1 00:00:05,559 --> 00:00:08,680 Speaker 1: Hello, Hello. This is Smart Talks with IBM, a podcast 2 00:00:08,720 --> 00:00:12,479 Speaker 1: from Pushkin Industries, our our radio and IBM about what 3 00:00:12,480 --> 00:00:15,560 Speaker 1: it means to look at today's most challenging problems in 4 00:00:15,600 --> 00:00:25,120 Speaker 1: a new way. I'm Malcolm Gladwell. For our final episode, 5 00:00:26,280 --> 00:00:28,640 Speaker 1: I bring you an ode to the holiday shopping season. 6 00:00:29,040 --> 00:00:32,360 Speaker 1: Well not just a holiday shopping season. This episode is 7 00:00:32,400 --> 00:00:34,800 Speaker 1: for all of you who waited six months or longer 8 00:00:35,120 --> 00:00:37,279 Speaker 1: for your new couch to arrive, and those of you 9 00:00:37,520 --> 00:00:40,560 Speaker 1: still struggling to buy a car because of the chip shortage. 10 00:00:43,159 --> 00:00:45,720 Speaker 1: It's all about what's going on with the supply chain, 11 00:00:46,040 --> 00:00:48,040 Speaker 1: and we're gonna look at how the supply chain has 12 00:00:48,080 --> 00:00:51,000 Speaker 1: evolved since the late nineteen and why we've seen so 13 00:00:51,080 --> 00:00:56,320 Speaker 1: many hiccups and interruptions over the last two years. No 14 00:00:56,360 --> 00:00:58,920 Speaker 1: one knows the current struggles of the supply chain better 15 00:00:59,080 --> 00:01:03,160 Speaker 1: than Jonathan Wright. Jonathan is the global Managing Partner for 16 00:01:03,240 --> 00:01:07,200 Speaker 1: Supply Chain Consulting at IBM, and I think now what 17 00:01:07,240 --> 00:01:11,720 Speaker 1: we're going to see is uh strategic supply chains, strategic 18 00:01:11,800 --> 00:01:15,840 Speaker 1: relationships which are brought together through technology, and that that 19 00:01:16,000 --> 00:01:19,280 Speaker 1: vertical integration which once was through ownership, will now be 20 00:01:19,360 --> 00:01:24,200 Speaker 1: through technology integration. Together, we'll look at the evolution of 21 00:01:24,200 --> 00:01:27,800 Speaker 1: our modern day supply chain and explore how today's demand 22 00:01:28,200 --> 00:01:33,280 Speaker 1: has created something called a bull whip effect. Jonathan and 23 00:01:33,319 --> 00:01:35,480 Speaker 1: I will get into what all of this means and 24 00:01:35,520 --> 00:01:38,240 Speaker 1: the ways technology can be used to help address current 25 00:01:38,520 --> 00:01:50,160 Speaker 1: supply chain shortages. Let's dive in. Hi, Jonathan, it's a 26 00:01:50,280 --> 00:01:53,440 Speaker 1: pleasure to meet you. It's a big moment for me, Malcolm. 27 00:01:53,480 --> 00:01:56,360 Speaker 1: It's is an honor and it's great to be spending 28 00:01:56,360 --> 00:01:59,240 Speaker 1: some time chatting to you about supply chain. Yeah, so 29 00:01:59,360 --> 00:02:03,640 Speaker 1: this we have chosen a topic that is very much 30 00:02:03,680 --> 00:02:05,720 Speaker 1: of the moment. I am dying for you to explain 31 00:02:05,840 --> 00:02:08,760 Speaker 1: just what is going on right now. So I'm I 32 00:02:08,760 --> 00:02:10,240 Speaker 1: feel like you're one of the few people who can 33 00:02:10,360 --> 00:02:13,560 Speaker 1: actually tell me the big picture. I hope we can. 34 00:02:13,840 --> 00:02:16,160 Speaker 1: I hope we can break that down and get into 35 00:02:16,200 --> 00:02:19,000 Speaker 1: some detail. But it's certainly an exciting time to be 36 00:02:19,120 --> 00:02:21,520 Speaker 1: working in supply chain. Is so much going on, and 37 00:02:21,560 --> 00:02:24,799 Speaker 1: we've got to unpack some some issues to to get 38 00:02:24,840 --> 00:02:27,440 Speaker 1: to the root. Cause I think, yeah, well, let's start 39 00:02:27,480 --> 00:02:31,520 Speaker 1: with you know, three years ago, no one like me 40 00:02:31,760 --> 00:02:34,840 Speaker 1: ever thought about a word about the state of the 41 00:02:34,880 --> 00:02:38,840 Speaker 1: supply chain. Um, now people like me, do we hear 42 00:02:38,880 --> 00:02:41,400 Speaker 1: it all the time. Tell me what has happened in 43 00:02:41,440 --> 00:02:46,760 Speaker 1: the last say two years two to drive this disruption? Well, again, 44 00:02:46,800 --> 00:02:50,600 Speaker 1: I often say to people, it's like welcome to literally 45 00:02:50,600 --> 00:02:55,520 Speaker 1: we we've accelerated UM the kind of thoughts and the 46 00:02:55,560 --> 00:02:58,320 Speaker 1: innovation around supply chain by ten years. And the pandemic 47 00:02:58,360 --> 00:03:02,160 Speaker 1: has driven that. For sure, UM necessity is the driver 48 00:03:02,240 --> 00:03:06,160 Speaker 1: of invention or innovation in this case. And and you 49 00:03:06,200 --> 00:03:10,000 Speaker 1: can't avoid that COVID period because it really did challenge 50 00:03:10,120 --> 00:03:12,200 Speaker 1: It put a shock into the supply chain, a shock 51 00:03:12,240 --> 00:03:15,520 Speaker 1: on the supply side UM when Wuhan went into lockdown, 52 00:03:15,560 --> 00:03:18,440 Speaker 1: and then a shock on the demand side when people 53 00:03:18,480 --> 00:03:21,720 Speaker 1: started buying fundamentally different things than they had been doing. 54 00:03:22,320 --> 00:03:25,000 Speaker 1: And and I think you know that's probably the biggest 55 00:03:25,040 --> 00:03:29,200 Speaker 1: shock UM to the supply chaine since the war. In reality, 56 00:03:29,680 --> 00:03:32,840 Speaker 1: is a supply chain system, right that has been disrupted. 57 00:03:33,360 --> 00:03:35,320 Speaker 1: Can you be a little more specific on what you 58 00:03:35,360 --> 00:03:39,520 Speaker 1: mean by disrupted? So you mentioned people started buying different 59 00:03:39,560 --> 00:03:44,640 Speaker 1: things and certain parts of the world were no longer 60 00:03:44,720 --> 00:03:48,920 Speaker 1: as capable of producing or moving products as did before. 61 00:03:48,960 --> 00:03:51,240 Speaker 1: But can you could have drilled down on the on 62 00:03:51,280 --> 00:03:53,880 Speaker 1: all of the sources here, Yeah, for sure, I mean, 63 00:03:54,040 --> 00:03:56,080 Speaker 1: you know, we were running out of of people, We 64 00:03:56,080 --> 00:03:59,080 Speaker 1: didn't have of toilet paper, all of the classic things 65 00:03:59,120 --> 00:04:02,280 Speaker 1: and um, and we went into survival mode and and 66 00:04:02,320 --> 00:04:04,200 Speaker 1: I think, you know, people roll their sleeves up, and 67 00:04:04,240 --> 00:04:06,480 Speaker 1: we're tenacious, and they figured out how to solve some 68 00:04:06,560 --> 00:04:11,560 Speaker 1: of those supply chain issues and keep society running and healthy. 