:53,133 like 15 00:00:54,048 --> 00:00:57,250 get comfortable with the platform and like understand how to utilize it 16 00:00:57,250 --> 00:00:57,450 more. 17 00:00:57,451 --> 00:01:00,492 So I'm thankful for you to bring some clarity to it. 18 00:01:00,893 --> 00:01:04,537 And I'd be interested to know how your experience was before you got 19 00:01:04,537 --> 00:01:05,498 into Optilogic. 20 00:01:05,498 --> 00:01:09,291 It seems like you've had a pretty long career and or maybe as 21 00:01:09,291 --> 00:01:10,271 long as mine. 22 00:01:10,271 --> 00:01:11,992 I feel like I've had a long career now. 23 00:01:12,393 --> 00:01:15,455 So yeah, help bring us up to speed to how you got to 24 00:01:15,455 --> 00:01:17,466 where you are with your prior experience. 25 00:01:18,242 --> 00:01:20,805 Yeah, and then first of all, thank you for having me. 26 00:01:21,005 --> 00:01:21,685 My pleasure. 27 00:01:21,732 --> 00:01:23,393 Yeah, so I have 22 years 28 00:01:24,154 --> 00:01:26,556 with Transplace and Uber Freight combined. 29 00:01:26,643 --> 00:01:31,070 I started off actually writing optimization apps for 30 00:01:31,771 --> 00:01:35,114 several of Transplace's customers, shippers. 31 00:01:35,472 --> 00:01:40,395 like JCPenney, AutoZone, different customers wanting specific 32 00:01:41,116 --> 00:01:44,183 niche optimization salts, but also having 33 00:01:44,944 --> 00:01:48,886 users interact with those optimization apps to make daily decisions. 34 00:01:48,886 --> 00:01:53,870 So a lot of my earlier career was in writing those apps, also 35 00:01:53,910 --> 00:01:57,052 integrating them into our homegrown TMS systems. 36 00:01:57,564 --> 00:02:05,644 And then as technology started to evolve, always see that like early 2000s 37 00:02:05,644 --> 00:02:09,244 was a lot about optimization, a lot about solver. 38 00:02:09,504 --> 00:02:11,224 You could see solver growth. 39 00:02:11,404 --> 00:02:13,664 It's a lot about adding constraints, 40 00:02:14,764 --> 00:02:17,164 real world, know, multi-stop routing, 41 00:02:18,084 --> 00:02:21,204 gaining efficiency through optimization. 42 00:02:21,944 --> 00:02:28,955 And as technology evolved, you know, people started to look at supply 43 00:02:28,955 --> 00:02:31,109 chain very strategically. 44 00:02:31,159 --> 00:02:33,855 It used to be always, hey, we need to... 45 00:02:34,143 --> 00:02:37,124 chokes transportation because that's where a lot of the cost is and we 46 00:02:37,124 --> 00:02:38,304 need to make it efficient. 47 00:02:38,355 --> 00:02:42,727 But as globalization really spread out, information became more available, 48 00:02:42,727 --> 00:02:47,818 data started flowing into these through the systems into people's hands. 49 00:02:48,218 --> 00:02:51,539 People started making cool stuff out of data. 50 00:02:51,919 --> 00:02:55,704 And so this is where the solvers, I think, 51 00:02:56,785 --> 00:03:01,146 in democratic, precisely into so many people's hands about, can we 52 00:03:02,194 --> 00:03:05,894 really take a strategic look at how we are spending money in 53 00:03:05,894 --> 00:03:06,625 transportation. 54 00:03:06,625 --> 00:03:11,079 Are we doing justice to our customers? 55 00:03:11,079 --> 00:03:13,180 Are they getting the right amount of service? 56 00:03:13,921 --> 00:03:19,310 And so a lot of that 2010 to 2015, 2016 was more about 57 00:03:19,945 --> 00:03:21,616 network optimizations. 58 00:03:21,616 --> 00:03:24,378 know, my supply chain is global. 59 00:03:24,879 --> 00:03:27,111 Where should I have my distribution centers? 60 00:03:27,111 --> 00:03:28,402 How big they should be? 61 00:03:28,461 --> 00:03:29,972 Which customers should I service from? 62 00:03:29,972 --> 00:03:30,422 Where? 63 00:03:30,663 --> 00:03:32,464 How much inventory should I hold? 64 00:03:32,520 --> 00:03:33,180 All those. 65 00:03:33,541 --> 00:03:37,303 And then what the later half of, think, the second decade 66 00:03:38,230 --> 00:03:42,132 taught us of this century was really the uncertainty, right? 67 00:03:42,132 --> 00:03:42,605 Like, okay, 68 00:03:42,625 --> 00:03:42,825 Yes. 69 00:03:42,782 --> 00:03:44,483 well, supply chain can be 70 00:03:45,163 --> 00:03:47,444 efficient through a lot of different steps. 71 00:03:47,444 --> 00:03:52,406 We optimize it, we plan around it, we design the right things, but 72 00:03:52,426 --> 00:03:54,567 uncertainty throws a wrench into everything. 73 00:03:55,027 --> 00:03:57,028 So how do you handle uncertainty? 74 00:03:57,071 --> 00:03:58,611 How do you handle volatility? 75 00:03:58,648 --> 00:04:01,009 And then one-off situations and things like that. 76 00:04:01,009 --> 00:04:06,591 So later on, as we started getting into these natural calamities you know, 77 00:04:06,591 --> 00:04:10,074 wars or disruptions through volcanoes and things like that, 78 00:04:10,774 --> 00:04:15,871 or whether it became important to have a more robust plan and thought 79 00:04:15,871 --> 00:04:21,925 process around how do we optimize it under uncertainty and how should the 80 00:04:21,925 --> 00:04:25,651 executives be prepared to make decisions in such an environment. 81 00:04:25,718 --> 00:04:30,992 And so that's kind of the evolution that I have experienced, you know, 82 00:04:30,992 --> 00:04:35,079 starting with that transportation and so towards the tail end of my career 83 00:04:35,079 --> 00:04:38,983 the last 10 years were mostly spent into consulting. 84 00:04:39,028 --> 00:04:42,734 For the very reasons I just talked about is executives would come and 85 00:04:43,074 --> 00:04:47,498 ask questions about hey how should I operate and things like that and 86 00:04:47,618 --> 00:04:51,885 the consulting practice that I helped start with my other peers there 87 00:04:52,586 --> 00:04:54,868 really addressed the need at that moment. 88 00:04:55,631 --> 00:04:56,133 Yeah. 89 00:04:56,234 --> 00:04:59,593 And that's before, during or after Uber Freight. 90 00:05:00,020 --> 00:05:00,780 This was 91 00:05:01,529 --> 00:05:05,892 both during and after and so I think before, during and after because 92 00:05:05,892 --> 00:05:11,974 we really started in 2010 and that's where this software was starting to 93 00:05:11,974 --> 00:05:14,016 become easier to use 94 00:05:14,036 --> 00:05:14,386 Yes. 95 00:05:15,346 --> 00:05:22,291 and the role of supply chain modeler was coming along very well and 96 00:05:22,792 --> 00:05:27,877 that's the before part but After you Uber Freight, think as I transitioned 97 00:05:27,877 --> 00:05:31,900 into Optilogic, I'm seeing a tremendous platform here. 98 00:05:32,392 --> 00:05:32,620 Yeah. 99 00:05:32,640 --> 00:05:38,068 Makes it so much easier for strategic decision making and you can actually 100 00:05:38,988 --> 00:05:43,281 deploy that decision into hands of many users through apps and digital 101 00:05:43,281 --> 00:05:44,432 twins and things like that. 102 00:05:44,492 --> 00:05:45,373 So really excited. 103 00:05:45,862 --> 00:05:46,413 Yeah. 104 00:05:46,633 --> 00:05:48,575 And how's your role evolved now? 105 00:05:48,695 --> 00:05:50,887 Like Optilogic that's a new role for you. 106 00:05:50,887 --> 00:05:53,539 I'm sure there's a lot of getting used to it and figuring out 107 00:05:53,539 --> 00:05:57,004 like what is a the place where you can have the maximum positive 108 00:05:57,004 --> 00:05:57,364 impact. 109 00:05:58,335 --> 00:05:58,995 Absolutely. 110 00:05:59,056 --> 00:06:03,198 Although the role has definitely evolved, it's everything that I like to 111 00:06:03,198 --> 00:06:06,439 do and used to do in a different world. 112 00:06:07,099 --> 00:06:09,113 So there's really three main things 113 00:06:09,833 --> 00:06:10,593 I do here. 114 00:06:10,664 --> 00:06:13,465 One is really solutioning for our customers. 