Managing Supply Chain Volatility in the Height of the Shopping Season
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Hello, hello. Malcolm Gladwell here. I want to tell you about a new series we're launching at Pushkin Industries on the 1936 Olympic Games. Adolf Hitler's Games. Fascism, anti-Semitism, racism, high Olympic ideals, craven self-interest, naked ambition, illusion, delusion, all collide in the long, contentious lead-up to the most controversial Olympics in history. The Germans put on a propaganda show, and America went along with all of it. Why?

This season on Revisionist History, the story of the games behind the games. Listen to this season of Revisionist History wherever you get your podcasts. If you want to hear episodes before they're released to the public, subscribe to Pushkin Plus on Apple Podcasts or at pushkin.fm slash plus.

Hello, hello. This is Smart Talks with IBM, a podcast from Pushkin Industries, iHeartRadio, and IBM about what it means to look at today's most challenging problems in a new way. I'm Malcolm Gladwell. ♪

For our final episode of 2021, I bring you an ode to the holiday shopping season. Well, not just the holiday shopping season. This episode is for all of you who waited six months or longer for your new couch to arrive, and those of you still struggling to buy a car because of the chip shortage. It's all about what's going on with the supply chain. And we're going to look at how the supply chain has evolved since the late 1940s and why we've seen so many hiccups and interruptions over the last two years.

No one knows the current struggles of the supply chain better than Jonathan Wright. Jonathan is the global managing partner for supply chain consulting at IBM. And I think now what we're going to see is strategic supply chains, strategic relationships, which are brought together through technology. And that vertical integration, which once was through ownership, will now be through technology integration.

Together, we'll look at the evolution of our modern-day supply chain and explore how today's demand has created something called a bullwhip effect. Jonathan and I will get into what all of this means and the ways technology can be used to help address current supply chain shortages. Let's dive in. Hi, Jonathan. It's a pleasure to meet you.

It's a big moment for me, Malcolm. It's an honor and it's great to be spending some time chatting to you about supply chain. Yeah. So this we have chosen a topic that is very much of the moment. I am dying for you to explain just what is going on right now. So I feel like you are one of the few people who could actually tell me the big picture.

Well, I hope we can break that down and get into some detail. But it's certainly an exciting time to be working in supply chain. There's so much going on and we've got to unpack some issues to get to the root cause, I think. Yeah. Well, let's start with, you know, three years ago, no one like me ever thought about or worried about the state of the supply chain.

Now people like me do. We hear it all the time. Tell me what has happened in the last, say, two years to drive this disruption.

Well, again, I often say to people, it's like, welcome to 2030. Literally, we've accelerated the kind of thoughts and the innovation around supply chain by 10 years. And the pandemic has driven that for sure. Necessity is the driver of invention or innovation in this case. And

And you can't avoid that COVID period because it really did challenge. It put a shock into the supply chain, a shock on the supply side when Wuhan went into lockdown, and then a shock on the demand side when people started buying fundamentally different things than they had been doing. And I think that's probably the biggest shock to the supply chain since the war, in reality, is the supply chain system that has been disrupted.

Can you be a little more specific on what you mean by disrupted? So you mentioned that people started buying different things and certain parts of the world were no longer as capable of

of producing or moving products as they did before. But can you kind of drill down on all of the sources here? Yeah, for sure. I mean, you know, we were running out of people, we didn't have toilet paper, all of the classic things. And we went into survival mode. And I think, you know, people rolled their sleeves up and were tenacious and they figured out how to solve some of those supply chain issues and keep society running and healthy.

And then we went into resourceful mode where we started to think about, hey, well, we could repurpose some facilities and make more PPE and we could take some fashion retailers and start creating new products. So this system, which has been very stable and just incrementally growing, now we're starting to repurpose things.

And then, of course, we've had a rapid recovery. The world has started moving faster and coming back. And that recovery has put demand onto the supply chain at a time where the supply base is not robust because people are still in flex. And so...

