Speaker 1: Hello, Hello. This is Smart Talks with IBM, a podcast
Speaker 1: from Pushkin Industries, our our radio and IBM about what
Speaker 1: it means to look at today's most challenging problems in
Speaker 1: a new way. I'm Malcolm Gladwell. For our final episode,
Speaker 1: I bring you an ode to the holiday shopping season.
Speaker 1: Well not just a holiday shopping season. This episode is
Speaker 1: for all of you who waited six months or longer
Speaker 1: for your new couch to arrive, and those of you
Speaker 1: still struggling to buy a car because of the chip shortage.
Speaker 1: It's all about what's going on with the supply chain,
Speaker 1: and we're gonna look at how the supply chain has
Speaker 1: evolved since the late nineteen and why we've seen so
Speaker 1: many hiccups and interruptions over the last two years. No
Speaker 1: one knows the current struggles of the supply chain better
Speaker 1: than Jonathan Wright. Jonathan is the global Managing Partner for
Speaker 1: Supply Chain Consulting at IBM, and I think now what
Speaker 1: we're going to see is uh strategic supply chains, strategic
Speaker 1: relationships which are brought together through technology, and that that
Speaker 1: vertical integration which once was through ownership, will now be
Speaker 1: through technology integration. Together, we'll look at the evolution of
Speaker 1: our modern day supply chain and explore how today's demand
Speaker 1: has created something called a bull whip effect. Jonathan and
Speaker 1: I will get into what all of this means and
Speaker 1: the ways technology can be used to help address current
Speaker 1: supply chain shortages. Let's dive in. Hi, Jonathan, it's a
Speaker 1: pleasure to meet you. It's a big moment for me, Malcolm.
Speaker 1: It's is an honor and it's great to be spending
Speaker 1: some time chatting to you about supply chain. Yeah, so
Speaker 1: this we have chosen a topic that is very much
Speaker 1: of the moment. I am dying for you to explain
Speaker 1: just what is going on right now. So I'm I
Speaker 1: feel like you're one of the few people who can
Speaker 1: actually tell me the big picture. I hope we can.
Speaker 1: I hope we can break that down and get into
Speaker 1: some detail. But it's certainly an exciting time to be
Speaker 1: working in supply chain. Is so much going on, and
Speaker 1: we've got to unpack some some issues to to get
Speaker 1: to the root. Cause I think, yeah, well, let's start
Speaker 1: with you know, three years ago, no one like me
Speaker 1: ever thought about a word about the state of the
Speaker 1: supply chain. Um, now people like me, do we hear
Speaker 1: it all the time. Tell me what has happened in
Speaker 1: the last say two years two to drive this disruption? Well, again,
Speaker 1: I often say to people, it's like welcome to literally
Speaker 1: we we've accelerated UM the kind of thoughts and the
Speaker 1: innovation around supply chain by ten years. And the pandemic
Speaker 1: has driven that. For sure, UM necessity is the driver
Speaker 1: of invention or innovation in this case. And and you
Speaker 1: can't avoid that COVID period because it really did challenge
Speaker 1: It put a shock into the supply chain, a shock
Speaker 1: on the supply side UM when Wuhan went into lockdown,
Speaker 1: and then a shock on the demand side when people
Speaker 1: started buying fundamentally different things than they had been doing.
Speaker 1: And and I think you know that's probably the biggest
Speaker 1: shock UM to the supply chaine since the war. In reality,
Speaker 1: is a supply chain system, right that has been disrupted.
Speaker 1: Can you be a little more specific on what you
Speaker 1: mean by disrupted? So you mentioned people started buying different
Speaker 1: things and certain parts of the world were no longer
Speaker 1: as capable of producing or moving products as did before.
Speaker 1: But can you could have drilled down on the on
Speaker 1: all of the sources here, Yeah, for sure, I mean,
Speaker 1: you know, we were running out of of people, We
Speaker 1: didn't have of toilet paper, all of the classic things
Speaker 1: and um, and we went into survival mode and and
Speaker 1: I think, you know, people roll their sleeves up, and
Speaker 1: we're tenacious, and they figured out how to solve some
Speaker 1: of those supply chain issues and keep society running and healthy.