115 00:06:13,540 --> 00:06:17,732 Most of our customers have global supply chains or they're logistics 116 00:06:17,732 --> 00:06:24,764 companies and really engage with them and help them really show, hey, 117 00:06:25,575 --> 00:06:29,847 how can they make a much more positive impact to their ways of 118 00:06:29,847 --> 00:06:34,150 operating through supply chain design, through the technology we have 119 00:06:34,150 --> 00:06:34,721 available? 120 00:06:34,771 --> 00:06:39,213 Secondly, for some of our customers who are mature, really helping them 121 00:06:39,213 --> 00:06:39,574 with 122 00:06:40,554 --> 00:06:44,135 whether it's building a model, whether it's building a strategy, sometimes 123 00:06:44,135 --> 00:06:46,937 it can be a how do we build a center of excellence? 124 00:06:46,983 --> 00:06:50,161 Because we want to have this as a core capability now as supply 125 00:06:50,291 --> 00:06:52,954 takes central focus in organizations. 126 00:06:53,711 --> 00:06:57,370 And again, the third thing is really customer engagement. 127 00:06:57,530 --> 00:07:02,833 Once a customer has onboarded on our platform, how do we make our 128 00:07:02,833 --> 00:07:04,024 customers successful? 129 00:07:04,568 --> 00:07:04,768 Yes. 130 00:07:04,705 --> 00:07:06,047 Because as... 131 00:07:06,411 --> 00:07:10,262 We want to have as many of our customers with most efficient supply 132 00:07:10,262 --> 00:07:15,000 chain, most efficient in terms of carbon emissions, everything like that. 133 00:07:15,000 --> 00:07:19,523 So that's the role I enjoy as well as to help our customers 134 00:07:19,523 --> 00:07:21,445 succeed and adopt our platform. 135 00:07:22,134 --> 00:07:22,504 Yeah. 136 00:07:22,745 --> 00:07:23,306 I love it. 137 00:07:23,426 --> 00:07:24,187 That's awesome. 138 00:07:24,187 --> 00:07:26,881 I'm sure you're happy when you read about 'em in the news, doing 139 00:07:26,881 --> 00:07:27,231 well. 140 00:07:27,911 --> 00:07:28,662 fantastic. 141 00:07:28,662 --> 00:07:30,113 So what would you say are 142 00:07:30,803 --> 00:07:32,765 some of the main problems people are facing? 143 00:07:32,765 --> 00:07:37,103 I mean, I totally get that you've already kind of as you've talked 144 00:07:37,103 --> 00:07:41,868 about the maturity of the industry, that already talks about a lot of 145 00:07:41,868 --> 00:07:44,590 the problems and what I had told you about was 146 00:07:45,441 --> 00:07:49,194 being in Southern California, a lot of people recognize it's a high 147 00:07:49,256 --> 00:07:50,317 barrier to entry. 148 00:07:50,415 --> 00:07:52,859 It has a lot of regulations and restrictions. 149 00:07:53,365 --> 00:07:57,909 It has a high cost of real estate, high cost of labor, high 150 00:07:57,909 --> 00:07:59,100 cost of housing. 151 00:07:59,520 --> 00:08:02,420 And so companies are always trying to figure out and then the big 152 00:08:02,420 --> 00:08:04,681 population center and the ports. 153 00:08:05,142 --> 00:08:09,108 And so it's been interesting for us to have companies go to Las 154 00:08:09,108 --> 00:08:12,140 Vegas and Phoenix as an alternative to save money. 155 00:08:12,621 --> 00:08:17,575 And then now that the market has peaked and is now coming back 156 00:08:17,575 --> 00:08:22,382 down to the trough, now all of a sudden the pricing for real 157 00:08:22,382 --> 00:08:26,755 estate in terms of warehouses is now coming back down where it's not 158 00:08:26,815 --> 00:08:32,365 at parity with those markets, but it's close enough where at some point 159 00:08:32,365 --> 00:08:36,488 in time like that makes all those decisions people made and those long 160 00:08:36,488 --> 00:08:37,449 term commitments. 161 00:08:37,868 --> 00:08:40,501 New commitments now are made with new information. 162 00:08:40,501 --> 00:08:43,433 So I'd be interested to see if you're experiencing that and what that 163 00:08:43,553 --> 00:08:45,274 how that manifests on your side. 164 00:08:46,008 --> 00:08:46,839 Yeah, absolutely. 165 00:08:46,839 --> 00:08:51,024 And so I think, you know, and that's what supply chain design is 166 00:08:51,044 --> 00:08:55,990 all about is trying to find that, you know, best balance between different 167 00:08:55,990 --> 00:08:56,490 costs 168 00:08:57,271 --> 00:08:57,520 that 169 00:08:57,540 --> 00:08:57,740 Yeah. 170 00:08:57,621 --> 00:08:59,033 you are faced with today. 171 00:08:59,434 --> 00:08:59,634 And 172 00:08:59,622 --> 00:08:59,822 Yeah. 173 00:08:59,634 --> 00:09:02,522 because all these different costs, whether you want to take 174 00:09:03,000 --> 00:09:09,533 transportation, warehousing, which has a labor and a storage component. 175 00:09:09,613 --> 00:09:13,798 Then you have the inventory costs on top of that. 176 00:09:14,538 --> 00:09:16,379 At times they move in different directions. 177 00:09:16,379 --> 00:09:23,142 There's different macroeconomic parameters influencing these costs. 178 00:09:23,562 --> 00:09:27,264 And so at any given time, the supply chain design is going to 179 00:09:27,524 --> 00:09:32,546 give you the best of all the combinations because our technology would 180 00:09:32,727 --> 00:09:37,590 look at optimizing across all of these different costs as a cost to 181 00:09:37,590 --> 00:09:38,715 serve kind of a parameter. 182 00:09:38,735 --> 00:09:39,085 Yes. 183 00:09:40,064 --> 00:09:40,272 Yes. 184 00:09:40,292 --> 00:09:43,935 But the opposite direction to that becomes service. 185 00:09:44,175 --> 00:09:47,177 And that's where your California example, Southern Cal 186 00:09:47,927 --> 00:09:51,829 comes into play is if this was all about service, I would put 187 00:09:52,090 --> 00:09:56,212 my distribution center in Southern Cal because that's where a lot of your 188 00:09:56,212 --> 00:10:01,232 demand is or somewhere in California due to hit the West Coast. 189 00:10:01,969 --> 00:10:06,609 But when people actually look at supply chain, it's not just the demand, 190 00:10:07,169 --> 00:10:10,109 but you also have to look at where is your supply coming from. 191 00:10:11,409 --> 00:10:15,649 And what is so for one of the customers I worked with in 192 00:10:15,649 --> 00:10:22,869 a manufacturing industry where they had a plant in Salt Lake City and 193 00:10:22,869 --> 00:10:27,167 all most of the market was in California, Southern California. 194 00:10:27,488 --> 00:10:31,685 So obviously there was a need for having a warehouse there, but how 195 00:10:31,685 --> 00:10:33,358 do those cost metrics work? 196 00:10:33,872 --> 00:10:37,191 I'm in the middle of an assignment where we're comparing these two right 197 00:10:37,191 --> 00:10:37,492 now. 198 00:10:37,512 --> 00:10:37,967 So, like 199 00:10:37,987 --> 00:10:38,337 Yeah. 200 00:10:38,666 --> 00:10:41,373 I'm interested to hear how the story worked out. 201 00:10:42,008 --> 00:10:42,208 Exactly. 202 00:10:42,035 --> 00:10:42,446 Yeah. 203 00:10:43,178 --> 00:10:45,278 I would say, you 204 00:10:46,041 --> 00:10:48,658 know, start with understanding. 205 00:10:48,658 --> 00:10:50,102 I would say start with clarity. 206 00:10:50,544 --> 00:10:54,647 you need to have clarity on what is most important for your organization. 207 00:10:54,720 --> 00:10:58,703 People always say I want the best of both service and cost, but 208 00:10:58,823 --> 00:11:03,947 it's really saying that, well, I'm going to meet this service expectation. 209 00:11:03,947 --> 00:11:07,350 So if your service says I want to hit all my customers within 210 00:11:07,771 --> 00:11:12,635 six hours, eight hours, 12 hours, sub same day or one day, that 211 00:11:12,635 --> 00:11:13,896 becomes a different strategy. 212 00:11:14,076 --> 00:11:16,298 But if you want to say that, okay, I can do two or 213 00:11:16,298 --> 00:11:20,901 three days, but I want to really minimize cost or keep my cost 214 00:11:21,102 --> 00:11:22,462 KPIs in control. 215 00:11:23,104 --> 00:11:26,806 Then you have a little bit more flexibility around, where else can I 216 00:11:26,806 --> 00:11:27,156 be? 217 00:11:27,707 --> 00:11:31,110 So for this specific example, we looked at other options. 