So, you know, really, we're in a situation where we've got this very complex supply chain, which has started to be out of balance. And it's going to take some work to get it rebalanced, really. That was my next question. You know, in doing this series with IBM, one of the things that I've consistently been surprised about is that

things IBM now thinks about that I wouldn't have thought they thought about. Ten years ago, did IBM have people who thought about supply chain management? You know, we have always kind of worked in supply chain. We have our own supply chain. But I think now it is just way more important than ever before. And this is the time where we're seeing convergent technology having a real role to play, whether that's

kind of blockchain, IoT, AI, and Watson, which will help us with really understanding the demand signal and the supply signal. So I think technology has got a real role to play. And we did see that through COVID. We saw those that were invested ahead of the curve coming out faster, being able to respond quicker, being able to understand their supply base quicker and the exposures and the risks that they had.

So I do think this is a bit of a golden age that we're facing now. At what point do we come to conceive of supply chain management and supply chain problems as explicitly technological and data problems, as opposed to what you were talking about earlier, relationships, practical kind of bricks and mortary kind of questions? When does this transition to this notion of, oh, it's just another complicated data problem? Yeah.

When I sort of said welcome to 2030, that was a bit of the point. You know, I think this has been a huge acceleration, a huge jump forward and the interest now of corporations to invest in technology to solve some of these problems. If you go back to the early, early supply chains, we had vertical integration, right, where companies, you know, Ford, Rouge, you know, kind of they had

on site, they made their own steel, they had the whole integrated supply chain. And that's the way that they built trust and collaboration and security into the supply chains.

And I think now what we're going to see is strategic supply chains, strategic relationships, which are brought together through technology. And that vertical integration, which once was through ownership, will now be through technology integration. A couple of questions. This is super interesting. When you said welcome to 2030,

Did you mean that we are doing things because of this crisis in supply chain today that we might not have otherwise done until 2030? 100%. It's exactly what I'm saying. Exactly. Give me an example, a really concrete example. One of my clients was saying it would take them maybe a month to onboard a supplier. Yeah.

If I've got a new supplier, by the time I've worked with them, I've done due diligence, I've figured out their systems and my systems, I've integrated them, maybe it takes a month or longer. It could take even three months.

And through the pandemic, there was this necessity to bring in the supply straight away. And guess what? If you really break down some of those orthodoxies of the past and some of those practices and you ask why, why, why, you can do it in three days straight away. And you can figure out with some technology and with some new processes, you can do that in three days because of that necessity is driving that innovation in the process.

On the demand side, you know, basically supply chains have always grown up thinking about what happened last yesterday, last week, last month, last year will happen next month, next week. Right. And and now what we see is that's not not the case. The last two years are not a good proxy for what's going to happen in the next two years.

We've got to really start thinking about what are the drivers that impact demand. The drivers could be people working from home or not. Have I got another spike happening? Are schools open? Where are we? Maybe even hospitalizations in people movement. Whether all of these different aspects come into play to really understand at a zip code level, at a SKU level, at a product level, what is the demand?

And so now we can use AI and analyze the data, refine the data that we have from new sources, not just from within my four walls of what did I sell yesterday, last month, last quarter. I can now start thinking about all the external data. I can look at social media. I can look at, you know, kind of data from the state and from local authorities and use that.

to actually inform what's happening on the ground and what people's behaviors are and what will that mean for demand. Those kinds of much more sophisticated forecasting models

three years ago, we could have built them, but we didn't see the need. Correct. And what you're saying is all of a sudden we now see the need and so we're building. The capability was there, but not the motivation. Is that what you're saying? Yeah, absolutely. When you invest in technology, you want to make sure that there's a return on that investment, right? That you can actually drive real value. And pre-pandemic, from a forecasting perspective,

It was less important. Let's go back to two years ago as a, for example, three years ago, what have you. How many people would have had a deep map of their supply chain back then? Very few. 90% of the Fortune, the top 200, did not have the picture and the map that they needed.