69 00:04:11,600 --> 00:04:14,240 Speaker 1: And then we went into resourceful mode, where we started 70 00:04:14,240 --> 00:04:17,360 Speaker 1: to think about, hey, well we could repurpose some facilities 71 00:04:17,400 --> 00:04:19,839 Speaker 1: and make more ppe, and we could take some fashion 72 00:04:19,880 --> 00:04:24,400 Speaker 1: retailers and start creating new products. So this system, which 73 00:04:24,400 --> 00:04:27,840 Speaker 1: has been very stable and just incrementally growing, now we're 74 00:04:27,839 --> 00:04:31,479 Speaker 1: starting to repurpose things. And then of course we've had 75 00:04:31,680 --> 00:04:35,120 Speaker 1: a rapid recovery. The world has started moving faster and 76 00:04:35,160 --> 00:04:39,599 Speaker 1: coming back, and that recovery has put demand onto the 77 00:04:39,600 --> 00:04:42,279 Speaker 1: supply chain at a time where the supply base is 78 00:04:42,320 --> 00:04:46,680 Speaker 1: not robust because people are still in flex and so 79 00:04:47,200 --> 00:04:50,000 Speaker 1: you know, really we're in a in a situation where 80 00:04:50,000 --> 00:04:53,800 Speaker 1: we've got this very complex supply chain which is started 81 00:04:53,839 --> 00:04:56,760 Speaker 1: to be out of balance, and it's going to take 82 00:04:56,760 --> 00:05:00,760 Speaker 1: some work to get it rebalanced. Really, I was playing next, 83 00:05:01,040 --> 00:05:04,560 Speaker 1: you know, in doing this series with IBM. One of 84 00:05:04,560 --> 00:05:09,640 Speaker 1: the things that consistently been surprised about. Is the things 85 00:05:09,720 --> 00:05:12,680 Speaker 1: IBM now thinks about that I wouldn't have thought they 86 00:05:12,880 --> 00:05:16,360 Speaker 1: thought about ten years ago. Did IBM have people who 87 00:05:16,440 --> 00:05:19,719 Speaker 1: thought about supply chain management? You know, we have or 88 00:05:19,880 --> 00:05:22,440 Speaker 1: always kind of worked in supply chain, We have our 89 00:05:22,480 --> 00:05:25,400 Speaker 1: own supply chain, but I think now it is just 90 00:05:25,839 --> 00:05:29,240 Speaker 1: way more important than ever before. And this is at 91 00:05:29,240 --> 00:05:32,240 Speaker 1: the time where we're seeing convergent technology having a real 92 00:05:32,360 --> 00:05:36,920 Speaker 1: role to play, whether that's kind of blockchain, IoT AI 93 00:05:37,080 --> 00:05:39,960 Speaker 1: and Watson, which will help us with really understanding the 94 00:05:40,040 --> 00:05:43,520 Speaker 1: demand signal and the supply signal. So I think technology 95 00:05:43,560 --> 00:05:45,640 Speaker 1: has got a real role to play, and we did 96 00:05:45,640 --> 00:05:47,680 Speaker 1: see that through COVID. We saw those that we had 97 00:05:47,839 --> 00:05:51,360 Speaker 1: invested ahead of the curve coming out faster, being able 98 00:05:51,400 --> 00:05:55,200 Speaker 1: to respond quicker, being able to understand the supply base quicker, 99 00:05:55,240 --> 00:05:57,960 Speaker 1: and the and the exposures and the risk that they had. 100 00:05:58,520 --> 00:06:01,520 Speaker 1: UM So I think, you know, this is a bit 101 00:06:01,560 --> 00:06:05,000 Speaker 1: of a golden age that we're facing now. At what 102 00:06:05,040 --> 00:06:09,640 Speaker 1: point do we come to conceive of supply chain management 103 00:06:09,680 --> 00:06:14,560 Speaker 1: and splashing problems as as explicitly technological and data problems 104 00:06:15,400 --> 00:06:19,359 Speaker 1: as opposed to what you're talking about earlier relationships, you know, 105 00:06:20,480 --> 00:06:24,640 Speaker 1: practical kind of bricks and mortary kind of questions. When 106 00:06:24,680 --> 00:06:26,719 Speaker 1: does this transition to this notion of it, Oh, it's 107 00:06:26,800 --> 00:06:30,240 Speaker 1: just another complicated data problem. And I sort of said, 108 00:06:30,279 --> 00:06:32,640 Speaker 1: welcome to twenty that was a bit of the point, 109 00:06:32,760 --> 00:06:35,080 Speaker 1: you know, I think this has been a huge acceleration, 110 00:06:35,120 --> 00:06:39,359 Speaker 1: a huge jump forward, and the the interest now of 111 00:06:39,880 --> 00:06:43,200 Speaker 1: corporations to invest in technology to solve some of these problems. 112 00:06:43,480 --> 00:06:46,080 Speaker 1: If you go back to the early early supply chains, 113 00:06:46,120 --> 00:06:51,080 Speaker 1: we had vertical integration right where companies forward rouge, you know, 114 00:06:51,200 --> 00:06:54,080 Speaker 1: kind of they had on site, they made their own steel, 115 00:06:54,200 --> 00:06:57,440 Speaker 1: they had the whole integrated supply chain, and that's the 116 00:06:57,440 --> 00:07:01,760 Speaker 1: way that they built trust and collaborate action and security 117 00:07:01,800 --> 00:07:04,520 Speaker 1: into the supply chains. And I think now what we're 118 00:07:04,520 --> 00:07:09,640 Speaker 1: going to see is uh strategic supply chains, strategic relationships 119 00:07:09,640 --> 00:07:14,000 Speaker 1: which are brought together through technology, and that that vertical integration, 120 00:07:14,080 --> 00:07:18,040 Speaker 1: which once was through ownership, will now be through technology integration. 121 00:07:19,040 --> 00:07:22,560 Speaker 1: A couple of questions, super interesting when you said welcome 122 00:07:22,600 --> 00:07:27,920 Speaker 1: to did you mean that we are doing things because 123 00:07:27,960 --> 00:07:30,760 Speaker 1: of this crisis and especially today that we might not 124 00:07:30,960 --> 00:07:35,120 Speaker 1: have otherwise done until is exactly what I say, exactly 125 00:07:35,200 --> 00:07:37,920 Speaker 1: give me, give me an example, a really concrete example. 126 00:07:38,360 --> 00:07:40,720 Speaker 1: One of my one of my clients was I saying 127 00:07:41,080 --> 00:07:45,520 Speaker 1: it would take them maybe a month to onboard a supplier. 