218 00:11:31,153 --> 00:11:34,995 really creatively looking at Henderson, Nevada, which is right out of Las 219 00:11:34,995 --> 00:11:35,495 Vegas. 220 00:11:35,545 --> 00:11:40,291 And you've got Glendale, Arizona, Phoenix area, even Reno. 221 00:11:40,336 --> 00:11:43,976 And so what else to look for is really what can differentiate between 222 00:11:44,096 --> 00:11:46,397 one customer versus other is 223 00:11:47,135 --> 00:11:49,816 how is their inbound supply chain laid out? 224 00:11:49,816 --> 00:11:51,597 Where is the product coming from? 225 00:11:52,017 --> 00:11:56,423 If you're making it in Salt Lake City, choices for modes of transportation 226 00:11:56,683 --> 00:11:58,003 going into California. 227 00:11:58,303 --> 00:12:02,544 Now, also remember that sometimes getting into California is cheaper 228 00:12:02,664 --> 00:12:04,024 because it's a backhaul lane. 229 00:12:04,304 --> 00:12:05,570 And so if you have 230 00:12:05,590 --> 00:12:05,940 Okay. 231 00:12:06,445 --> 00:12:11,671 a site in Las Vegas, for example, outside, that becomes a backhaul lane. 232 00:12:11,671 --> 00:12:15,182 you're all the carriers and you're trucking it are wanting to go back 233 00:12:15,182 --> 00:12:15,882 to California. 234 00:12:16,162 --> 00:12:16,362 So 235 00:12:16,282 --> 00:12:16,482 Yes. 236 00:12:16,442 --> 00:12:17,165 you're going to get a better 237 00:12:17,185 --> 00:12:17,493 You need 238 00:12:17,513 --> 00:12:17,713 rate. 239 00:12:17,576 --> 00:12:18,468 to match loads. 240 00:12:18,755 --> 00:12:18,955 Yes, 241 00:12:18,929 --> 00:12:19,129 yeah. 242 00:12:19,135 --> 00:12:19,765 exactly. 243 00:12:19,765 --> 00:12:22,677 So you're going to get a better rate going back to California. 244 00:12:22,757 --> 00:12:26,549 So even though you're incurring a little bit more miles, you might 245 00:12:26,549 --> 00:12:28,460 actually get better line haul. 246 00:12:28,525 --> 00:12:32,177 And you just have to see, does now do I now get better 247 00:12:32,177 --> 00:12:33,307 labor availability? 248 00:12:34,087 --> 00:12:36,189 Are the taxes better here? 249 00:12:36,253 --> 00:12:39,675 You know, compared to what I'm paying because inventory in some certain 250 00:12:39,675 --> 00:12:43,222 counties can be taxed and, you know, there can be a tax implication 251 00:12:43,583 --> 00:12:46,534 that could kill your profitability and could change your decision. 252 00:12:46,557 --> 00:12:47,037 as well. 253 00:12:47,178 --> 00:12:50,830 So all these parameters, I think you need to think about what's important 254 00:12:50,830 --> 00:12:51,321 and then 255 00:12:52,181 --> 00:12:55,584 you feed it into the optimizer and it gives you a good side-by-side 256 00:12:55,584 --> 00:12:58,026 comparison of all the options you have chosen. 257 00:12:58,627 --> 00:12:59,177 Yeah. 258 00:13:00,020 --> 00:13:03,344 cost of power, I imagine, makes it into there. 259 00:13:03,344 --> 00:13:05,986 I know it sh certainly does on a lot of these line items. 260 00:13:05,986 --> 00:13:10,688 I hadn't seen it in like a network optimization models, but I would 261 00:13:10,688 --> 00:13:14,494 imagine it's increasingly part of the conversation and it's almost a big 262 00:13:14,494 --> 00:13:18,005 enough impact for manufacturers anyways, that 263 00:13:18,914 --> 00:13:21,935 that it doesn't drive the decision, but it's still something that needs to 264 00:13:21,935 --> 00:13:22,736 be accounted for. 265 00:13:23,829 --> 00:13:24,490 Absolutely. 266 00:13:24,610 --> 00:13:28,526 And I would say like if it's sometimes the decisions are lot easier 267 00:13:28,526 --> 00:13:31,280 when you're actually opening up a new facility. 268 00:13:31,713 --> 00:13:35,671 versus you are relocating something because now you have to think about 269 00:13:35,671 --> 00:13:39,603 labor and are people willing to relocate and you know all those things 270 00:13:39,603 --> 00:13:39,993 so 271 00:13:40,733 --> 00:13:44,475 because skilled labor is an asset you know and I think it's on 272 00:13:44,475 --> 00:13:47,477 paper it seems very easy oh move from here to here and get 273 00:13:47,477 --> 00:13:52,376 the savings but when you actually start implementing this there's a lot of 274 00:13:52,376 --> 00:13:55,439 things you have to be very sensitive about because all that training and 275 00:13:55,439 --> 00:13:58,070 development that's gone into your labor in a given 276 00:13:59,122 --> 00:14:02,233 facility, you know, what does it cost to replicate that 277 00:14:03,115 --> 00:14:03,337 in a 278 00:14:03,357 --> 00:14:03,557 Too 279 00:14:03,375 --> 00:14:03,575 different 280 00:14:03,567 --> 00:14:03,767 much. 281 00:14:03,676 --> 00:14:05,619 facility. 282 00:14:06,356 --> 00:14:06,936 Yeah. 283 00:14:07,370 --> 00:14:08,871 how did that project end up? 284 00:14:08,891 --> 00:14:10,632 Did you ever get to see how it ended? 285 00:14:10,652 --> 00:14:13,650 I know for me I have one where we're looking at that now 286 00:14:13,650 --> 00:14:16,192 and it's more of someone who's already in California. 287 00:14:16,552 --> 00:14:19,574 And it is interesting to think that the southern parts of Salt Lake 288 00:14:19,574 --> 00:14:23,086 City you can reach in a day by truck, although it's like right 289 00:14:23,086 --> 00:14:25,337 at the edge and it's only the southern parts. 290 00:14:25,918 --> 00:14:29,175 And then they do have Skilled labor. 291 00:14:29,175 --> 00:14:32,194 They do have like a good pool of labor over there. 292 00:14:32,456 --> 00:14:35,605 But I'd be interested to see how that one example what ended up 293 00:14:35,605 --> 00:14:36,057 happening. 294 00:14:37,071 --> 00:14:42,042 Yeah, and so in this case, there was a sizable amount of product 295 00:14:42,082 --> 00:14:44,653 that was coming from the ports as well. 296 00:14:44,653 --> 00:14:51,084 So the Long Beach, Rialto area was where DC was selected. 297 00:14:51,831 --> 00:14:52,031 Okay. 298 00:14:51,984 --> 00:14:55,511 And so although you had a plant in Salt Lake City that now 299 00:14:55,511 --> 00:14:59,173 cost a little bit more to move that product all the way into 300 00:14:59,173 --> 00:15:04,110 Rialto, but for anything that was moving in the rivers you know all 301 00:15:04,110 --> 00:15:06,953 these containers are coming in and you know 302 00:15:07,714 --> 00:15:11,688 getting stored it was lot easier to have those ocean containers bring into 303 00:15:11,688 --> 00:15:15,852 Long Beach and then have that product available right there in Southern 304 00:15:15,852 --> 00:15:16,463 California. 305 00:15:16,855 --> 00:15:17,315 Yeah. 306 00:15:17,796 --> 00:15:20,377 I would think that's we're gonna see a lot of that in the 307 00:15:20,377 --> 00:15:20,998 next year. 308 00:15:21,598 --> 00:15:25,032 Like some of these other markets are already starting to go up in 309 00:15:25,032 --> 00:15:28,034 price for a property and where 310 00:15:28,845 --> 00:15:33,226 the inland empire isn't going up yet and perhaps could take a little 311 00:15:33,226 --> 00:15:34,937 while for it to start going up. 312 00:15:35,237 --> 00:15:37,917 So I would think now we'll get to see how the other side 313 00:15:37,917 --> 00:15:40,619 of that coin like what it looks like and see people take that 314 00:15:40,619 --> 00:15:41,330 into account. 315 00:15:42,090 --> 00:15:45,522 Yeah, and then there is one more piece before we move on to 316 00:15:45,522 --> 00:15:48,325 the next one, I would like to add is there is also a 317 00:15:48,325 --> 00:15:50,766 little subjective element which 318 00:15:51,447 --> 00:15:55,218 you don't see that as well documented online, but you just get it 319 00:15:55,218 --> 00:15:56,389 when you are interacting 320 00:15:56,785 --> 00:15:56,985 Yes. 321 00:15:56,949 --> 00:16:00,992 with senior executives and leaders is what are really they going through. 