And what percentage now have the picture of the map they need? It's a good question. I don't know. Certainly all of the clients that I work with, there's a top priority for them, particularly now as many of them have got exposures to semiconductors and the like. So they're now having to go at much, much more detailed analysis of their supply chain. So I think they've really had to kind of up the game. Your phone must have been...

Ringing off the hook for the last two years. Am I right? I mean, how crazy has your life been? I mean, I'm fortunate that I work in supply chain and this has absolutely the most exciting time to work in supply chain. And

Whether it's supporting clients with vaccine distribution and working through the issues of transparency and making sure that we understand how to do that through to just supply issues and helping clients navigate this volatile period. Certainly one of the positives that I think will come out of this is more interest in supply chain and therefore us being able to attract new talent.

Because one thing that we have got to do to solve these complex issues is have diverse talent. And I personally believe that when we bring in more diverse talent, cognitive, ethnic, gender diversity, we're much better able to solve for the world's most complex issues. And we'll see a much richer ability to solve for the future. How long does it take?

to build one of these maps. Let's say I come to you, I'm Fortune 500, for one reason or another though, I have simply neglected. I have the most kind of plain vanilla supply chain map

And I'm freaking out and I call you up and I say, I want to go gold standard as fast as possible. I'm a company with sales of, I don't know, $50 billion. Okay. Let's assume complex international, you know, like not an easy case. Yeah.

Tell me how long, tell me how many people would work on this problem. Tell me how you would start to solve the problem. - It's actually, it's a bit of a trick question, right? Because it's a lot easier than you think.

And the reason it's a lot easier than you think is because many of the suppliers out there are already supplying other companies who already have mapped their supply chain. So we work with platform companies that are able to accelerate this journey towards critical risk modeling.

We map the tier one suppliers. We prioritize the supply base. And in weeks, yes, weeks, we're able to get onboarded companies a view, an 80-20 view of their deep supply chain.

That's 80% of their key suppliers in their supply chain. And people are willing to share that kind of data? Yes, absolutely. That's the business model for these platform providers. You know, we partner with them. They make sure that we have the visibility. And that visibility is permissioned and restricted.

And we use that in our own supply chain. And it's an incredibly powerful tool for getting into the deep supply chain. And then over time, we can continue to build out the richness of that data and the modeling. And then you have to start looking at how am I organized so I can use that data?

and use that much more effectively. So what are my internal processes? And that's actually where potentially the harder piece comes, which is reorganizing and getting people to use data in a different way.

I have a view that we should all have a virtual assistant by the side of our desks. In the same way that you have a virtual assistant at home, we should all have one in the supply chain. We can interact with natural language and we can ask Watson, hey, tell me what happens if there's an issue at Malaysia airport? What are my suppliers are going to be affected?

Guess what? We internally already have that for our own supply chain system. But my vision is that every supply chain professional will have that virtual assistant and that they can access the data. But that requires a different way of working. But if we get that right, we can have a cool, cool environment. We can attract more talent because instead of doing mundane, dull tasks, transactional tasks, they can actually be doing value-added tasks. Yeah, yeah. Walk me through...

You mentioned this little bit about what you do with the information. So I'm the same company with this large complex business. You've now given me this much more detailed, accurate map of what my supply chain looks like. And we see a problem. One of my suppliers, supplier, supplier, deep somewhere on the other side of the world, who this is one of my critical components. And I see, uh-oh.

It's supposed to come next week. I don't think it's going to come for two months. Yeah. What do I do with that information? How do I react to it? Well, back in the year 2000, Nokia and Ericsson, if you remember, they were market leaders in mobile phones before the world changed. They had two very different strategies here around supplier management.

And actually, Ericsson failed big time when there was a fire in Albuquerque in New Mexico at a Philips chip manufacturing point. And so this was all to do with internal processes, how you handle the information. The information came through that there was a fire. A lot of the chips have got soaked and saturated and smoke damaged.