Speaker 1: And then we went into resourceful mode, where we started
Speaker 1: to think about, hey, well we could repurpose some facilities
Speaker 1: and make more ppe, and we could take some fashion
Speaker 1: retailers and start creating new products. So this system, which
Speaker 1: has been very stable and just incrementally growing, now we're
Speaker 1: starting to repurpose things. And then of course we've had
Speaker 1: a rapid recovery. The world has started moving faster and
Speaker 1: coming back, and that recovery has put demand onto the
Speaker 1: supply chain at a time where the supply base is
Speaker 1: not robust because people are still in flex and so
Speaker 1: you know, really we're in a in a situation where
Speaker 1: we've got this very complex supply chain which is started
Speaker 1: to be out of balance, and it's going to take
Speaker 1: some work to get it rebalanced. Really, I was playing next,
Speaker 1: you know, in doing this series with IBM. One of
Speaker 1: the things that consistently been surprised about. Is the things
Speaker 1: IBM now thinks about that I wouldn't have thought they
Speaker 1: thought about ten years ago. Did IBM have people who
Speaker 1: thought about supply chain management? You know, we have or
Speaker 1: always kind of worked in supply chain, We have our
Speaker 1: own supply chain, but I think now it is just
Speaker 1: way more important than ever before. And this is at
Speaker 1: the time where we're seeing convergent technology having a real
Speaker 1: role to play, whether that's kind of blockchain, IoT AI
Speaker 1: and Watson, which will help us with really understanding the
Speaker 1: demand signal and the supply signal. So I think technology
Speaker 1: has got a real role to play, and we did
Speaker 1: see that through COVID. We saw those that we had
Speaker 1: invested ahead of the curve coming out faster, being able
Speaker 1: to respond quicker, being able to understand the supply base quicker,
Speaker 1: and the and the exposures and the risk that they had.
Speaker 1: UM So I think, you know, this is a bit
Speaker 1: of a golden age that we're facing now. At what
Speaker 1: point do we come to conceive of supply chain management
Speaker 1: and splashing problems as as explicitly technological and data problems
Speaker 1: as opposed to what you're talking about earlier relationships, you know,
Speaker 1: practical kind of bricks and mortary kind of questions. When
Speaker 1: does this transition to this notion of it, Oh, it's
Speaker 1: just another complicated data problem. And I sort of said,
Speaker 1: welcome to twenty that was a bit of the point,
Speaker 1: you know, I think this has been a huge acceleration,
Speaker 1: a huge jump forward, and the the interest now of
Speaker 1: corporations to invest in technology to solve some of these problems.
Speaker 1: If you go back to the early early supply chains,
Speaker 1: we had vertical integration right where companies forward rouge, you know,
Speaker 1: kind of they had on site, they made their own steel,
Speaker 1: they had the whole integrated supply chain, and that's the
Speaker 1: way that they built trust and collaborate action and security
Speaker 1: into the supply chains. And I think now what we're
Speaker 1: going to see is uh strategic supply chains, strategic relationships
Speaker 1: which are brought together through technology, and that that vertical integration,
Speaker 1: which once was through ownership, will now be through technology integration.
Speaker 1: A couple of questions, super interesting when you said welcome
Speaker 1: to did you mean that we are doing things because
Speaker 1: of this crisis and especially today that we might not
Speaker 1: have otherwise done until is exactly what I say, exactly
Speaker 1: give me, give me an example, a really concrete example.
Speaker 1: One of my one of my clients was I saying
Speaker 1: it would take them maybe a month to onboard a supplier.
Speaker 1: But if you if I got a new supplier, by
Speaker 1: time I've worked with them, I've done due diligence, I've
Speaker 1: figured out their systems and my systems have integrated them.