322 00:16:01,672 --> 00:16:05,714 And that one piece I want to highlight is ease of doing business, 323 00:16:06,154 --> 00:16:09,776 which is very, it can differ by state. 324 00:16:09,866 --> 00:16:14,477 state and that's where I think you can give them a recommendation from 325 00:16:14,477 --> 00:16:19,008 a number standpoint but they may still decide to override it because that 326 00:16:19,008 --> 00:16:25,039 state or that specific geography is just not easy to do business with 327 00:16:25,079 --> 00:16:27,300 and there could be labor laws or 328 00:16:28,180 --> 00:16:33,122 certain things associated with a lot of parameters but that's a subjective 329 00:16:33,182 --> 00:16:35,583 piece that people may bring in at some point. 330 00:16:36,176 --> 00:16:36,606 Yes. 331 00:16:37,348 --> 00:16:40,976 And that certain cities, counties and states get a stigma or you have 332 00:16:40,976 --> 00:16:44,641 a bad experience and you don't wanna replace that or you recognize there's 333 00:16:44,641 --> 00:16:48,937 already a lot of risk and potential friction and like the last thing 334 00:16:48,937 --> 00:16:52,170 you wanna do is make that worse, by choosing an area that's not 335 00:16:52,170 --> 00:16:53,792 going to be as collaborative. 336 00:16:54,671 --> 00:16:55,052 Exactly. 337 00:16:55,052 --> 00:16:59,520 And on the other side is like there could be probably nothing wrong, 338 00:16:59,520 --> 00:17:01,607 but somebody else gives you better incentives. 339 00:17:02,461 --> 00:17:02,811 Yes. 340 00:17:03,972 --> 00:17:04,953 Yeah, it's so funny. 341 00:17:04,953 --> 00:17:11,181 I don't see that play out regionally, but I feel like across the 342 00:17:11,181 --> 00:17:12,652 country if people are gonna 343 00:17:12,948 --> 00:17:13,148 Yes. 344 00:17:13,032 --> 00:17:17,579 like move further out, that's more of something that is increasingly on 345 00:17:17,579 --> 00:17:18,079 the table. 346 00:17:18,472 --> 00:17:21,663 Yeah, it is an interesting one and insight selection like playing that 347 00:17:21,663 --> 00:17:23,214 game of when you do that. 348 00:17:23,534 --> 00:17:27,306 And for us it's challenging as real estate practitioners because sometimes 349 00:17:27,306 --> 00:17:31,608 the opportunity for when a property is available and which one is the 350 00:17:31,608 --> 00:17:32,358 right one, 351 00:17:33,076 --> 00:17:36,717 that can happen faster than the incentives conversations. 352 00:17:37,197 --> 00:17:40,719 Sometimes that can happen slower than the incentive conversations. 353 00:17:40,719 --> 00:17:45,139 And so trying to time those up can be that can be challenging 354 00:17:45,139 --> 00:17:49,066 for like an actual assignment that is like a green field assignment. 355 00:17:49,803 --> 00:17:50,153 Yeah. 356 00:17:50,859 --> 00:17:54,828 what are things ex that's a good thinking about like executives and what's 357 00:17:54,828 --> 00:17:58,279 in their mind and how they ultimately make decisions, like that is who 358 00:17:58,279 --> 00:18:01,361 we all serve, those are the people that are trusted in those corporations 359 00:18:01,361 --> 00:18:02,631 to make these big decisions. 360 00:18:03,112 --> 00:18:06,173 What are a lot of things you see that they get wrong or 361 00:18:06,173 --> 00:18:10,559 that like are pitfalls or challenges that they often have when you think 362 00:18:10,559 --> 00:18:12,627 through the lens of network optimization? 363 00:18:13,356 --> 00:18:15,710 Yeah, so I think that's a very good question. 364 00:18:15,710 --> 00:18:17,873 think we, you know. 365 00:18:17,873 --> 00:18:23,180 em And I'm glad there's, we work with some really good executives who 366 00:18:23,268 --> 00:18:26,110 before making a decision, they are 367 00:18:26,850 --> 00:18:32,272 wanting to see what the model or supply chain design project is actually 368 00:18:32,272 --> 00:18:35,954 telling them and whether that decision is right or wrong. 369 00:18:36,554 --> 00:18:40,966 And a lot of, maybe the most, one of the most common one 370 00:18:40,966 --> 00:18:45,980 I see in the last few years is nearshoring. 371 00:18:46,056 --> 00:18:47,056 outsourcing, right? 372 00:18:47,056 --> 00:18:50,880 So now, as you can see, one of the, I'll be very specific, 373 00:18:50,880 --> 00:18:53,164 but theme is fairly general. 374 00:18:53,304 --> 00:18:58,928 But that example I want to call out is a carpet company that 375 00:18:58,928 --> 00:19:02,135 had manufacturing as well as some suppliers in 376 00:19:03,156 --> 00:19:04,157 Southeast Asia. 377 00:19:04,517 --> 00:19:08,319 And so they were bringing in all these containers into North America, 378 00:19:08,363 --> 00:19:12,226 which was both a mix of some raw materials, but also finished products. 379 00:19:12,256 --> 00:19:17,403 So a few years back when there was volatility in the ocean rates, 380 00:19:17,457 --> 00:19:20,820 you would see the container rates were spiking up. 381 00:19:21,249 --> 00:19:21,460 Yes. 382 00:19:21,480 --> 00:19:27,113 And when you are so much dependent on that one move, obviously the 383 00:19:27,113 --> 00:19:29,025 question comes, hey, what can I do different? 384 00:19:29,626 --> 00:19:32,698 And some of the executives were about to make a decision that, hey, 385 00:19:32,698 --> 00:19:35,690 let's just do nearshoring, move all these 386 00:19:36,930 --> 00:19:40,573 manufacturing units or lines, per se, to Mexico and 387 00:19:41,233 --> 00:19:44,335 there was not much more capacity available in the US itself. 388 00:19:44,426 --> 00:19:48,467 But they did this study before making that decision, which really prevented 389 00:19:48,467 --> 00:19:53,121 them from making a wrong decision was that when you look at Mexico, 390 00:19:53,161 --> 00:19:59,325 it was a good option, but the labor from a transportation cost standpoint, 391 00:19:59,364 --> 00:20:03,017 as well as from a lead time standpoint, it was really hard to 392 00:20:03,017 --> 00:20:03,947 beat the labor. 393 00:20:03,987 --> 00:20:10,182 So the difference came very close and that's where the other pieces come 394 00:20:10,182 --> 00:20:13,571 in is long-term relationships, long-term contracts with 395 00:20:13,591 --> 00:20:13,791 Yeah. 396 00:20:13,674 --> 00:20:15,966 suppliers and your partners. 397 00:20:16,687 --> 00:20:19,849 How should you weigh that versus some short-term gains? 398 00:20:20,069 --> 00:20:20,419 And 399 00:20:21,137 --> 00:20:26,014 so the scenarios that we were able to bring in front of these 400 00:20:26,014 --> 00:20:29,336 executives were, hey, what if you kept 401 00:20:30,017 --> 00:20:31,698 your product in Southeast Asia? 402 00:20:31,698 --> 00:20:35,708 What's the worst case if ocean rates spike and they stay long for 403 00:20:35,708 --> 00:20:37,022 a period of to 12 months. 404 00:20:37,683 --> 00:20:42,876 Versus what if you bring everything into Mexico or what if you start 405 00:20:42,876 --> 00:20:45,688 another line hypothetically in the US. 406 00:20:45,788 --> 00:20:50,171 And by seeing those different cost parameters side by side, 407 00:20:50,852 --> 00:20:53,714 although there was a little dip in the Mexico option, 408 00:20:54,434 --> 00:20:59,283 they still selected to choose to keep the sourcing in Southeast Asia 409 00:20:59,283 --> 00:21:02,885 because of the relationship and the short term nature of this disruption. 410 00:21:03,005 --> 00:21:03,725 and so forth. 411 00:21:04,126 --> 00:21:07,908 So they prevented making a wrong decision I think at the end and 412 00:21:07,938 --> 00:21:12,252 I'm glad you know they decided to use this approach to really make 413 00:21:12,252 --> 00:21:16,795 that decision as an intelligent decision through data and modeling. 