And a mid-manager at Ericsson had kind of got in contact with Philips and had taken a risk assessment that the place was going to be up and running quite soon and there was no major action required, no major disruption. Nokia, on the other hand...

had much more collaborative approach. And they said, no, this could be a real issue here. I don't trust that information. I'm not going to be too complacent. And literally flew over, went down, did the risk assessment, said, no, this is not going to be up and running in any near term.

And went and triggered some other contracts they had and basically soaked up all of the supply of those chips. Long story short, Ericsson were unable to supply the market and ultimately failed and the company were no longer making money.

mobile phones and Nokia went from strength to strength until another technology evolution took place. But the processes and the strategies around how to handle the supply signal were handled very differently. So both of them had the same quantitative information. One of them, though, added a qualitative layer on top of that where they went in and made an assessment of whether the supplier was

was being trustworthy in their assessment of how dangerous things were. Correct. And this is where the organization design and the skills and the capability will always be super important. And I think...

Yes, we've got to make sure that we have the right – the number of suppliers and we've got kind of the balance of de-risking our suppliers by having a number of contracts in place and we haven't got sort of an exposure of one supplier. But then –

have I got the right skills and capability and a culture that listens to risk and risk management and is absorbing that versus a culture of maybe complacency and trust, which could lead to some failure. I think you do get some aha moments. I do think, you know, particularly when you start to look into,

As you say, the deep supply chain map, you start to realize where those bottlenecks are. And they're not obvious. They're not obvious because when you start to model out and you start to see where those flows are, you might say, hey, I've got I've got too much risk here because of one location. So I think it's when you do that modeling of the supply chain.

both in terms of physical flows, network modeling, and the deep network, that you start to see those vulnerabilities. And nobody, the way that organizations are set up, you tend to have people focusing on one category or one product line. You don't necessarily have people looking all the way across. What is the hardest problem to solve?

You said one part of it you already said. It can be surprisingly easy if your suppliers have maps themselves. What's the hard part? I think that there's two hardest parts. One is the cleanliness of data. It's very...

It's very typical in large organizations for the data to be dirty and like oil, right? If you get dirty oil, it's a problem, right? If you get nice refined oil, it's valuable. I think the same for data. When you refine it and you clean it and you use it in the right way, it's very valuable. But if it's dirty, then it's a problem. I have a client, a retailer couldn't understand why they couldn't

They have on-shelf availability. They couldn't replenish the shelf quick enough. And the reason was that in the system, the shelf was recorded as 10 centimeters, not a meter. So when I send one product, I fill the shelf up.

I need, because the system thinks that the shelf is this big. Actually, the shelf is this big. So you- Wait, why? That's fascinating. How long had that error existed in the- It had been going on for a while. It had been going on for a while. And then they have sort of manual workarounds. But if you lose that tribal knowledge, you use that manual workaround, then you start to realize what's actually happening. And then you find the systemic solution. How long into COVID-19

before you realized that your world was going to explode? Well, actually, pretty early on, some of the leaders were coming to us saying, we need help. It was one consumer products company. I remember literally in that March, April time, we had a project running where we were doing

this data-driven demand forecasting. And we created a dashboard for them. Within a month, they could see all of their products, all of their customers, retailers, at a zip code level. And we had a map of where we thought their demand would go. In Minneapolis, they were not going to be a significant drop-off of buying single chocolates on the way to work as a snack because there was nobody going to work.

Instead, their family packs were going to go up by 300% because people would be gorging on them at home. So that signal was super important for that consumer products company, the food company, to then repurpose their manufacturing lines to move from singles to family packs.

And if they could get that signal ahead of the retailers giving them that signal, they could get the ground truth, then they could proactively sort out. That was happening in April time. But it was new technology and new analysis. And within a month, they had that new analysis. It was an incredible piece of work.