Speaker 1: Maybe it takes a month or longer, could take even
Speaker 1: three months. And through the pandemic, um there was this
Speaker 1: necessity to bring in the supply straight away. And guess
Speaker 1: what if you really break down some of those orthodoxes
Speaker 1: of the past and there's some of those practices, and
Speaker 1: you ask why, why why you can do it in
Speaker 1: three days straight away? And you can figure out with
Speaker 1: some technology and with some new processes, you can do
Speaker 1: that in three days. Because of that necessity is driving
Speaker 1: that innovation in the process. On the demand side. You know, basically,
Speaker 1: supply chains have always grown up thinking about what happened
Speaker 1: last yesterday, last week, last month, last year, will happen
Speaker 1: next month, next week? Right? And and now what we
Speaker 1: see is, um, that's not not the case. You know,
Speaker 1: the last two years are not a good proxy for
Speaker 1: what's going to happen in the next two years, We've
Speaker 1: got to really start thinking about what are the drivers
Speaker 1: that impact demand. The drivers could be a people working
Speaker 1: from home or not. You know, have I got another
Speaker 1: spike happening at school? Is open? Are? You know? Where
Speaker 1: are we maybe even hospitalizations in people movement, Whether all
Speaker 1: of these different aspects come into play to really understand
Speaker 1: at a zip code level, at a skew level, at
Speaker 1: a product level, you know, what is the demand and
Speaker 1: and so now we can use AI and analyze the data,
Speaker 1: refine the data that we have from new sources, not
Speaker 1: just from within my four walls of what did I
Speaker 1: sell yesterday, last month, last last quarter. I can now
Speaker 1: start thinking about all the external data. I can look
Speaker 1: at social media, I can look at you know, kind
Speaker 1: of data from the state and from local authorities and
Speaker 1: use that to actually inform what's happening on the ground
Speaker 1: and what people's behaviors are and what will that mean
Speaker 1: for demand. Those kinds of much more sophisticated forecasting models.
Speaker 1: Three years ago, we could have built them, but we
Speaker 1: didn't see the need. Correct, And what you're saying is
Speaker 1: all of a sudden, we now see the need and
Speaker 1: so we're building. The capability was there but not but
Speaker 1: not a motivation? Is that what you're saying, Absolutely, when
Speaker 1: you invest in technology, you want to make sure that
Speaker 1: there's a return on that investment, right, that you can
Speaker 1: actually drive real value and pre pandemic. From a forecasting perspective,
Speaker 1: it was less less important. Let's go back to two
Speaker 1: years ago as a as A for example, was three
Speaker 1: years ago? What have you? How many people would have
Speaker 1: had a deep map of their supply chain back then?
Speaker 1: Very few of the fortune the top two did not
Speaker 1: have the picture and the map that they needed. And
Speaker 1: what percentage now and have the picture of the map
Speaker 1: I needed? I say, it's a good question. I don't
Speaker 1: know certainly. All of the clients that I work with,
Speaker 1: there's a top priority for them, particularly now as many
Speaker 1: of them have got exposures to semiconductors and the like,
Speaker 1: so they're now having to go at much much more
Speaker 1: detailed analysis of their supply chain. So I think they've
Speaker 1: really had to, you know, kind of up the game. Ye,
Speaker 1: your phone must have been bringing off the hook for
Speaker 1: the last two years. How crazy has your life been?