414 00:21:17,538 --> 00:21:21,673 Yeah, I totally compare that to a lot of times you have long 415 00:21:21,673 --> 00:21:27,926 term decisions that are based off of short term problems or short term 416 00:21:27,926 --> 00:21:33,000 like changes, disruptions, and then trying to match those back up again to 417 00:21:33,000 --> 00:21:37,672 say, Is this the right long term decision if these short term challenges 418 00:21:37,833 --> 00:21:42,055 go away or resolve themselves, like would you still be happy with the 419 00:21:42,055 --> 00:21:42,555 outcome? 420 00:21:42,555 --> 00:21:46,191 And that's Another way you can use data to help like tell that 421 00:21:46,191 --> 00:21:48,139 story and like await that risk. 422 00:21:48,895 --> 00:21:49,245 Yeah. 423 00:21:49,406 --> 00:21:54,488 And now our answer to all of this is because we've seen the 424 00:21:54,488 --> 00:22:00,006 number of disruptions that have a negative impact are growing in number. 425 00:22:00,006 --> 00:22:02,007 They're becoming almost a way of life. 426 00:22:02,068 --> 00:22:06,787 I just attended a conference recently where theme of key supply chain 427 00:22:07,468 --> 00:22:11,369 officers was supply chain management has become more of a firefighting 428 00:22:11,570 --> 00:22:12,019 exercise, 429 00:22:12,039 --> 00:22:12,395 Yes. 430 00:22:12,690 --> 00:22:12,890 right? 431 00:22:12,808 --> 00:22:13,158 Yep. 432 00:22:13,510 --> 00:22:14,291 We don't want 433 00:22:15,091 --> 00:22:16,952 anyone to constantly firefight. 434 00:22:17,512 --> 00:22:19,093 everybody to be on top of that. 435 00:22:19,414 --> 00:22:23,996 And so our answer to that is having an always-on digital twin 436 00:22:24,509 --> 00:22:24,859 Yes. 437 00:22:25,197 --> 00:22:29,390 in the market where you have your supply chain model ready and it's 438 00:22:29,390 --> 00:22:33,737 all refreshed so periodically, so frequently that it's always on, meaning 439 00:22:33,737 --> 00:22:35,300 I have the most current view 440 00:22:35,320 --> 00:22:35,520 Yes. 441 00:22:35,498 --> 00:22:36,379 of my network. 442 00:22:36,739 --> 00:22:37,140 Yes. 443 00:22:37,173 --> 00:22:41,545 And then I'm either anticipating and modeling what can go wrong. 444 00:22:41,805 --> 00:22:45,126 And I have a really a playbook of, this goes wrong. 445 00:22:45,126 --> 00:22:46,988 I'm going to take these three decisions first. 446 00:22:47,408 --> 00:22:49,969 If this goes wrong, I'm going to take these decisions first. 447 00:22:50,229 --> 00:22:53,801 And it's not too hard to understand what can go wrong because you 448 00:22:53,801 --> 00:22:57,953 have a good history, but you also know your current metrics, right? 449 00:22:58,273 --> 00:23:03,035 It's like, what are my current metrics that are exposed to risks like 450 00:23:03,035 --> 00:23:03,385 these? 451 00:23:03,458 --> 00:23:05,659 And so being prepared to... 452 00:23:06,119 --> 00:23:07,330 disruptions are not going to stop. 453 00:23:07,330 --> 00:23:10,525 We are not going to in the business of stopping disruptions, but we 454 00:23:10,525 --> 00:23:13,437 want to make sure that you're prepared to handle that. 455 00:23:13,437 --> 00:23:17,970 You can anticipate those and you have a playbook of actions ready. 456 00:23:18,470 --> 00:23:21,602 If that happens, you're not starting from scratch. 457 00:23:21,602 --> 00:23:22,273 You're really 458 00:23:23,073 --> 00:23:25,355 getting into, okay, where should I act? 459 00:23:26,069 --> 00:23:26,509 Yeah. 460 00:23:26,810 --> 00:23:29,426 You've said digital twin twice now. 461 00:23:29,966 --> 00:23:32,861 Prasad, I'm keeping score over here. 462 00:23:32,861 --> 00:23:36,994 So I recognize that a lot of people's experience with network designer 463 00:23:36,994 --> 00:23:41,306 optimization is a one-time study right before they make a big decision. 464 00:23:41,606 --> 00:23:45,288 And that's on like the small to medium sized scale of things, perhaps 465 00:23:45,288 --> 00:23:49,521 oftentimes where on the global side or once you have a center of 466 00:23:49,521 --> 00:23:52,793 excellence and you have a team and you have an in-house capability. 467 00:23:53,095 --> 00:23:57,557 you can perhaps lean into the digital twin and having like a persistent 468 00:23:57,557 --> 00:24:03,221 and consistent view so that you can like always be playing out scenarios, 469 00:24:03,221 --> 00:24:05,532 you can react, you can be proactive. 470 00:24:05,912 --> 00:24:06,332 So 471 00:24:07,241 --> 00:24:12,775 like tell me more about the digital twin how it works and who 472 00:24:12,775 --> 00:24:15,166 does it work for and who doesn't it work for. 473 00:24:15,166 --> 00:24:16,959 Is this only Fortune 500? 474 00:24:17,359 --> 00:24:20,361 Is this only once you get above a hundred locations? 475 00:24:20,759 --> 00:24:25,703 How would you categorize like the total addressable market or like who the 476 00:24:25,703 --> 00:24:30,037 ideal use cases are for it and who it's really maybe like a 477 00:24:30,037 --> 00:24:33,206 not for or who haven't grown to that scale? 478 00:24:33,206 --> 00:24:35,328 Like where do you draw the line on who benefits from that? 479 00:24:36,069 --> 00:24:37,290 Yeah, great question. 480 00:24:37,290 --> 00:24:44,338 And I think it's more of a matter of how your exposure is 481 00:24:44,359 --> 00:24:47,627 in supply chain versus whether you're big or small. 482 00:24:47,728 --> 00:24:52,890 And that's what I think because even if you're a small company, if 483 00:24:53,230 --> 00:24:57,842 you have a critical mass of suppliers, if something happens to them, it 484 00:24:57,842 --> 00:24:59,293 can really take the company down. 485 00:25:00,183 --> 00:25:02,579 This becomes a critical feature to have for you. 486 00:25:02,631 --> 00:25:07,800 Secondly, It doesn't cost as much to build a digital twin nowadays with 487 00:25:07,800 --> 00:25:12,474 technology and especially our platform, is so AI enabled, that 488 00:25:12,494 --> 00:25:12,862 Yeah. 489 00:25:13,283 --> 00:25:18,262 once you have the data available with a team of humans plus AI 490 00:25:18,262 --> 00:25:23,956 as an enabler, you can easily set up your data pipelines through our 491 00:25:23,956 --> 00:25:25,517 DataStar technology. 492 00:25:25,920 --> 00:25:31,377 and having our agent API really makes it simpler to cleanse the data, 493 00:25:31,377 --> 00:25:31,797 make it. 494 00:25:32,213 --> 00:25:35,512 more structured for modeling and so forth. 495 00:25:35,752 --> 00:25:40,855 So having those data pipelines, connections is now becoming very standard 496 00:25:40,875 --> 00:25:44,676 in a digital twin so that you with a click of a button 497 00:25:44,676 --> 00:25:46,657 can get a refreshed data 498 00:25:47,317 --> 00:25:50,099 or set some automatic jobs to do that. 499 00:25:50,179 --> 00:25:52,380 And so your platform is always current. 500 00:25:52,380 --> 00:25:56,391 So anybody who needs to assess their supply chain and say, hey, what 501 00:25:56,391 --> 00:25:57,142 are our risks? 502 00:25:57,642 --> 00:26:00,123 Are we exposed to disruptions? 503 00:26:00,243 --> 00:26:04,326 and I would be surprised if anybody says no. 504 00:26:05,306 --> 00:26:08,008 And why should I not have a digital twin, right? 505 00:26:08,008 --> 00:26:11,070 And if you don't get an answer, that's really the path forward. 506 00:26:11,114 --> 00:26:14,736 And then the last thing is the reporting has become so crystal clear 507 00:26:15,317 --> 00:26:20,080 with our platform as well as the use of our agent AI is 508 00:26:20,541 --> 00:26:26,411 that you're not just telling senior executives that or your decision 509 00:26:26,411 --> 00:26:30,832 makers or your operations people, business users that, hey, this is what 510 00:26:31,553 --> 00:26:32,493 the delta is. 511 00:26:33,294 --> 00:26:37,195 But it's actually going deeper into saying, this is what the delta is, 512 00:26:37,195 --> 00:26:38,396 why this is happening, 513 00:26:39,136 --> 00:26:40,737 and this is what you should do. 514 00:26:41,337 --> 00:26:43,478 So the getting from insights. 