Wow. So within a month, they had reconfigured their manufacturing lines to do more family packs than singles? Yeah, absolutely. And within a month, they had the data and the facts behind it to help them get the balance right. To stay with that example, that over the last, let's just say six months, they would be monitoring this and gradually readjusting their mix.

As people start going back to work. Well, and then we come back to this problem, which is the bullwhip effect, right? And the bullwhip effect is a real problem that we have at the moment. What is the bullwhip effect? The bullwhip effect says that I can see a demand signal for maybe...

extra five units. So I forecast I'm going to sell an extra five units. But my distributor says, oh, they're going to sell an extra five units, but they typically get it wrong. So I'm going to say an extra 10 units. So they put that back onto their supply and say, hey, you know, this company's now gone, it's gone extra 10 units. They say, oh, we'll make that 20. And then their supplier says, oh, they typically, you know, I don't want to go short here. So we'll make it 50. So before you know it, my five units of demand further down the supply chain is 50 units.

Now, this happens where you have a lack of trust in the demand signal. Because if you don't really trust that demand signal, you always inflate it a little bit. And so what's happening at the moment, we've got problems on both sides, as I said. That demand signal is hard to understand because we don't really know what the new sort of behavior is. And the supply signal we know is disrupted because we've got this repurposing going on and rebalancing in the supply chain.

So what happens now is I'm going, hey, I'm going to order 10, not five. I'm going to order 10 because I'm worried about my supply. In fact, I might order the whole season's worth in one go. I might, instead of having weekly orders, I might put monthly orders in or quarterly order. And so then you get this bumper bullwhip effect where, oh, they put in a whole quarter. Wow, demand's picking up. I'm going to double that. I'm

I'm worried about this amplitude effect that's happening as people start to say, I'm going to put bigger supply points in because I don't trust my supply base. And people say, you don't really know your demand. So actually, we're going to continue to inflate. And so that has problems, obviously, because there's going to be some winners and some losers with that scenario. So it could be the case.

I'm in a competitive marketplace. I might trust my own data, but I don't trust that you trust your data, right? So I behave strategically and say, well, I don't know what Jonathan's doing.

He could be, he could be hoarding this thing. So even though I only need five units, I'm going to order 10. Yeah, exactly. How do you restore trust systemically then? Yeah, you, you have to build trust, I think through technology, because you

You have to find those suppliers and those strategic supply points, and you have to start sharing data and actually proving that that five is real, right? And that you shouldn't be inflating it. And I also need to know that you, Malcolm, as my supplier, right, that you have got the capacity that I need.

Because if I'm worried that you might allocate your capacity to somewhere else, then I'm going to double my demand onto you so that you give me some. If I give you, if I order 30, maybe I'll get the five that I wanted. So you start to worry a little bit about. Classic hoarding problem, really, because I'm not sure I fully understand. So I can see how on an individual company level,

technology can allow me to create a far more accurate assessment of what my true demand for something is. But everyone has to have trust in their own estimates in order for the system to work again and for hoarding to be prevented. So how do you go from individual actor trust to everyone in the marketplace trusting everyone else's estimates? I...

I think you have to do it piece by piece. I think you have to get your own demand signal clear. You have to build the relationships with your suppliers and make sure you build trust with them and you put technology in place to share information with them. And over time, you have to just start working through that and

hopefully we will start to see the supply base rebalancing and settling. The vibrations calming down a bit, the bullwhip effect calming down a bit, and we'll have a more secure supply of product. And then we'll be able to trust the demand signal. The holiday season's a big effect at the moment, right? Some of the analysis that we've seen says that

that shoppers are more likely, as you'd expect, to start shopping earlier than they have in the past. And one in four of global consumers have already started shopping. So you're starting to see this early consumer demand picking up. Now, at the same time, what we're seeing in analysis is that they're unlikely to spend more this year than they did last year.