Speaker 1: I mean, I'm fortunate that I work in supply chain
Speaker 1: and This has absolutely the most exciting time to work
Speaker 1: in supply chain, and whether it's you know, supporting clients
Speaker 1: with vaccine distribution and working through the issues of transparency
Speaker 1: and making sure that we understand how how to do
Speaker 1: that through too just supply issues and um and and
Speaker 1: helping clients navigate this volatile PERIODI is certainly one of
Speaker 1: the one of the positives that I think will come
Speaker 1: out of this is is more interesting supply chain and
Speaker 1: therefore us being able to attract new talent because one
Speaker 1: thing that we have got to do to solve these
Speaker 1: complex issues is have diverse talent. And I I personally
Speaker 1: believe that and we bring in more diverse talent cognitive, ethnic,
Speaker 1: gender diversity, we're much better able to solve for the
Speaker 1: world's most complex issues, and we'll see a much richer
Speaker 1: ability to solve for the future. How long does it
Speaker 1: take to build one of these maps. Let's say I
Speaker 1: come to you unfortunate for one reason another though I
Speaker 1: have simply neglected, I have the the most kind of
Speaker 1: plain vanilla supply chain map, and I'm freaking out, and
Speaker 1: I call you up and I say I want to
Speaker 1: go gold standard as fast as possible. I'm a company
Speaker 1: with sales of I don't know, fifty billion dollars. Okay,
Speaker 1: let's assume complex international, you know, like not an easy kisse. Um,
Speaker 1: how tell me how long? Tell me how many people
Speaker 1: would work on this problem? Tell me tell me how
Speaker 1: you would start? Yeah, it's actually, um, it's a bit
Speaker 1: of a trick question, right, because it's a lot easier
Speaker 1: than you think. And the reason it's a lot easier
Speaker 1: than you think is because many of the suppliers out
Speaker 1: there are already supplying other companies who already have mapped
Speaker 1: their supply chain. So we work with platform companies that
Speaker 1: are able to accelerate this journey towards critical risk modeling.
Speaker 1: We map the tier one suppliers, we prioritize the supply base,
Speaker 1: and in weeks, yes, weeks, we're able to get onboarded
Speaker 1: companies a view, a view of their deep supply chain,
Speaker 1: that's of their key suppliers in their supply chain. People
Speaker 1: are willing to share that kind of data. Yes, absolutely,
Speaker 1: that's the business model for these platform providers. You know,
Speaker 1: we partner with them. They make sure that we have
Speaker 1: the visibility, and that visibility is permissioned and restricted. Um,
Speaker 1: we use that in our own supply chain, and it's
Speaker 1: an incredibly powerful tool for getting into the deep supply chain.
Speaker 1: And then over time we can continue to build out
Speaker 1: and the richness of that data and the modeling, and
Speaker 1: then you have to start looking at how am I
Speaker 1: organized so I can use that data um and use
Speaker 1: that much more effectively. So what are my internal processes?
Speaker 1: And that's actually where the potentially the harder piece comes,
Speaker 1: which is reorganizing and getting people to to use data
Speaker 1: in a different way. I have a view that we
Speaker 1: should all have a virtual assistant by the side of
Speaker 1: our desks. In the same way that you you have
Speaker 1: a virtual as system at home, we should all have
Speaker 1: one in the supply chain. We can interact with natural
Speaker 1: language and we can ask what's and hey, you know,
Speaker 1: tell me what happens if if there's an issue at
Speaker 1: Malaysia Airport, what are my suppliers are going to be affected?
Speaker 1: Guess what? We internally already have that for our own
Speaker 1: supply chain system. But my vision is that every supply
Speaker 1: chain professional will have that virtual assistant and that they
Speaker 1: can access the data. But that acquires a different way
Speaker 1: of working. But if we get that right to me,
Speaker 1: he can have a cool, cool environment. We can attract
Speaker 1: more talent because instead of doing mundane, dull tasks transactional task,
Speaker 1: they can actually be doing value adding tasks. Do you
Speaker 1: walk me through this? You mentioned this little bit about
Speaker 1: what you do with the information. So I'm I'm the
Speaker 1: same company with this large, complex business. You've not given
Speaker 1: me this much more detailed, accurate map of what my
Speaker 1: supply him looks like. And we see a problem one
Speaker 1: of my suppliers, suppliers, supplier deep somewhere on the other
Speaker 1: side of the world. Who this is one of my
Speaker 1: critical components. And I see, Oh, it's supposed to come
Speaker 1: next week. I don't think it's going to come for
Speaker 1: two months. What what do I do with that information?