515 00:26:44,192 --> 00:26:47,249 into prescription is I think the real value of 516 00:26:47,269 --> 00:26:47,469 Yeah. 517 00:26:47,403 --> 00:26:48,304 a digital twin. 518 00:26:48,716 --> 00:26:49,066 Yeah. 519 00:26:49,524 --> 00:26:54,286 Everything else is structure and you know mechanics which I think we have 520 00:26:54,286 --> 00:26:56,207 mastered how to do that pretty well. 521 00:26:56,567 --> 00:27:00,938 So if you tell me there's a company that doesn't value prescriptions I 522 00:27:00,938 --> 00:27:03,809 don't think digital twin is for them but I don't think you'll find 523 00:27:03,809 --> 00:27:04,550 such a company. 524 00:27:05,273 --> 00:27:05,733 Yeah. 525 00:27:05,814 --> 00:27:09,152 It does seem like you guys are more AI enabled than 526 00:27:09,218 --> 00:27:09,648 most. 527 00:27:09,648 --> 00:27:13,083 I know when I was going through some of my training not too 528 00:27:13,083 --> 00:27:16,714 long ago, it was like I wouldn't say zero. 529 00:27:17,222 --> 00:27:21,519 But it was it's amazing how much things have changed in four years 530 00:27:21,879 --> 00:27:24,450 or in a short period of time of if you think of how 531 00:27:24,450 --> 00:27:27,518 you were doing it five years ago versus how you're doing it now. 532 00:27:27,518 --> 00:27:29,839 Like it's pretty powerful the changes. 533 00:27:29,839 --> 00:27:32,611 It does seem like you guys leaned into that, were fast to it, 534 00:27:32,831 --> 00:27:35,549 and like people can greatly benefit as a result. 535 00:27:36,302 --> 00:27:39,685 Absolutely, and I always use the word that this is 536 00:27:40,526 --> 00:27:42,727 not a small improvement. 537 00:27:43,068 --> 00:27:44,188 This is a game changer. 538 00:27:44,259 --> 00:27:45,620 So I used to hear 539 00:27:46,480 --> 00:27:51,684 us say a lot that, we can model in days instead of weeks. 540 00:27:51,764 --> 00:27:55,427 And then when I actually tried it myself, so I come with 541 00:27:56,147 --> 00:27:58,789 actually a very minimal modeling background. 542 00:27:59,730 --> 00:28:01,031 But I will, with the help of... 543 00:28:01,788 --> 00:28:02,298 either 544 00:28:03,078 --> 00:28:04,259 our agentic platform 545 00:28:05,004 --> 00:28:06,925 and AI, 546 00:28:07,585 --> 00:28:12,867 the whole burden of modeling can be done in, I would say, if 547 00:28:12,867 --> 00:28:14,868 you are fairly data ready. 548 00:28:14,903 --> 00:28:19,985 But from setting up the pipelines to the actual model to getting a 549 00:28:19,985 --> 00:28:21,645 reasonable number of scenarios out. 550 00:28:22,001 --> 00:28:23,332 It could be hours or days. 551 00:28:23,993 --> 00:28:29,178 I have built personally eight to 10 models in a month that got 552 00:28:29,178 --> 00:28:33,362 done just within hours and they were across different use cases. 553 00:28:33,362 --> 00:28:37,506 So some were network optimization, some were pure transportation routing, 554 00:28:38,067 --> 00:28:40,629 know, fleet optimization, sizing the fleet. 555 00:28:41,210 --> 00:28:45,511 Everything is becoming like an hour's play instead of like weeks and weeks 556 00:28:45,511 --> 00:28:45,922 of work. 557 00:28:46,801 --> 00:28:47,241 Yeah. 558 00:28:48,182 --> 00:28:48,683 That's 559 00:28:49,556 --> 00:28:51,077 that's fantastic, right? 560 00:28:51,077 --> 00:28:52,383 That's what it's all about. 561 00:28:52,459 --> 00:28:55,442 it's funny when you think of like connecting with people and them having 562 00:28:55,442 --> 00:28:59,035 their data in order, how often you just get like the Excel sheet 563 00:28:59,035 --> 00:29:02,574 with all the data versus now I would imagine it's more plug and 564 00:29:02,574 --> 00:29:02,925 play. 565 00:29:03,648 --> 00:29:03,958 Yeah. 566 00:29:03,978 --> 00:29:07,597 And then is that many of your customers are experienced 3PLs? 567 00:29:07,897 --> 00:29:12,888 I know in our world for industrial real estate, like thirty to fifty 568 00:29:12,888 --> 00:29:16,059 percent of the market is third party logistics. 569 00:29:16,400 --> 00:29:19,461 So anytime I'm talking with anybody I'm always curious 570 00:29:20,294 --> 00:29:22,124 where that fits into your world. 571 00:29:22,485 --> 00:29:25,914 And it's different, right, than you would think of like consumer package 572 00:29:25,914 --> 00:29:26,384 goods 573 00:29:27,065 --> 00:29:27,465 and 574 00:29:28,675 --> 00:29:31,107 Kind of corporate America as they're making their decisions. 575 00:29:31,668 --> 00:29:34,251 I've found some 3PLs like to do some of this in house 576 00:29:34,251 --> 00:29:35,252 more often, right? 577 00:29:35,252 --> 00:29:38,065 Like if they're a bigger three PL and they have the center of 578 00:29:38,065 --> 00:29:40,946 excellence and they need the software and they need help from people like 579 00:29:40,946 --> 00:29:41,296 you. 580 00:29:41,716 --> 00:29:45,606 would you say how big is that as a percentage of total customers 581 00:29:45,606 --> 00:29:47,158 you guys have that you interact with? 582 00:29:48,449 --> 00:29:49,220 Yeah, and I... 583 00:29:49,599 --> 00:29:51,100 Thanks for asking that question. 584 00:29:51,100 --> 00:29:56,866 actually that's coming from the 3PL and really 4PL now background. 585 00:29:57,326 --> 00:30:01,656 That was a very important aspect for me coming here. 586 00:30:02,437 --> 00:30:09,460 And we actually now have a pretty good playbook for 4PLs or 3PLs 587 00:30:10,020 --> 00:30:12,301 who would like to do these 588 00:30:13,036 --> 00:30:14,957 services for their customers 589 00:30:15,697 --> 00:30:16,778 or even themselves. 590 00:30:17,202 --> 00:30:21,054 So one of the things that's becoming very critical, I just saw a 591 00:30:21,054 --> 00:30:26,800 survey recently, is that going forward, the future of the revenue looks 592 00:30:26,800 --> 00:30:31,173 like for the 3PLs and 4PLs is there's going to be a lot 593 00:30:31,173 --> 00:30:35,585 more growth, faster growth in the services and solutions side than the 594 00:30:35,585 --> 00:30:37,030 trucking side itself 595 00:30:37,770 --> 00:30:40,192 or any other modes of transportation. 596 00:30:40,234 --> 00:30:44,998 services aspect here is how do you be that strategic partner to your 597 00:30:44,998 --> 00:30:45,438 shipper. 598 00:30:45,480 --> 00:30:49,962 And that's a pretty decent, I would say, thought process. 599 00:30:49,962 --> 00:30:53,494 But also, I would say it's more essential now that if you're a 600 00:30:53,494 --> 00:30:57,917 3PL and if you have the customers, your shipper's data, 601 00:30:58,638 --> 00:31:01,880 there is an implicit expectation that give me insights. 602 00:31:02,160 --> 00:31:06,303 Be an advocate, be an advisor, be more than just a partner. 603 00:31:06,406 --> 00:31:06,756 or 604 00:31:07,537 --> 00:31:10,619 take that relationship to the next level than just being transactional 605 00:31:10,619 --> 00:31:11,000 with me. 606 00:31:11,660 --> 00:31:16,304 And this is where our 4PL playbook would come in play is these 607 00:31:16,304 --> 00:31:23,450 are very specific, pre-designed use cases that 4PLs would run both from 608 00:31:23,450 --> 00:31:26,011 their solutioning side as well as 609 00:31:26,992 --> 00:31:32,176 repeat customer improvement value at standpoint is they would have an 610 00:31:32,176 --> 00:31:34,678 array of these use cases already ready to go. 611 00:31:35,385 --> 00:31:35,699 Yeah. 612 00:31:35,719 --> 00:31:36,329 So whether it's 613 00:31:36,349 --> 00:31:36,549 That's 614 00:31:36,441 --> 00:31:36,641 like 615 00:31:36,630 --> 00:31:36,830 awesome. 616 00:31:36,790 --> 00:31:37,692 a. 617 00:31:37,795 --> 00:31:39,386 Yeah, a lot of that is tactical. 