128 00:07:46,320 --> 00:07:48,640 Speaker 1: But if you if I got a new supplier, by 129 00:07:48,760 --> 00:07:51,400 Speaker 1: time I've worked with them, I've done due diligence, I've 130 00:07:51,400 --> 00:07:54,720 Speaker 1: figured out their systems and my systems have integrated them. 131 00:07:54,840 --> 00:07:57,080 Speaker 1: Maybe it takes a month or longer, could take even 132 00:07:57,120 --> 00:08:01,040 Speaker 1: three months. And through the pandemic, um there was this 133 00:08:01,120 --> 00:08:04,240 Speaker 1: necessity to bring in the supply straight away. And guess 134 00:08:04,280 --> 00:08:07,040 Speaker 1: what if you really break down some of those orthodoxes 135 00:08:07,040 --> 00:08:08,800 Speaker 1: of the past and there's some of those practices, and 136 00:08:08,840 --> 00:08:11,080 Speaker 1: you ask why, why why you can do it in 137 00:08:11,120 --> 00:08:15,120 Speaker 1: three days straight away? And you can figure out with 138 00:08:15,240 --> 00:08:17,720 Speaker 1: some technology and with some new processes, you can do 139 00:08:17,760 --> 00:08:20,320 Speaker 1: that in three days. Because of that necessity is driving 140 00:08:20,720 --> 00:08:26,000 Speaker 1: that innovation in the process. On the demand side. You know, basically, 141 00:08:26,280 --> 00:08:30,160 Speaker 1: supply chains have always grown up thinking about what happened 142 00:08:30,240 --> 00:08:35,720 Speaker 1: last yesterday, last week, last month, last year, will happen 143 00:08:36,000 --> 00:08:40,760 Speaker 1: next month, next week? Right? And and now what we 144 00:08:40,840 --> 00:08:43,719 Speaker 1: see is, um, that's not not the case. You know, 145 00:08:43,840 --> 00:08:46,240 Speaker 1: the last two years are not a good proxy for 146 00:08:46,280 --> 00:08:48,320 Speaker 1: what's going to happen in the next two years, We've 147 00:08:48,320 --> 00:08:51,520 Speaker 1: got to really start thinking about what are the drivers 148 00:08:51,559 --> 00:08:55,280 Speaker 1: that impact demand. The drivers could be a people working 149 00:08:55,280 --> 00:08:58,640 Speaker 1: from home or not. You know, have I got another 150 00:08:58,679 --> 00:09:01,720 Speaker 1: spike happening at school? Is open? Are? You know? Where 151 00:09:01,720 --> 00:09:06,280 Speaker 1: are we maybe even hospitalizations in people movement, Whether all 152 00:09:06,320 --> 00:09:09,199 Speaker 1: of these different aspects come into play to really understand 153 00:09:09,200 --> 00:09:11,880 Speaker 1: at a zip code level, at a skew level, at 154 00:09:11,880 --> 00:09:15,720 Speaker 1: a product level, you know, what is the demand and 155 00:09:15,720 --> 00:09:19,640 Speaker 1: and so now we can use AI and analyze the data, 156 00:09:19,800 --> 00:09:23,360 Speaker 1: refine the data that we have from new sources, not 157 00:09:23,520 --> 00:09:25,560 Speaker 1: just from within my four walls of what did I 158 00:09:25,600 --> 00:09:29,559 Speaker 1: sell yesterday, last month, last last quarter. I can now 159 00:09:29,640 --> 00:09:32,880 Speaker 1: start thinking about all the external data. I can look 160 00:09:32,880 --> 00:09:35,160 Speaker 1: at social media, I can look at you know, kind 161 00:09:35,200 --> 00:09:38,840 Speaker 1: of data from the state and from local authorities and 162 00:09:39,160 --> 00:09:43,400 Speaker 1: use that to actually inform what's happening on the ground 163 00:09:43,440 --> 00:09:46,320 Speaker 1: and what people's behaviors are and what will that mean 164 00:09:46,400 --> 00:09:50,800 Speaker 1: for demand. Those kinds of much more sophisticated forecasting models. 165 00:09:52,360 --> 00:09:55,720 Speaker 1: Three years ago, we could have built them, but we 166 00:09:55,720 --> 00:09:58,360 Speaker 1: didn't see the need. Correct, And what you're saying is 167 00:09:58,640 --> 00:10:00,720 Speaker 1: all of a sudden, we now see the need and 168 00:10:00,720 --> 00:10:03,280 Speaker 1: so we're building. The capability was there but not but 169 00:10:03,360 --> 00:10:06,240 Speaker 1: not a motivation? Is that what you're saying, Absolutely, when 170 00:10:06,240 --> 00:10:08,320 Speaker 1: you invest in technology, you want to make sure that 171 00:10:08,360 --> 00:10:11,160 Speaker 1: there's a return on that investment, right, that you can 172 00:10:11,160 --> 00:10:18,520 Speaker 1: actually drive real value and pre pandemic. From a forecasting perspective, 173 00:10:19,280 --> 00:10:22,760 Speaker 1: it was less less important. Let's go back to two 174 00:10:22,840 --> 00:10:26,040 Speaker 1: years ago as a as A for example, was three 175 00:10:26,080 --> 00:10:28,920 Speaker 1: years ago? What have you? How many people would have 176 00:10:28,920 --> 00:10:32,319 Speaker 1: had a deep map of their supply chain back then? 177 00:10:32,920 --> 00:10:38,080 Speaker 1: Very few of the fortune the top two did not 178 00:10:39,000 --> 00:10:42,840 Speaker 1: have the picture and the map that they needed. And 179 00:10:42,880 --> 00:10:44,680 Speaker 1: what percentage now and have the picture of the map 180 00:10:44,679 --> 00:10:47,200 Speaker 1: I needed? I say, it's a good question. I don't 181 00:10:47,240 --> 00:10:49,040 Speaker 1: know certainly. All of the clients that I work with, 182 00:10:49,080 --> 00:10:52,160 Speaker 1: there's a top priority for them, particularly now as many 183 00:10:52,200 --> 00:10:55,280 Speaker 1: of them have got exposures to semiconductors and the like, 184 00:10:55,480 --> 00:10:58,880 Speaker 1: so they're now having to go at much much more 185 00:10:58,920 --> 00:11:02,040 Speaker 1: detailed analysis of their supply chain. So I think they've 186 00:11:02,080 --> 00:11:05,560 Speaker 1: really had to, you know, kind of up the game. Ye, 187 00:11:06,679 --> 00:11:10,319 Speaker 1: your phone must have been bringing off the hook for 188 00:11:10,360 --> 00:11:15,240 Speaker 1: the last two years. How crazy has your life been? 189 00:11:15,600 --> 00:11:19,120 Speaker 1: I mean, I'm fortunate that I work in supply chain 190 00:11:19,160 --> 00:11:21,800 Speaker 1: and This has absolutely the most exciting time to work 191 00:11:21,800 --> 00:11:25,360 Speaker 1: in supply chain, and whether it's you know, supporting clients 192 00:11:25,360 --> 00:11:31,040 Speaker 1: with vaccine distribution and working through the issues of transparency 193 00:11:31,040 --> 00:11:33,200 Speaker 1: and making sure that we understand how how to do 194 00:11:33,320 --> 00:11:37,959 Speaker 1: that through too just supply issues and um and and 195 00:11:38,000 --> 00:11:41,120 Speaker 1: helping clients navigate this volatile PERIODI is certainly one of 196 00:11:41,160 --> 00:11:43,600 Speaker 1: the one of the positives that I think will come 197 00:11:43,600 --> 00:11:47,120 Speaker 1: out of this is is more interesting supply chain and 198 00:11:47,160 --> 00:11:50,719 Speaker 1: therefore us being able to attract new talent because one 199 00:11:50,760 --> 00:11:52,800 Speaker 1: thing that we have got to do to solve these 200 00:11:52,880 --> 00:11:58,480 Speaker 1: complex issues is have diverse talent. And I I personally 201 00:11:58,520 --> 00:12:03,520 Speaker 1: believe that and we bring in more diverse talent cognitive, ethnic, 202 00:12:03,840 --> 00:12:08,160 Speaker 1: gender diversity, we're much better able to solve for the 203 00:12:08,200 --> 00:12:11,880 Speaker 1: world's most complex issues, and we'll see a much richer 204 00:12:11,960 --> 00:12:15,559 Speaker 1: ability to