Speaker 1: How do I react to it? Well, that back in
Speaker 1: the year two thousand not here and Ericsson, if you remember,
Speaker 1: they were market leaders in mobile phones UM before before
Speaker 1: the world changed. They had two two very different strategies
Speaker 1: here around supplier management and UM. And actually Ericsson failed
Speaker 1: big time when there was a fire in Albuquerque, in
Speaker 1: New Mexico at a Philip's chip manufacturing point. And so
Speaker 1: this was all to do with internal processes. How you
Speaker 1: handle the information. The information came through that there was
Speaker 1: a fire, a lot of the chips had got you know,
Speaker 1: soaked and saturated and smoked damage, and UM and a
Speaker 1: mid manager at Ericson had had kind of got in
Speaker 1: contact with Phillips and had taken a risk assessment that
Speaker 1: the place was going to be up and running quite
Speaker 1: soon and there was no major action required, no major disruption. Nokia,
Speaker 1: on the other hand, had much more collaborative approach and
Speaker 1: they said, no, this, this could be a real issue here.
Speaker 1: I don't trust that information. I'm not going to be
Speaker 1: too complacent and and literally flew over, went down, did
Speaker 1: the risk assessment, said no, this, this is not going
Speaker 1: to be up and running in any near term. Um
Speaker 1: and went and triggered some other contracts they had and
Speaker 1: basically soaked up all of the supply of those chips.
Speaker 1: Long story short, Ericsson were unable to supply the market
Speaker 1: and ultimately failed and the company who were no longer
Speaker 1: making mobile phones and Nokia went from strength to strength
Speaker 1: until another technology evolution took place. But the processes and
Speaker 1: the strategies around how to handle the supply signal will
Speaker 1: handled very differently, and so so you had both of
Speaker 1: them had the same quantitative information. One of them though
Speaker 1: added a qualitative layer on top of that where they
Speaker 1: went and made an assessment of whether the the supplier
Speaker 1: was was being trustworthy in their assessment of how to
Speaker 1: interesting to work correct. And this is this is where
Speaker 1: the organization design and the skills and the capability will
Speaker 1: always be super important. And I think, yes, we've got
Speaker 1: to make sure that we have the right um that
Speaker 1: the number of suppliers and we've got kind of the
Speaker 1: balance of de risking a suppliers by having a number
Speaker 1: of contracts in place, and we haven't got sort of
Speaker 1: an exposure of one supplier. But then have I got
Speaker 1: the right skills and capability and a culture that that
Speaker 1: listens to risk and risk management and and is is
Speaker 1: absorbing that versus a culture of maybe complacency and trust
Speaker 1: which could lead to some failure. M hmm. I think,
Speaker 1: I think, I think you do get some are hard moments.
Speaker 1: I do think, you know, particularly when you start to
Speaker 1: look into um as you say, the deep supply chain map,
Speaker 1: you start to realize where those bottom necks are and
Speaker 1: they're not obvious. They're not obvious because when you start
Speaker 1: to model out and you start to see where those
Speaker 1: flows are. You might say, hey, I've got I've got
Speaker 1: too much risk here because of your one one location.
Speaker 1: So I think it's when you do that modeling of
Speaker 1: the supply chain um both in terms of physical flows,
Speaker 1: network modeling and the deep network, that you you start
Speaker 1: to see those vulnerabilities and nobody. The way that organizations
Speaker 1: are set up, you you tend to have people focusing
Speaker 1: on one category or one product line. You don't necessarily
Speaker 1: have people looking all the way across. What is the
Speaker 1: hardest problem to solve on this? In these kinds of
Speaker 1: you said one part of it you already said, well,
Speaker 1: it can be surprisingly easy if your suppliers have maps themselves.
Speaker 1: What's the hard part? I think that there's there's to
Speaker 1: the two hardest parts. M One is is the cleanliness
Speaker 1: of data. Right, It's it's very it's very typical in
Speaker 1: large organizations for the data to be dirty. And like oil, right,
Speaker 1: if you've get dirty oil, it's a problem. Right, if
Speaker 1: you get nice refined oil, it's valuable. I think the
Speaker 1: same for data. When you refine it and you clean
Speaker 1: it and you use it in the right way, it's
Speaker 1: very valuable. But if it's dirty UM. Then it's a
Speaker 1: problem I have. You know, a client, a retailer couldn't
Speaker 1: understand why they couldn't UM have on shelf availability. They
Speaker 1: couldn't they couldn't replenish the shelf quick enough. And the
Speaker 1: reason was that in the system it was recorded as
Speaker 1: the shelf was recorded as ten centimeters not not a meter.