618 00:31:39,386 --> 00:31:44,068 Like, example, obviously the strategic is fairly obvious, but tactical is 619 00:31:44,068 --> 00:31:48,050 like, I want to change my network this year, but I want to 620 00:31:48,050 --> 00:31:49,570 see if there's anything I can do. 621 00:31:49,609 --> 00:31:50,680 Should I use a cross-dock? 622 00:31:50,680 --> 00:31:54,871 Should I use an extra space in my DC as a pool point? 623 00:31:55,852 --> 00:32:00,294 Should I, anything that goes into Mexico, know, should I send it through 624 00:32:00,294 --> 00:32:04,646 Laredo or should I have a pooling point somewhere in Chicago, right? 625 00:32:04,646 --> 00:32:08,098 For everything that goes south, same with everything that comes north, 626 00:32:08,159 --> 00:32:10,270 what should be my fleet size and so forth. 627 00:32:10,270 --> 00:32:15,236 So all these use cases, we're offering that as a playbook for three 628 00:32:15,236 --> 00:32:16,126 PLs and 4PLs. 629 00:32:16,970 --> 00:32:17,472 Love it. 630 00:32:17,512 --> 00:32:19,338 How long you think that's been going on now? 631 00:32:19,460 --> 00:32:21,215 That's pretty new in the last year maybe? 632 00:32:22,262 --> 00:32:22,612 yeah. 633 00:32:22,885 --> 00:32:28,045 I would say that's really recent and maybe always had the capability to 634 00:32:28,045 --> 00:32:30,465 run it through our platform. 635 00:32:31,065 --> 00:32:37,825 But then, you know, what our recent advancements in deploying these apps 636 00:32:37,825 --> 00:32:40,885 is much of a differentiator. 637 00:32:40,925 --> 00:32:46,165 So when you package all of these use cases into a ready to 638 00:32:46,165 --> 00:32:50,985 use app, then a lot more broader people can use it. 639 00:32:51,125 --> 00:32:52,839 They have a good... 640 00:32:52,849 --> 00:32:56,182 screen to understand they have clicks of buttons and then they have 641 00:32:56,182 --> 00:32:59,366 different tabs where they can go and see the output and take actions. 642 00:32:59,386 --> 00:32:59,736 Yeah. 643 00:33:00,797 --> 00:33:01,237 Yeah. 644 00:33:01,878 --> 00:33:02,388 I love it. 645 00:33:02,388 --> 00:33:03,098 That's awesome. 646 00:33:03,539 --> 00:33:06,140 Yeah, I figure that's such a big part of the market that that's 647 00:33:06,160 --> 00:33:11,643 a like undeniable segment that you have to address and cater and like 648 00:33:11,643 --> 00:33:12,704 it's a growth segment. 649 00:33:13,347 --> 00:33:16,589 though like perhaps it's not growing as much as it was a few 650 00:33:16,589 --> 00:33:17,210 years ago. 651 00:33:17,210 --> 00:33:21,913 Like it is undeniably a segment of the industry that's like going to 652 00:33:21,913 --> 00:33:24,314 be here and going to continue to flourish for a long time to 653 00:33:24,314 --> 00:33:25,275 come to some extent. 654 00:33:26,054 --> 00:33:26,404 Yeah. 655 00:33:26,695 --> 00:33:27,095 cool. 656 00:33:27,095 --> 00:33:31,048 And then let's say it this was Prasad Industries and you were in 657 00:33:31,048 --> 00:33:33,010 charge of the roadmap for what's next. 658 00:33:33,010 --> 00:33:35,433 What would you say is one of the next things you would think 659 00:33:35,433 --> 00:33:39,710 to add or to build that would make Optilogic more helpful for people 660 00:33:40,051 --> 00:33:40,932 and where it's growing? 661 00:33:41,460 --> 00:33:44,835 Or what are customers asking for that you don't yet have? 662 00:33:44,835 --> 00:33:46,733 That would be another way of asking that question. 663 00:33:46,973 --> 00:33:47,323 Yeah. 664 00:33:47,704 --> 00:33:52,336 And I, it's, I see more of this as a, we, we are, 665 00:33:52,597 --> 00:33:56,357 our customers always ask for some things and I think, I'll address that, 666 00:33:56,357 --> 00:34:01,043 but from a more broader space side, I see us more as a, 667 00:34:01,043 --> 00:34:05,554 are leading the customer into, Hey, how should you do things best? 668 00:34:06,058 --> 00:34:07,350 and what is out there. 669 00:34:07,350 --> 00:34:11,457 So I do think that we are definitely, and I've experienced this coming 670 00:34:11,457 --> 00:34:12,409 in fairly new. 671 00:34:12,409 --> 00:34:17,594 I started in February here is, you know, the pace of innovation is 672 00:34:17,594 --> 00:34:19,046 just so high. 673 00:34:19,621 --> 00:34:19,821 that 674 00:34:19,699 --> 00:34:20,049 Yes. 675 00:34:21,232 --> 00:34:25,194 we had this agentic AI initially a few months back. 676 00:34:25,252 --> 00:34:27,613 Then we have this Claude connector that went in. 677 00:34:27,613 --> 00:34:30,074 We were the first supply chain design company to get there. 678 00:34:30,117 --> 00:34:34,347 Now we have the digital twin, full approach, step-by-step walkthrough. 679 00:34:34,788 --> 00:34:38,037 And then we are also deploying cool things around apps. 680 00:34:38,085 --> 00:34:42,704 And so I think my focus would be also, hey, let's just bring 681 00:34:42,704 --> 00:34:44,865 our customers along, focus on adoption, 682 00:34:45,745 --> 00:34:47,665 show them the value that it brings. 683 00:34:48,225 --> 00:34:52,726 And then finding the good balance between human and AI to make sure 684 00:34:52,726 --> 00:34:53,086 that 685 00:34:53,866 --> 00:34:57,084 we are bringing the best to the industry as a whole and 686 00:34:57,104 --> 00:34:57,326 Yeah. 687 00:34:57,346 --> 00:35:03,297 to our customers, both in terms of efficiency, productivity, and then the 688 00:35:03,297 --> 00:35:05,288 accuracy of the decisions that they are making. 689 00:35:06,477 --> 00:35:06,927 Yeah. 690 00:35:07,187 --> 00:35:11,123 That's oftentimes it's the idea of like making better use of what is 691 00:35:11,123 --> 00:35:15,535 available and making sure that all the people that could possibly benefit 692 00:35:15,535 --> 00:35:19,356 from it, like have it available, they're aware of it, they know how 693 00:35:19,356 --> 00:35:20,416 to maximize it. 694 00:35:20,796 --> 00:35:27,158 And in a fast paced like technological revolution, that seems like that's 695 00:35:27,648 --> 00:35:30,899 a challenge in of its in and of itself, just having everybody know 696 00:35:30,899 --> 00:35:34,070 what is possible now that there are all these new powerful tools 697 00:35:34,070 --> 00:35:34,650 available. 698 00:35:35,675 --> 00:35:40,220 Absolutely and then You know, we also have a ton of progress in 699 00:35:40,220 --> 00:35:42,322 simulation, which is really 700 00:35:42,342 --> 00:35:42,692 Okay? 701 00:35:42,700 --> 00:35:43,655 running hundreds 702 00:35:43,675 --> 00:35:43,920 Yeah. 703 00:35:43,940 --> 00:35:46,011 and thousands of scenarios very quickly. 704 00:35:46,472 --> 00:35:46,672 And 705 00:35:46,514 --> 00:35:46,714 Yeah. 706 00:35:46,682 --> 00:35:51,662 the way I see the product evolve there is, you know, that you 707 00:35:51,662 --> 00:35:55,314 have classic sensitivity analysis, which used to be fairly limited to 708 00:35:55,314 --> 00:35:59,016 certain parameters, certain what ifs and all those things. 709 00:35:59,016 --> 00:36:03,448 But can I just run a thousand of these very quickly as processing 710 00:36:03,448 --> 00:36:04,669 times become faster 711 00:36:05,359 --> 00:36:10,115 and then give you, instead of you choosing, oh, I'm sensitive to this 712 00:36:10,115 --> 00:36:10,736 or that, 713 00:36:11,717 --> 00:36:16,294 but the twin or the tool actually tells you that, okay, you're 714 00:36:16,294 --> 00:36:19,438 going to run out of capacity in June, 2028 715 00:36:20,359 --> 00:36:20,709 at 716 00:36:21,360 --> 00:36:21,941 this speed. 717 00:36:23,318 --> 00:36:26,970 with this set of demand and this criteria, if nothing changes, because 718 00:36:26,970 --> 00:36:30,020 those are the questions people always want to know is at 719 00:36:30,040 --> 00:36:30,240 Totally. 720 00:36:30,141 --> 00:36:35,263 what point, you know, business continuity is a great use case here because 721 00:36:35,763 --> 00:36:38,705 you want to have business continuity as you are growing. 722 00:36:39,324 --> 00:36:42,656 And even if you are a mature company, you want to still maintain 723 00:36:42,656 --> 00:36:44,107 that in a profitable way 724 00:36:44,767 --> 00:36:45,508 at no point. 