solve for the future. How long does it 205 00:12:15,600 --> 00:12:19,599 Speaker 1: take to build one of these maps. Let's say I 206 00:12:19,720 --> 00:12:24,040 Speaker 1: come to you unfortunate for one reason another though I 207 00:12:24,120 --> 00:12:28,240 Speaker 1: have simply neglected, I have the the most kind of 208 00:12:29,920 --> 00:12:34,800 Speaker 1: plain vanilla supply chain map, and I'm freaking out, and 209 00:12:34,840 --> 00:12:36,760 Speaker 1: I call you up and I say I want to 210 00:12:36,800 --> 00:12:40,560 Speaker 1: go gold standard as fast as possible. I'm a company 211 00:12:40,600 --> 00:12:44,520 Speaker 1: with sales of I don't know, fifty billion dollars. Okay, 212 00:12:44,960 --> 00:12:51,800 Speaker 1: let's assume complex international, you know, like not an easy kisse. Um, 213 00:12:51,880 --> 00:12:55,280 Speaker 1: how tell me how long? Tell me how many people 214 00:12:55,280 --> 00:12:58,040 Speaker 1: would work on this problem? Tell me tell me how 215 00:12:58,080 --> 00:13:02,679 Speaker 1: you would start? Yeah, it's actually, um, it's a bit 216 00:13:02,720 --> 00:13:05,120 Speaker 1: of a trick question, right, because it's a lot easier 217 00:13:05,160 --> 00:13:07,480 Speaker 1: than you think. And the reason it's a lot easier 218 00:13:07,480 --> 00:13:10,000 Speaker 1: than you think is because many of the suppliers out 219 00:13:10,040 --> 00:13:13,439 Speaker 1: there are already supplying other companies who already have mapped 220 00:13:13,440 --> 00:13:17,280 Speaker 1: their supply chain. So we work with platform companies that 221 00:13:17,320 --> 00:13:21,679 Speaker 1: are able to accelerate this journey towards critical risk modeling. 222 00:13:22,600 --> 00:13:26,720 Speaker 1: We map the tier one suppliers, we prioritize the supply base, 223 00:13:27,160 --> 00:13:30,680 Speaker 1: and in weeks, yes, weeks, we're able to get onboarded 224 00:13:30,760 --> 00:13:35,640 Speaker 1: companies a view, a view of their deep supply chain, 225 00:13:36,280 --> 00:13:40,320 Speaker 1: that's of their key suppliers in their supply chain. People 226 00:13:40,360 --> 00:13:43,439 Speaker 1: are willing to share that kind of data. Yes, absolutely, 227 00:13:44,080 --> 00:13:47,600 Speaker 1: that's the business model for these platform providers. You know, 228 00:13:47,679 --> 00:13:51,160 Speaker 1: we partner with them. They make sure that we have 229 00:13:51,280 --> 00:13:55,880 Speaker 1: the visibility, and that visibility is permissioned and restricted. Um, 230 00:13:56,320 --> 00:13:58,480 Speaker 1: we use that in our own supply chain, and it's 231 00:13:58,480 --> 00:14:02,960 Speaker 1: an incredibly powerful tool for getting into the deep supply chain. 232 00:14:03,160 --> 00:14:06,480 Speaker 1: And then over time we can continue to build out 233 00:14:06,559 --> 00:14:09,640 Speaker 1: and the richness of that data and the modeling, and 234 00:14:09,679 --> 00:14:11,800 Speaker 1: then you have to start looking at how am I 235 00:14:11,960 --> 00:14:15,640 Speaker 1: organized so I can use that data um and use 236 00:14:15,720 --> 00:14:18,760 Speaker 1: that much more effectively. So what are my internal processes? 237 00:14:18,800 --> 00:14:22,000 Speaker 1: And that's actually where the potentially the harder piece comes, 238 00:14:22,040 --> 00:14:26,600 Speaker 1: which is reorganizing and getting people to to use data 239 00:14:26,640 --> 00:14:28,800 Speaker 1: in a different way. I have a view that we 240 00:14:28,840 --> 00:14:31,560 Speaker 1: should all have a virtual assistant by the side of 241 00:14:31,560 --> 00:14:34,200 Speaker 1: our desks. In the same way that you you have 242 00:14:34,920 --> 00:14:37,200 Speaker 1: a virtual as system at home, we should all have 243 00:14:37,240 --> 00:14:39,840 Speaker 1: one in the supply chain. We can interact with natural 244 00:14:39,920 --> 00:14:42,320 Speaker 1: language and we can ask what's and hey, you know, 245 00:14:42,400 --> 00:14:45,160 Speaker 1: tell me what happens if if there's an issue at 246 00:14:45,200 --> 00:14:47,960 Speaker 1: Malaysia Airport, what are my suppliers are going to be affected? 247 00:14:48,320 --> 00:14:51,240 Speaker 1: Guess what? We internally already have that for our own 248 00:14:51,320 --> 00:14:55,000 Speaker 1: supply chain system. But my vision is that every supply 249 00:14:55,080 --> 00:14:58,120 Speaker 1: chain professional will have that virtual assistant and that they 250 00:14:58,120 --> 00:15:01,480 Speaker 1: can access the data. But that acquires a different way 251 00:15:01,480 --> 00:15:04,240 Speaker 1: of working. But if we get that right to me, 252 00:15:04,320 --> 00:15:06,880 Speaker 1: he can have a cool, cool environment. We can attract 253 00:15:06,880 --> 00:15:12,200 Speaker 1: more talent because instead of doing mundane, dull tasks transactional task, 254 00:15:12,200 --> 00:15:15,880 Speaker 1: they can actually be doing value adding tasks. Do you 255 00:15:16,280 --> 00:15:20,160 Speaker 1: walk me through this? You mentioned this little bit about 256 00:15:20,400 --> 00:15:24,200 Speaker 1: what you do with the information. So I'm I'm the 257 00:15:24,360 --> 00:15:28,800 Speaker 1: same company with this large, complex business. You've not given 258 00:15:28,840 --> 00:15:33,800 Speaker 1: me this much more detailed, accurate map of what my 259 00:15:33,840 --> 00:15:37,560 Speaker 1: supply him looks like. And we see a problem one 260 00:15:37,560 --> 00:15:41,800 Speaker 1: of my suppliers, suppliers, supplier deep somewhere on the other 261 00:15:41,800 --> 00:15:44,520 Speaker 1: side of the world. Who this is one of my 262 00:15:44,560 --> 00:15:49,400 Speaker 1: critical components. And I see, Oh, it's supposed to come 263 00:15:49,440 --> 00:15:51,320 Speaker 1: next week. I don't think it's going to come for 264 00:15:51,480 --> 00:15:56,320 Speaker 1: two months. What what do I do with that information? 