So that's interesting, or only marginally more. So they're shopping earlier, but they're not going to shop more. So one of the interesting things here is, again, is understanding the behavior. Does that mean I pick up that signal earlier that demand is increasing, that I've got a big economic bounce, or does it mean that people are just buying earlier because they're worried about the supply point? The difference between those two forecasts is huge. One is bumper crop, the other is same crop,

But with very, very different demands on your manufacturing distribution. Correct, correct. And that's where this more sophisticated driver-based analysis of demand becomes really important. And then building that

tight relationship with my supply base. So I'm keeping them up to speed as to what we're seeing, because any sort of drop off means, hey, we're not seeing the massive recovery that we might have been seeing. So I have to have that transparency with my key suppliers to make sure that I don't have the bullwhip effect continuing to amplify. Yeah, yeah. So now that we have some insight into the holiday season, what should

do and what should suppliers and manufacturers do? A tough one on customers because I think the natural statement from me would be, please don't go out there and buy too early. Don't think there's a rush, right? But then you say that and then the natural thing is people are going to go out and rush and buy things early. So any communication around the consumer is a tough message. I think the

The best thing is that the retailers and the suppliers, that they stay really close to each other, that they are communicating regularly to make sure that they can have a trusted supply. As long as there's a trusted supply and that product is available, then we will make sure that we avoid any kind of surge problems.

hoarding happening from a customer perspective. So I think for me, I put the reliance onto the retailers and the suppliers to just work really closely together, to really collaborate, to make sure they're listening and watching the supply signal at a increased level so that they can really understand what's

you know, where, you know, where the, where the demand is going and that they respond as quickly as possible to that. And then, you know, hopefully there'll be enough product and we won't have any hoarding and everyone will have the right turkey at the right time and the right gifts for their family and friends.

Jonathan, it's been so much fun. I really appreciate you taking the time. And I'm going to disregard what you say and rush from this interview and order everything I can in the next 15 minutes because now I'm petrified. Exactly. But maybe by next Christmas, your magic will have transformed the marketplace. No, really, really enjoyed the conversation, Malcolm. And, you know, just wonderful to spend time with you. So thank you for your time. Thank you again to Jonathan Wright.

As I think back to all the conversations I've had here on Smart Talks, I'm filled with a renewed sense of promise. From supply chains and quantum computing to 5G and empathetic AI, IBM and its partners are truly on the cutting edge of technology that will shape the way we live and work. Who knows what industry they will revolutionize next? Smart Talks with IBM is produced by Emily Rostak and Molly Socia.

with Carly Migliore and Catherine Giraudoux. Edited by Karen Shikurji. Engineering by Martin Gonzalez and Una Marrera. Mixed and mastered by Jason Gembrell. Music by Gramascope. Special thanks also to Kathy Callahan, Andy Kelly, Mia LaBelle, Jacob Breisberg, Heather Fane, Eric Sandler, Maggie Taylor, and the teams at 8 Bar and IBM.

Smart Talks with IBM is a production of Pushkin Industries and iHeartRadio. This is a paid advertisement from IBM. You can find more episodes at ibm.com slash smart talks. You'll find more Pushkin podcasts on the iHeartRadio app, Apple podcasts, or wherever you like to listen. I'm Malcolm Gladwell. See you next time.

Hello, hello. Malcolm Gladwell here. I want to tell you about a new series we're launching at Pushkin Industries on the 1936 Olympic Games. Adolf Hitler's Games. Fascism, anti-Semitism, racism, high Olympic ideals, craven self-interest, naked ambition, illusion, delusion, all collide in the long, contentious lead-up to the most controversial Olympics in history. The Germans put on a propaganda show, and America went along with all of it.

This season on Revisionist History, the story of the games behind the games. Listen to this season of Revisionist History wherever you get your podcasts. If you want to hear episodes before they're released to the public, subscribe to Pushkin Plus on Apple Podcasts or at pushkin.fm slash plus.