Speaker 1: So who you know, when I send one product, I
Speaker 1: fill the shelf up I need because the system thinks
Speaker 1: that the shelf is this big. Actually the shelf is
Speaker 1: this big. So you you why how long had that
Speaker 1: error existed in? There have been going on for a
Speaker 1: while for a while, and and then they have sort
Speaker 1: of manual workarounds. But but you know, if you lose
Speaker 1: that tribal knowledge, you use that manual work around, then
Speaker 1: you start to realize, you know, what's actually happening, and
Speaker 1: then to find the systemic solution. How how long into
Speaker 1: COVID before you realized that your world was going to explode? Well, actually,
Speaker 1: pretty early on some of the leaders were coming to
Speaker 1: us saying we need help. It was one consumer products company.
Speaker 1: I remember literally in in that March April time, we
Speaker 1: had a project running where we were doing this data
Speaker 1: driven demand forecasting, and we created a dashboard for them.
Speaker 1: Within a month, they could see all of their products,
Speaker 1: all of their customers retailers at a zip code level,
Speaker 1: and we had a map of where we thought the
Speaker 1: demand would go. In Minneapolis. They were not going to
Speaker 1: be a significant drop off of buying single chocolates on
Speaker 1: the way to work as a snack because there's nobody
Speaker 1: going to work. Instead, they would be their family packs
Speaker 1: were going to go up by because people would be
Speaker 1: would be gorging on them at home. So that signal
Speaker 1: was super important for that consumer products company, um of
Speaker 1: Food Food Company to to then repurpose their manufacturing lines
Speaker 1: to move from singles to family packs. And if they
Speaker 1: could get that signal ahead of the retailers giving them
Speaker 1: that signal, they could get the ground truth. Then they
Speaker 1: could they could proactively sort out that was happening in
Speaker 1: April time. But it was new technology and new new analysis,
Speaker 1: and within a month they had that new analysis. It
Speaker 1: was it was an incredible piece of work. Well, so
Speaker 1: within a month they had they had reconfigured their manufacturing
Speaker 1: lines to do more family packs than singles, absolutely and
Speaker 1: with and within a month they had the data and
Speaker 1: the facts behind it to to help them, you know, um,
Speaker 1: get them to get the balance right, to stay with
Speaker 1: that example that over the last let's just say six months,
Speaker 1: they would be monitors and gradually readjusting their mix as
Speaker 1: people start going back to work. Well, and then and
Speaker 1: then we come back to this this problem which is
Speaker 1: the bullwhip effect, right, and the bull whip effect is
Speaker 1: a real problem that we have at the moment um.
Speaker 1: What is the bullwhip effect? The bullwhip effect says that
Speaker 1: I can see a demand signal for maybe extra five units,
Speaker 1: so I forecast I'm gonna sell an extra five units.
Speaker 1: But my distributor says, oh, they're going to sell an
Speaker 1: extra five units, but they typically get it wrong. So
Speaker 1: I'm going to say an extra ten units. So they
Speaker 1: put that back onto their supply and say, hey, you
Speaker 1: know this company is now gone, is gone extra ten years.
Speaker 1: They say, oh, we'll make that twenty and then their
Speaker 1: supplies says, oh, they typically, you know, I don't want
Speaker 1: to go short here, so we'll make it fifty. Before
Speaker 1: you know it, my five units of demand further down
Speaker 1: the supply chain is fifty units. Now this happens where
Speaker 1: you have a lack of trust in the demand signal,
Speaker 1: because if you don't really trust that demand signal, you
Speaker 1: always inflated a little bit um. And so what's happening
Speaker 1: at the moment, We've got problems on both sides. As
Speaker 1: I said, when with that, that demand signal is hard
Speaker 1: to understand because we don't really know what what the
Speaker 1: new sort of behavior is. And the supply signal, we
Speaker 1: know is disruptive because we've got this repurposing going on
Speaker 1: and rebalancing in the supply. So what happens now is
Speaker 1: I'm going, Hey, I'm going to order ten, not five.