265 00:15:56,320 --> 00:15:58,480 Speaker 1: How do I react to it? Well, that back in 266 00:15:58,680 --> 00:16:01,800 Speaker 1: the year two thousand not here and Ericsson, if you remember, 267 00:16:01,800 --> 00:16:05,920 Speaker 1: they were market leaders in mobile phones UM before before 268 00:16:05,920 --> 00:16:10,680 Speaker 1: the world changed. They had two two very different strategies 269 00:16:10,680 --> 00:16:17,000 Speaker 1: here around supplier management and UM. And actually Ericsson failed 270 00:16:17,440 --> 00:16:20,200 Speaker 1: big time when there was a fire in Albuquerque, in 271 00:16:20,480 --> 00:16:24,760 Speaker 1: New Mexico at a Philip's chip manufacturing point. And so 272 00:16:24,800 --> 00:16:27,400 Speaker 1: this was all to do with internal processes. How you 273 00:16:27,440 --> 00:16:30,720 Speaker 1: handle the information. The information came through that there was 274 00:16:30,760 --> 00:16:33,280 Speaker 1: a fire, a lot of the chips had got you know, 275 00:16:33,440 --> 00:16:36,960 Speaker 1: soaked and saturated and smoked damage, and UM and a 276 00:16:37,000 --> 00:16:40,560 Speaker 1: mid manager at Ericson had had kind of got in 277 00:16:40,600 --> 00:16:45,360 Speaker 1: contact with Phillips and had taken a risk assessment that 278 00:16:45,560 --> 00:16:47,200 Speaker 1: the place was going to be up and running quite 279 00:16:47,240 --> 00:16:51,800 Speaker 1: soon and there was no major action required, no major disruption. Nokia, 280 00:16:51,840 --> 00:16:55,400 Speaker 1: on the other hand, had much more collaborative approach and 281 00:16:55,440 --> 00:16:57,840 Speaker 1: they said, no, this, this could be a real issue here. 282 00:16:57,880 --> 00:17:00,800 Speaker 1: I don't trust that information. I'm not going to be 283 00:17:00,880 --> 00:17:05,320 Speaker 1: too complacent and and literally flew over, went down, did 284 00:17:05,320 --> 00:17:07,439 Speaker 1: the risk assessment, said no, this, this is not going 285 00:17:07,480 --> 00:17:10,520 Speaker 1: to be up and running in any near term. Um 286 00:17:10,600 --> 00:17:14,560 Speaker 1: and went and triggered some other contracts they had and 287 00:17:14,640 --> 00:17:18,280 Speaker 1: basically soaked up all of the supply of those chips. 288 00:17:19,080 --> 00:17:23,320 Speaker 1: Long story short, Ericsson were unable to supply the market 289 00:17:23,480 --> 00:17:27,600 Speaker 1: and ultimately failed and the company who were no longer 290 00:17:27,640 --> 00:17:30,840 Speaker 1: making mobile phones and Nokia went from strength to strength 291 00:17:30,920 --> 00:17:36,480 Speaker 1: until another technology evolution took place. But the processes and 292 00:17:36,520 --> 00:17:40,560 Speaker 1: the strategies around how to handle the supply signal will 293 00:17:40,600 --> 00:17:44,480 Speaker 1: handled very differently, and so so you had both of 294 00:17:44,520 --> 00:17:47,680 Speaker 1: them had the same quantitative information. One of them though 295 00:17:47,840 --> 00:17:50,760 Speaker 1: added a qualitative layer on top of that where they 296 00:17:50,800 --> 00:17:55,520 Speaker 1: went and made an assessment of whether the the supplier 297 00:17:55,840 --> 00:17:59,960 Speaker 1: was was being trustworthy in their assessment of how to 298 00:18:00,200 --> 00:18:02,879 Speaker 1: interesting to work correct. And this is this is where 299 00:18:03,520 --> 00:18:08,440 Speaker 1: the organization design and the skills and the capability will 300 00:18:08,480 --> 00:18:11,880 Speaker 1: always be super important. And I think, yes, we've got 301 00:18:11,880 --> 00:18:14,800 Speaker 1: to make sure that we have the right um that 302 00:18:14,920 --> 00:18:17,119 Speaker 1: the number of suppliers and we've got kind of the 303 00:18:17,160 --> 00:18:20,640 Speaker 1: balance of de risking a suppliers by having a number 304 00:18:20,640 --> 00:18:23,160 Speaker 1: of contracts in place, and we haven't got sort of 305 00:18:23,359 --> 00:18:28,000 Speaker 1: an exposure of one supplier. But then have I got 306 00:18:28,000 --> 00:18:32,640 Speaker 1: the right skills and capability and a culture that that 307 00:18:32,760 --> 00:18:35,960 Speaker 1: listens to risk and risk management and and is is 308 00:18:36,000 --> 00:18:40,800 Speaker 1: absorbing that versus a culture of maybe complacency and trust 309 00:18:40,880 --> 00:18:45,200 Speaker 1: which could lead to some failure. M hmm. I think, 310 00:18:45,280 --> 00:18:47,800 Speaker 1: I think, I think you do get some are hard moments. 311 00:18:48,040 --> 00:18:50,000 Speaker 1: I do think, you know, particularly when you start to 312 00:18:50,800 --> 00:18:54,400 Speaker 1: look into um as you say, the deep supply chain map, 313 00:18:54,440 --> 00:18:56,800 Speaker 1: you start to realize where those bottom necks are and 314 00:18:57,000 --> 00:18:59,960 Speaker 1: they're not obvious. They're not obvious because when you start 315 00:19:00,040 --> 00:19:01,800 Speaker 1: to model out and you start to see where those 316 00:19:01,840 --> 00:19:03,720 Speaker 1: flows are. You might say, hey, I've got I've got 317 00:19:03,720 --> 00:19:07,200 Speaker 1: too much risk here because of your one one location. 318 00:19:07,320 --> 00:19:10,439 Speaker 1: So I think it's when you do that modeling of 319 00:19:10,520 --> 00:19:14,480 Speaker 1: the supply chain um both in terms of physical flows, 320 00:19:14,560 --> 00:19:18,399 Speaker 1: network modeling and the deep network, that you you start 321 00:19:18,480 --> 00:19:23,240 Speaker 1: to see those vulnerabilities and nobody. The way that organizations 322 00:19:23,080 --> 00:19:25,400 Speaker 1: are set up, you you tend to have people focusing 323 00:19:25,400 --> 00:19:29,000 Speaker 1: on one category or one product line. You don't necessarily 324 00:19:29,000 --> 00:19:31,720 Speaker 1: have people looking all the way across. What is the 325 00:19:31,800 --> 00:19:35,159 Speaker 1: hardest problem to solve on this? In these kinds of 326 00:19:35,560 --> 00:19:37,080 Speaker 1: you said one part of it you already said, well, 327 00:19:37,280 --> 00:19:40,800 Speaker 1: it can be surprisingly easy if your suppliers have maps themselves. 328 00:19:41,320 --> 00:19:45,480 Speaker 1: What's the hard part? I think that there's there's to 329 00:19:46,200 --> 00:19:50,800 Speaker 1: the two hardest parts. M One is is the cleanliness 330 00:19:50,800 --> 00:19:55,199 Speaker 1: of data. Right, It's it's very it's very typical in 331 00:19:55,280 --> 00:19:59,440 Speaker 1: large organizations for the data to be dirty. And like oil, right, 332 00:19:59,520 --> 00:20:02,680 Speaker 1: if you've get dirty oil, it's a problem. Right, if 333 00:20:02,720 --> 00:20:05,280 Speaker 1: you get nice refined oil, it's valuable. I think the 334 00:20:05,320 --> 00:20:07,639 Speaker 1: same for data. When you refine it and you clean 335 00:20:07,680 --> 00:20:09,120 Speaker 1: it and you use it in the right way, it's 336 00:20:09,240 --> 00:20:12,480 Speaker 1: very valuable. But if it's dirty UM. Then it's a 337 00:20:12,520 --> 00:20:16,119 Speaker 1: problem I have. You know, a client, a retailer couldn't 338 00:20:16,160 --> 00:20:20,600 Speaker 1: understand why they couldn't UM have on shelf availability. They 339 00:20:20,640 --> 00:20:24,679 Speaker 1: couldn't they couldn't replenish the shelf quick enough. And the 340 00:20:24,720 --> 00:20:27,200 Speaker 1: reason was that in the system it was recorded as 341 00:20:27,320 --> 00:20:31,160 Speaker 1: the shelf was recorded as ten centimeters not not a meter. 