725 00:36:45,508 --> 00:36:49,529 And we saw that during COVID that people really had to sign leases 726 00:36:50,330 --> 00:36:53,558 on warehouses at a really expensive rate because they ran out of capacity. 727 00:36:53,986 --> 00:36:54,759 Could be double. 728 00:36:54,961 --> 00:36:57,286 Yeah, we have a lot of people coming out of that are giving 729 00:36:57,286 --> 00:36:58,290 space back right now. 730 00:36:58,722 --> 00:37:03,777 Yeah, so that proactive feedback is what I would see people focus more 731 00:37:03,817 --> 00:37:07,560 on is, you know, not as much as how do I model and, 732 00:37:07,861 --> 00:37:11,975 you know, which model do I create, but for my supply chain, what 733 00:37:11,975 --> 00:37:16,099 is that proactive feed that will alert me, you know, what are my 734 00:37:16,099 --> 00:37:18,481 sensitive parameters in the next three to five years? 735 00:37:19,215 --> 00:37:19,655 Yeah. 736 00:37:19,833 --> 00:37:24,144 since we do leases oftentimes for these big companies, the difference 737 00:37:24,144 --> 00:37:27,226 between three, five, seven, and ten years, they're all juggling what 738 00:37:27,226 --> 00:37:27,927 should I take? 739 00:37:27,927 --> 00:37:34,070 And that's all like in relation to their debt maturity or their contracts 740 00:37:34,070 --> 00:37:38,782 with their customers or the other host of other like a liabilities or 741 00:37:38,782 --> 00:37:42,204 revenue opportunities that are all contractually based that they have to 742 00:37:42,524 --> 00:37:46,657 juggle and to like make the appropriate like decision. 743 00:37:47,063 --> 00:37:48,283 with all of that in mind. 744 00:37:49,032 --> 00:37:49,552 Cool. 745 00:37:49,826 --> 00:37:52,078 we're busting through an hour over here, Prasad. 746 00:37:52,078 --> 00:37:55,466 The last thing I would ask is just a entry level, like a 747 00:37:55,466 --> 00:37:59,574 people first getting started that might call you and call Optilogic that's 748 00:37:59,574 --> 00:38:04,288 not already using somebody, like a different provider, or they don't 749 00:38:04,288 --> 00:38:05,810 already have the skill in-house. 750 00:38:05,810 --> 00:38:11,886 Like what is usually the first like the entry level that someone's dealing 751 00:38:11,886 --> 00:38:12,236 with? 752 00:38:12,384 --> 00:38:15,910 Like size of company or size of problem when they first are like, 753 00:38:15,910 --> 00:38:20,376 Hey Prasad, I I'm dealing with this, I've grown to this size, I'd 754 00:38:20,376 --> 00:38:23,281 like to start implementing Optilogic. 755 00:38:23,281 --> 00:38:24,794 What would like a entry level be? 756 00:38:25,538 --> 00:38:26,914 Yeah, and I think the... 757 00:38:27,405 --> 00:38:30,376 Or would you say most of your customers are just like, I've had 758 00:38:30,376 --> 00:38:31,237 it with Coupa, 759 00:38:31,904 --> 00:38:35,151 it's finally time to make the shift, or would you say, that's only 760 00:38:35,151 --> 00:38:38,744 half the people and the rest are all like the first time people 761 00:38:38,744 --> 00:38:41,205 that have grown to a certain level where now they need more help 762 00:38:41,205 --> 00:38:43,225 making bigger, more sophisticated decisions? 763 00:38:44,404 --> 00:38:47,647 I think I see a good mix between the two. 764 00:38:47,713 --> 00:38:49,881 We have a pretty sizable that... 765 00:38:50,515 --> 00:38:54,974 are definitely coming to us from others just citing the pace of our 766 00:38:54,974 --> 00:38:59,289 innovation and so much investment we are doing in our products and 767 00:38:59,289 --> 00:38:59,929 services. 768 00:38:59,987 --> 00:39:03,609 So, and then for that entry level, I would say, 769 00:39:04,399 --> 00:39:08,706 I'll quote our CEO here is he always says, be curious. 770 00:39:09,286 --> 00:39:11,788 So there is with that at this pace. 771 00:39:12,334 --> 00:39:17,737 and where we are technologically from a feature standpoint as well as from 772 00:39:17,737 --> 00:39:18,847 an AI standpoint. 773 00:39:19,597 --> 00:39:22,302 Being curious is really important to 774 00:39:23,063 --> 00:39:26,309 really start that, whether you want to start a center of excellence or 775 00:39:26,309 --> 00:39:28,670 whether you want to start small 776 00:39:29,530 --> 00:39:30,971 with a quick improvement. 777 00:39:31,057 --> 00:39:33,358 There's nothing wrong in either of these options. 778 00:39:33,401 --> 00:39:34,841 But be curious right now. 779 00:39:35,122 --> 00:39:38,003 You just have to think what you want to do. 780 00:39:38,643 --> 00:39:42,145 And there are our platform would allow you to enable that. 781 00:39:42,346 --> 00:39:46,188 And especially with AI, you don't have to worry as much about, how 782 00:39:46,188 --> 00:39:47,309 do I make this happen? 783 00:39:47,449 --> 00:39:50,511 know, it's the technology is going to guide you through that. 784 00:39:50,791 --> 00:39:54,854 So what's really important as an entry level is to really be thoughtful 785 00:39:54,854 --> 00:39:59,477 about where that value is, how much how quickly I want to deliver 786 00:39:59,617 --> 00:40:04,631 that for my organization and not get lost into too much of the 787 00:40:04,631 --> 00:40:05,641 weeds. 788 00:40:05,641 --> 00:40:08,173 You know, like if your data if you're not data ready. 789 00:40:08,896 --> 00:40:13,638 Don't worry, start somewhere, start small, get that quick win, get that 790 00:40:13,678 --> 00:40:17,930 ROI and that will drive more investment from your stakeholders, your 791 00:40:17,930 --> 00:40:19,480 leadership, your ELT team. 792 00:40:19,541 --> 00:40:22,162 Because when they see that as a success and they see that as 793 00:40:22,162 --> 00:40:26,012 an ROI, that goes a long way and then you'll get more investment 794 00:40:26,292 --> 00:40:28,393 to scale big and so forth. 795 00:40:28,922 --> 00:40:30,283 Yes, I love it. 796 00:40:30,283 --> 00:40:31,363 That's sage advice. 797 00:40:31,430 --> 00:40:35,346 get small quick wins to build momentum, build confidence, build a skill 798 00:40:35,346 --> 00:40:39,141 set, and then start like getting a positive impact as a result. 799 00:40:39,852 --> 00:40:40,392 Love it. 800 00:40:40,753 --> 00:40:42,424 well, Prasad, that's our hour. 801 00:40:42,424 --> 00:40:45,596 I would ask you for a second hour if I could, but that's 802 00:40:45,596 --> 00:40:46,596 a good start. 803 00:40:47,017 --> 00:40:50,861 And it's interesting to figure out where the intersection of real estate 804 00:40:50,861 --> 00:40:52,632 is and being a real estate practitioner. 805 00:40:53,280 --> 00:40:56,802 And dealing with supply chain officers and people that have that 806 00:40:56,802 --> 00:41:00,704 responsibility within companies to understand what they're dealing with 807 00:41:01,004 --> 00:41:05,127 and then see where their areas of responsibility then come back to the 808 00:41:05,127 --> 00:41:08,679 type of work that we do because these are big decisions, they require 809 00:41:08,679 --> 00:41:11,880 a lot of effort, a lot of capital and like a lot of 810 00:41:11,974 --> 00:41:14,465 analysis goes into what makes the right decision. 811 00:41:15,225 --> 00:41:15,807 Absolutely. 812 00:41:16,572 --> 00:41:16,851 Yeah. 813 00:41:16,871 --> 00:41:17,123 Thank 814 00:41:17,143 --> 00:41:17,343 Cool. 815 00:41:17,182 --> 00:41:17,477 you for 816 00:41:17,497 --> 00:41:17,697 Thanks. 817 00:41:17,593 --> 00:41:20,843 having me when I thoroughly enjoyed the conversation with you as well. 818 00:41:21,414 --> 00:41:22,596 Yeah, wonderful. 819 00:41:22,596 --> 00:41:23,448 Thank you, Prasad. 820 00:41:23,448 --> 00:41:24,470 I'll talk with you later. 821 00:41:24,975 --> 00:41:25,769 Yeah, talk to you. 822 00:41:25,769 --> 00:41:26,054 Thank you. 823 00:41:26,074 --> 00:41:26,875 Okay, bye-bye.