Speaker 1: I'm gonna attend because you know, I'm worried about my
Speaker 1: supply in fact and my order the whole season's worth
Speaker 1: in one go. I'm instead of having weekly orders, I
Speaker 1: might put monthly orders in all quarterly order. And so
Speaker 1: then you get this bumper bullwhip effect where oh, they
Speaker 1: put in a whole quarter of wow demands picking up.
Speaker 1: I'm gonna double that. I'm going to triple that. So
Speaker 1: I'm worried about this amplitude effect that's happening as people
Speaker 1: start to say I'm gonna put bigger supply points in
Speaker 1: because they don't trust my supply base, and people say,
Speaker 1: you don't really know your demand, so actually we're going
Speaker 1: to continue to inflate um. And so that has problems
Speaker 1: obviously because there's going to be some winners and some
Speaker 1: losers with that scenario. So it could be the case
Speaker 1: I'm in a competitive marketplace. I might trust my own data,
Speaker 1: but I don't trust you trust your data, right, So
Speaker 1: I behave strategically and say, well, I don't know what
Speaker 1: Jonathan is doing. He could be he could be holding
Speaker 1: this thing. So even though I only need five units,
Speaker 1: I'm going to return. Yeah, exactly, But how do you
Speaker 1: restore trust systemically? Then? Yeah, you you have to build
Speaker 1: trust I think through technology, because you have to find
Speaker 1: those suppliers and those strategic supply points, and you have
Speaker 1: to start sharing data and actually proving that that five
Speaker 1: is real, right, and that you shouldn't be inflating it.
Speaker 1: And I also need to know that you, Malcolm, is
Speaker 1: my supplier, right, that that you have got the capacity
Speaker 1: that I need, Because if I'm worried that you might
Speaker 1: allocate your capacity to somewhere else, then I'm going to
Speaker 1: double my demand onto you so that you give me
Speaker 1: some if I give you, if I order thirty, maybe
Speaker 1: I'll get the five that I wanted. So you start
Speaker 1: to worry a little bit about classic hoarding problem really
Speaker 1: because I'm not sure I fully understand. So I can
Speaker 1: see how on an individual company level, technology can allow
Speaker 1: me to get to create a far more accurate assessment
Speaker 1: of what my true demand for something is. But but
Speaker 1: everyone has to have trust in our own estimates in
Speaker 1: order for the system to work again and for hoarding
Speaker 1: to be prevented. So I don't how do you get
Speaker 1: how do you go from individual act or trust two
Speaker 1: everyone in the marketplace trusting everyone else's estimates. I I
Speaker 1: think you have to do it pace pace by pace,
Speaker 1: and I think you have you get your own demand
Speaker 1: signal clear. UM. You have to build the relationships with
Speaker 1: your suppliers, make sure you build trust with them, and
Speaker 1: you put technology in place to share information with them.
Speaker 1: And over time you have to you have to just
Speaker 1: start working working through that UM and hopefully we we
Speaker 1: will start to see the supply base rebalancing UM and settling,
Speaker 1: the vibrations calming down a bit, the bullwidth perfect calming
Speaker 1: down a bit, and we'll have a more secure supply
Speaker 1: of products. And then we'll be able to trust the
Speaker 1: demand signal. The holiday season is a big, big effect
Speaker 1: at the moment, right. You know, some of the analysis
Speaker 1: that we've seen says that the shoppers are more likely,
Speaker 1: as you would expect, to start shopping earlier right than
Speaker 1: they have in the past, and one in four global
Speaker 1: consumers have already started shopping, so you're starting to see
Speaker 1: this early consumer demand picking up now. At the same time,
Speaker 1: where what we're seeing in analysis is that they're unlikely
Speaker 1: to spend more this year than they did last year.