342 00:20:31,720 --> 00:20:34,119 Speaker 1: So who you know, when I send one product, I 343 00:20:34,160 --> 00:20:38,320 Speaker 1: fill the shelf up I need because the system thinks 344 00:20:38,359 --> 00:20:40,159 Speaker 1: that the shelf is this big. Actually the shelf is 345 00:20:40,200 --> 00:20:45,320 Speaker 1: this big. So you you why how long had that 346 00:20:45,520 --> 00:20:47,600 Speaker 1: error existed in? There have been going on for a 347 00:20:47,640 --> 00:20:50,600 Speaker 1: while for a while, and and then they have sort 348 00:20:50,600 --> 00:20:53,600 Speaker 1: of manual workarounds. But but you know, if you lose 349 00:20:53,640 --> 00:20:56,520 Speaker 1: that tribal knowledge, you use that manual work around, then 350 00:20:56,560 --> 00:20:59,600 Speaker 1: you start to realize, you know, what's actually happening, and 351 00:20:59,640 --> 00:21:03,840 Speaker 1: then to find the systemic solution. How how long into 352 00:21:03,880 --> 00:21:11,360 Speaker 1: COVID before you realized that your world was going to explode? Well, actually, 353 00:21:11,920 --> 00:21:14,240 Speaker 1: pretty early on some of the leaders were coming to 354 00:21:14,320 --> 00:21:19,120 Speaker 1: us saying we need help. It was one consumer products company. 355 00:21:19,960 --> 00:21:24,520 Speaker 1: I remember literally in in that March April time, we 356 00:21:24,560 --> 00:21:28,760 Speaker 1: had a project running where we were doing this data 357 00:21:28,880 --> 00:21:32,600 Speaker 1: driven demand forecasting, and we created a dashboard for them. 358 00:21:32,840 --> 00:21:36,560 Speaker 1: Within a month, they could see all of their products, 359 00:21:37,080 --> 00:21:40,720 Speaker 1: all of their customers retailers at a zip code level, 360 00:21:40,920 --> 00:21:42,879 Speaker 1: and we had a map of where we thought the 361 00:21:43,000 --> 00:21:46,159 Speaker 1: demand would go. In Minneapolis. They were not going to 362 00:21:46,200 --> 00:21:50,639 Speaker 1: be a significant drop off of buying single chocolates on 363 00:21:50,680 --> 00:21:53,919 Speaker 1: the way to work as a snack because there's nobody 364 00:21:53,920 --> 00:21:56,840 Speaker 1: going to work. Instead, they would be their family packs 365 00:21:56,880 --> 00:21:59,680 Speaker 1: were going to go up by because people would be 366 00:22:00,080 --> 00:22:03,240 Speaker 1: would be gorging on them at home. So that signal 367 00:22:03,359 --> 00:22:08,119 Speaker 1: was super important for that consumer products company, um of 368 00:22:08,480 --> 00:22:12,600 Speaker 1: Food Food Company to to then repurpose their manufacturing lines 369 00:22:12,680 --> 00:22:15,919 Speaker 1: to move from singles to family packs. And if they 370 00:22:15,920 --> 00:22:19,120 Speaker 1: could get that signal ahead of the retailers giving them 371 00:22:19,119 --> 00:22:21,600 Speaker 1: that signal, they could get the ground truth. Then they 372 00:22:21,600 --> 00:22:25,720 Speaker 1: could they could proactively sort out that was happening in 373 00:22:26,040 --> 00:22:30,440 Speaker 1: April time. But it was new technology and new new analysis, 374 00:22:30,600 --> 00:22:32,760 Speaker 1: and within a month they had that new analysis. It 375 00:22:32,880 --> 00:22:35,840 Speaker 1: was it was an incredible piece of work. Well, so 376 00:22:35,880 --> 00:22:39,960 Speaker 1: within a month they had they had reconfigured their manufacturing 377 00:22:40,000 --> 00:22:43,719 Speaker 1: lines to do more family packs than singles, absolutely and 378 00:22:43,760 --> 00:22:46,479 Speaker 1: with and within a month they had the data and 379 00:22:46,560 --> 00:22:49,639 Speaker 1: the facts behind it to to help them, you know, um, 380 00:22:50,080 --> 00:22:52,320 Speaker 1: get them to get the balance right, to stay with 381 00:22:52,320 --> 00:22:55,199 Speaker 1: that example that over the last let's just say six months, 382 00:22:55,680 --> 00:23:00,480 Speaker 1: they would be monitors and gradually readjusting their mix as 383 00:23:00,880 --> 00:23:04,080 Speaker 1: people start going back to work. Well, and then and 384 00:23:04,080 --> 00:23:06,159 Speaker 1: then we come back to this this problem which is 385 00:23:06,160 --> 00:23:09,840 Speaker 1: the bullwhip effect, right, and the bull whip effect is 386 00:23:10,560 --> 00:23:13,960 Speaker 1: a real problem that we have at the moment um. 387 00:23:14,000 --> 00:23:17,520 Speaker 1: What is the bullwhip effect? The bullwhip effect says that 388 00:23:17,680 --> 00:23:24,440 Speaker 1: I can see a demand signal for maybe extra five units, 389 00:23:24,520 --> 00:23:27,240 Speaker 1: so I forecast I'm gonna sell an extra five units. 390 00:23:27,280 --> 00:23:29,760 Speaker 1: But my distributor says, oh, they're going to sell an 391 00:23:29,760 --> 00:23:31,879 Speaker 1: extra five units, but they typically get it wrong. So 392 00:23:31,880 --> 00:23:33,800 Speaker 1: I'm going to say an extra ten units. So they 393 00:23:33,840 --> 00:23:36,520 Speaker 1: put that back onto their supply and say, hey, you 394 00:23:36,560 --> 00:23:39,280 Speaker 1: know this company is now gone, is gone extra ten years. 395 00:23:39,359 --> 00:23:41,920 Speaker 1: They say, oh, we'll make that twenty and then their 396 00:23:41,960 --> 00:23:44,000 Speaker 1: supplies says, oh, they typically, you know, I don't want 397 00:23:44,000 --> 00:23:46,320 Speaker 1: to go short here, so we'll make it fifty. Before 398 00:23:46,359 --> 00:23:49,200 Speaker 1: you know it, my five units of demand further down 399 00:23:49,200 --> 00:23:53,600 Speaker 1: the supply chain is fifty units. Now this happens where 400 00:23:53,640 --> 00:23:56,400 Speaker 1: you have a lack of trust in the demand signal, 401 00:23:57,520 --> 00:23:59,560 Speaker 1: because if you don't really trust that demand signal, you 402 00:23:59,600 --> 00:24:03,440 Speaker 1: always inflated a little bit um. And so what's happening 403 00:24:03,480 --> 00:24:05,600 Speaker 1: at the moment, We've got problems on both sides. As 404 00:24:05,600 --> 00:24:08,080 Speaker 1: I said, when with that, that demand signal is hard 405 00:24:08,119 --> 00:24:10,919 Speaker 1: to understand because we don't really know what what the 406 00:24:11,000 --> 00:24:13,800 Speaker 1: new sort of behavior is. And the supply signal, we 407 00:24:13,840 --> 00:24:17,320 Speaker 1: know is disruptive because we've got this repurposing going on 408 00:24:17,400 --> 00:24:21,040 Speaker 1: and rebalancing in the supply. So what happens now is 409 00:24:21,760 --> 00:24:24,600 Speaker 1: I'm going, Hey, I'm going to order ten, not five. 410 00:24:24,640 --> 00:24:27,560 Speaker 1: I'm gonna attend because you know, I'm worried about my 411 00:24:27,600 --> 00:24:30,560 Speaker 1: supply in fact and my order the whole season's worth 412 00:24:30,560 --> 00:24:33,480 Speaker 1: in one go. I'm instead of having weekly orders, I 413 00:24:33,520 --> 00:24:36,520 Speaker 1: might put monthly orders in all quarterly order. And so 414 00:24:36,600 --> 00:24:39,640 Speaker 1: then you get this bumper bullwhip effect where oh, they 415 00:24:39,680 --> 00:24:41,840 Speaker 1: put in a whole quarter of wow demands picking up. 416 00:24:41,840 --> 00:24:44,520 Speaker 1: I'm gonna double that. I'm going to triple that. So 417 00:24:45,400 --> 00:24:48,480 Speaker 1: I'm worried about this amplitude effect that's happening as people 418 00:24:48,520 --> 00:24:51,159 Speaker 1: start to say I'm gonna put bigger supply points in 419 00:24:51,240 --> 00:24:54,680 Speaker 1: because they don't trust my supply base, and people say, 420 00:24:54,840 --> 00:24:58,280 Speaker 1: you don't really know your demand, so actually we're going 421 00:24:58,359 --> 00:25:03,199 Speaker 1: to continue to inflate um. And so that has problems 422 00:25:03,280 --> 00:25:05,520 Speaker 1: obviously because there's going to be some winners and some 423 00:25:05,560 --> 00:25:08,920 Speaker 1: losers with that scenario. So it could be the case 424 00:25:09,640 --> 00:25:14,000 Speaker 1: I'm in a competitive marketplace. I might trust my own data, 425 00:25:14,320 --> 00:25:18,480 Speaker 1: but I don't trust you trust your data, right, So 426 00:25:18,560 --> 00:25:21,720 Speaker 1: I behave strategically and say, well, I don't know what 427 00:25:21,800 --> 00:25:25,119 Speaker 1: Jonathan is doing. He could be he could be holding 428 00:25:25,200 --> 00:25:27,440 Speaker 1: this thing. So even though I only need five units, 429 00:25:27,440 --> 00:25:31,520 Speaker 1: I'm going to return. Yeah, exactly, But how do you 430 00:25:31,600 --> 00:25:36,160 Speaker 1: restore trust systemically? Then? Yeah, you you have to build 431 00:25:36,200 --> 00:25:41,040 Speaker 1: trust I think through technology, because you have to find 432 00:25:41,080 --> 00:25:44,280 Speaker 1: those suppliers and those strategic supply points, and you have 433 00:25:44,440 --> 00:25:48,040 Speaker 1: to start sharing data and actually proving that that five 434 00:25:48,200 --> 00:25:51,560 Speaker 1: is real, right, and that you shouldn't be inflating it. 435 00:25:51,840 --> 00:25:54,920 Speaker 1: And I also need to know that you, Malcolm, is 436 00:25:54,960 --> 00:25:57,639 Speaker 1: my supplier, right, that that you have got the capacity 437 00:25:57,720 --> 00:26:00,719 Speaker 1: that I need, Because if I'm worried that you might 438 00:26:00,760 --> 00:26:03,040 Speaker 1: allocate your capacity to somewhere else, then I'm going to 439 00:26:03,119 --> 00:26:06,119 Speaker 1: double my demand onto you so that you give me 440 00:26:06,200 --> 00:26:08,280 Speaker 1: some if I give you, if I order thirty, maybe 441 00:26:08,280 --> 00:26:11,280 Speaker 1: I'll get the five that I wanted. So you start 442 00:26:11,320 --> 00:26:14,400 Speaker 1: to worry a little bit about classic hoarding problem really 443 00:26:14,400 --> 00:26:17,000 Speaker 1: because I'm not sure I fully understand. So I can 444 00:26:17,119 --> 00:26:23,480 Speaker 1: see how on an individual company level, technology can allow 445 00:26:23,520 --> 00:26:27,160 Speaker 1: me to get to create a far more accurate assessment 446 00:26:27,160 --> 00:26:31,720 Speaker 1: of what my true demand for something is. But but 447 00:26:32,440 --> 00:26:34,480 Speaker 1: everyone has to have trust in our own estimates in 448 00:26:34,560 --> 00:26:38,040 Speaker 1: order for the system to work again and for hoarding 449 00:26:38,080 --> 00:26:41,360 Speaker 1: to be prevented. So I don't how do you get 450 00:26:41,480 --> 00:26:46,240 Speaker 1: how do you go from individual act or trust two 451 00:26:47,080 --> 00:26:54,639 Speaker 1: everyone in the marketplace trusting everyone else's estimates. I I 452 00:26:55,320 --> 00:26:58,920 Speaker 1: think you have to do it pace pace by pace, 453 00:26:59,040 --> 00:27:01,960 Speaker 1: and I think you have you get your own demand 454 00:27:02,000 --> 00:27:06,320 Speaker 1: signal clear. UM. You have to build the relationships with 455 00:27:06,359 --> 00:27:09,720 Speaker 1: your suppliers, make sure you build trust with them, and 456 00:27:10,359 --> 00:27:13,440 Speaker 1: you put technology in place to share information with them. 457 00:27:13,920 --> 00:27:17,760 Speaker 1: And over time you have to you have to just 458 00:27:17,800 --> 00:27:23,320 Speaker 1: start working working through that UM and hopefully we we 459 00:27:23,359 --> 00:27:27,320 Speaker 1: will start to see the supply base rebalancing UM and settling, 460 00:27:28,240 --> 00:27:31,200 Speaker 1: the vibrations calming down a bit, the bullwidth perfect calming 461 00:27:31,240 --> 00:27:34,040 Speaker 1: down a bit, and we'll have a more secure supply 462 00:27:34,240 --> 00:27:36,720 Speaker 1: of products. And then we'll be able to trust the 463 00:27:36,760 --> 00:27:39,800 Speaker 1: demand signal. The holiday season is a big, big effect 464 00:27:39,840 --> 00:27:41,920 Speaker 1: at the moment, right. You know, some of the analysis 465 00:27:41,920 --> 00:27:45,439 Speaker 1: that we've seen says that the shoppers are more likely, 466 00:27:46,400 --> 00:27:50,320 Speaker 1: as you would expect, to start shopping earlier right than 467 00:27:50,359 --> 00:27:54,600 Speaker 1: they have in the past, and one in four global 468 00:27:54,640 --> 00:27:58,760 Speaker 1: consumers have already started shopping, so you're starting to see 469 00:27:58,800 --> 00:28:03,359 Speaker 1: this early consumer demand picking up now. At the same time, 470 00:28:03,359 --> 00:28:07,240 Speaker 1: where what we're seeing in analysis is that they're unlikely 471 00:28:07,320 --> 00:28:10,000 Speaker 1: to spend more this year than they did last year. 472 00:28:10,880 --> 00:28:15,160 Speaker 1: So it's interesting or only marginally more. So they're shopping earlier, 473 00:28:15,440 --> 00:28:18,880 Speaker 1: but they're not going to shop shop more. So one 474 00:28:18,880 --> 00:28:21,359 Speaker 1: of the interesting things here is again is understanding the 475 00:28:21,440 --> 00:28:25,200 Speaker 1: behavior is does that mean I pick up that signal earlier, 476 00:28:25,240 --> 00:28:28,080 Speaker 1: that demand is increasing, that I've got a big, big 477 00:28:28,119 --> 00:28:30,600 Speaker 1: economic bounds, or does it mean that people are just 478 00:28:30,760 --> 00:28:34,880 Speaker 1: buying earlier because they're worried about the supply point those 479 00:28:34,920 --> 00:28:38,400 Speaker 1: two forecasts is huge. One is bumper crop, the other 480 00:28:38,520 --> 00:28:41,920 Speaker 1: is the same crap but very very different demands on 481 00:28:41,960 --> 00:28:47,240 Speaker 1: your manufacturing distribution correct, and that's where this more sophisticated 482 00:28:47,480 --> 00:28:52,480 Speaker 1: driver based analysis of demand becomes really important. And then 483 00:28:52,920 --> 00:28:56,880 Speaker 1: building that type relationship with my supply base, so I'm 484 00:28:56,960 --> 00:28:58,920 Speaker 1: keeping them up to speed as to what we're seeing 485 00:28:58,920 --> 00:29:02,200 Speaker 1: because any sort of drop up off means, hey, we're 486 00:29:02,240 --> 00:29:05,200 Speaker 1: not seeing the massive recovery that we might have been. 487 00:29:05,520 --> 00:29:08,360 Speaker 1: So I have to have that transparency with my key 488 00:29:08,400 --> 00:29:11,440 Speaker 1: suppliers to make sure that I don't have the bullwhip 489 00:29:11,520 --> 00:29:16,080 Speaker 1: effect continuing to amplify. So, now that we have some 490 00:29:16,200 --> 00:29:22,320 Speaker 1: incident into the holiday season, what should consumers do and 491 00:29:22,360 --> 00:29:27,960 Speaker 1: what should suppliers and ants do? The tough one on 492 00:29:27,960 --> 00:29:31,480 Speaker 1: on customers because you know, I think, you know, the 493 00:29:31,560 --> 00:29:34,480 Speaker 1: natural statement from MA would be, you know, please don't 494 00:29:34,480 --> 00:29:37,320 Speaker 1: go out there and buy too early. Don't don't think 495 00:29:37,320 --> 00:29:39,440 Speaker 1: there's a rush. Right, But then you say that and 496 00:29:39,480 --> 00:29:41,000 Speaker 1: then natural thing is people are going to go out 497 00:29:41,000 --> 00:29:43,560 Speaker 1: and rush and buy things early. So, you know, any 498 00:29:43,640 --> 00:29:47,480 Speaker 1: any communication wherein the consumer is a tough message. You know. 499 00:29:47,560 --> 00:29:51,600 Speaker 1: I think the best thing is that the retailers and 500 00:29:51,600 --> 00:29:54,960 Speaker 1: the suppliers that they stay really close to each other, 501 00:29:55,000 --> 00:29:58,320 Speaker 1: that they are communicating regularly to make sure that they 502 00:29:58,360 --> 00:30:00,760 Speaker 1: can have a trusted supply. As long as there's a 503 00:30:00,800 --> 00:30:03,840 Speaker 1: trusted supply and that product is available, then we will 504 00:30:03,880 --> 00:30:07,560 Speaker 1: make sure that we avoid any kind of surge hoarding 505 00:30:07,720 --> 00:30:12,480 Speaker 1: happening from from a customer perspective. So I think for me, 506 00:30:12,560 --> 00:30:15,920 Speaker 1: I put the reliance onto the onto the retailers and 507 00:30:15,960 --> 00:30:20,040 Speaker 1: the suppliers to just work really closely together, to really 508 00:30:20,080 --> 00:30:22,600 Speaker 1: collaborate and make sure they're listening and watching the supply 509 00:30:22,680 --> 00:30:27,560 Speaker 1: signal at a increased level so that they can really 510 00:30:27,640 --> 00:30:32,040 Speaker 1: understand where you know, where the where the demand is going, um, 511 00:30:32,120 --> 00:30:34,600 Speaker 1: and that they respond as quickly as possible to that, 512 00:30:35,080 --> 00:30:37,320 Speaker 1: and then you know, hopefully there'll be enough product and 513 00:30:37,400 --> 00:30:39,960 Speaker 1: we won't have any hoarding and everyone will have the 514 00:30:40,040 --> 00:30:42,120 Speaker 1: right turkey at the right time and the right gifts 515 00:30:42,160 --> 00:30:47,680 Speaker 1: for their family and friends. Jon has been so much fun. Um, 516 00:30:47,720 --> 00:30:51,440 Speaker 1: I really appreciate you taking the time, and I disregard 517 00:30:51,520 --> 00:30:54,480 Speaker 1: what you say and rush from this interview in order 518 00:30:54,520 --> 00:30:56,640 Speaker 1: everything I care in the next fifteen minutes because now 519 00:30:56,680 --> 00:31:01,719 Speaker 1: I'm petrified exactly. But maybe by next Christmas your magic 520 00:31:01,760 --> 00:31:06,400 Speaker 1: will have transformed the marketplace. Really really enjoyed the conversation, Malcolm, 521 00:31:06,440 --> 00:31:08,520 Speaker 1: and you know, just wonderful to spend time with you. 522 00:31:08,600 --> 00:31:13,840 Speaker 1: So thank you for your time. Thank you again to Jonathan. 523 00:31:13,920 --> 00:31:18,520 Speaker 1: Right as I think back to all the conversations I've 524 00:31:18,560 --> 00:31:21,719 Speaker 1: had here on smart Talks. I'm filled with a renewed 525 00:31:21,760 --> 00:31:25,960 Speaker 1: sense of promise, from supply chains and quantum computing to 526 00:31:26,120 --> 00:31:30,640 Speaker 1: five G and empathetic AI. IBM and its partners are 527 00:31:30,720 --> 00:31:33,640 Speaker 1: truly on the cutting edge of technology that will shape 528 00:31:33,640 --> 00:31:36,960 Speaker 1: the way we live and work. Who knows what industry 529 00:31:37,320 --> 00:31:49,240 Speaker 1: they will revolutionize next. Smart Talks with IBM is produced 530 00:31:49,240 --> 00:31:53,480 Speaker 1: by Emily Rostak and Molly Sosha, with Carli Migliori and 531 00:31:53,680 --> 00:32:00,880 Speaker 1: Katherine Gurrodo. Edited by Karen shakerge engineering by Mauran Gonzales 532 00:32:01,160 --> 00:32:07,320 Speaker 1: and Unamrera, mixed and mastered by Jason Gambrel. Music by Granmascope. 533 00:32:08,080 --> 00:32:12,120 Speaker 1: Special thanks also to Kathy Callaghan and Kelly me LaBelle, 534 00:32:12,200 --> 00:32:17,120 Speaker 1: Jacob Briceburg, Heather Fane, Eric Sandler, Maggie Taylor and the 535 00:32:17,160 --> 00:32:23,040 Speaker 1: team's at eight Bar and IBM. Smart Talks with IBM 536 00:32:23,240 --> 00:32:25,880 Speaker 1: is a production of Pushkin Industries and I Heart Radio. 537 00:32:26,280 --> 00:32:32,000 Speaker 1: This is a paid advertisement from IBM. You can find 538 00:32:32,040 --> 00:32:36,400 Speaker 1: more episodes at IBM dot com slash smart Talks. You'll 539 00:32:36,400 --> 00:32:39,240 Speaker 1: find more Pushkin podcasts on the I Heart Radio app, 540 00:32:39,640 --> 00:32:46,880 Speaker 1: Apple Podcasts, or wherever you like to listen. I'm Malcolm Gladwell, 541 00:32:46,880 --> 00:32:47,680 Speaker 1: see you next time.