Speaker 1: So it's interesting or only marginally more. So they're shopping earlier,
Speaker 1: but they're not going to shop shop more. So one
Speaker 1: of the interesting things here is again is understanding the
Speaker 1: behavior is does that mean I pick up that signal earlier,
Speaker 1: that demand is increasing, that I've got a big, big
Speaker 1: economic bounds, or does it mean that people are just
Speaker 1: buying earlier because they're worried about the supply point those
Speaker 1: two forecasts is huge. One is bumper crop, the other
Speaker 1: is the same crap but very very different demands on
Speaker 1: your manufacturing distribution correct, and that's where this more sophisticated
Speaker 1: driver based analysis of demand becomes really important. And then
Speaker 1: building that type relationship with my supply base, so I'm
Speaker 1: keeping them up to speed as to what we're seeing
Speaker 1: because any sort of drop up off means, hey, we're
Speaker 1: not seeing the massive recovery that we might have been.
Speaker 1: So I have to have that transparency with my key
Speaker 1: suppliers to make sure that I don't have the bullwhip
Speaker 1: effect continuing to amplify. So, now that we have some
Speaker 1: incident into the holiday season, what should consumers do and
Speaker 1: what should suppliers and ants do? The tough one on
Speaker 1: on customers because you know, I think, you know, the
Speaker 1: natural statement from MA would be, you know, please don't
Speaker 1: go out there and buy too early. Don't don't think
Speaker 1: there's a rush. Right, But then you say that and
Speaker 1: then natural thing is people are going to go out
Speaker 1: and rush and buy things early. So, you know, any
Speaker 1: any communication wherein the consumer is a tough message. You know.
Speaker 1: I think the best thing is that the retailers and
Speaker 1: the suppliers that they stay really close to each other,
Speaker 1: that they are communicating regularly to make sure that they
Speaker 1: can have a trusted supply. As long as there's a
Speaker 1: trusted supply and that product is available, then we will
Speaker 1: make sure that we avoid any kind of surge hoarding
Speaker 1: happening from from a customer perspective. So I think for me,
Speaker 1: I put the reliance onto the onto the retailers and
Speaker 1: the suppliers to just work really closely together, to really
Speaker 1: collaborate and make sure they're listening and watching the supply
Speaker 1: signal at a increased level so that they can really
Speaker 1: understand where you know, where the where the demand is going, um,
Speaker 1: and that they respond as quickly as possible to that,
Speaker 1: and then you know, hopefully there'll be enough product and
Speaker 1: we won't have any hoarding and everyone will have the
Speaker 1: right turkey at the right time and the right gifts
Speaker 1: for their family and friends. Jon has been so much fun. Um,
Speaker 1: I really appreciate you taking the time, and I disregard
Speaker 1: what you say and rush from this interview in order
Speaker 1: everything I care in the next fifteen minutes because now
Speaker 1: I'm petrified exactly. But maybe by next Christmas your magic
Speaker 1: will have transformed the marketplace. Really really enjoyed the conversation, Malcolm,
Speaker 1: and you know, just wonderful to spend time with you.
Speaker 1: So thank you for your time. Thank you again to Jonathan.
Speaker 1: Right as I think back to all the conversations I've
Speaker 1: had here on smart Talks. I'm filled with a renewed
Speaker 1: sense of promise, from supply chains and quantum computing to
Speaker 1: five G and empathetic AI. IBM and its partners are
Speaker 1: truly on the cutting edge of technology that will shape
Speaker 1: the way we live and work. Who knows what industry
Speaker 1: they will revolutionize next. Smart Talks with IBM is produced
Speaker 1: by Emily Rostak and Molly Sosha, with Carli Migliori and
Speaker 1: Katherine Gurrodo. Edited by Karen shakerge engineering by Mauran Gonzales
Speaker 1: and Unamrera, mixed and mastered by Jason Gambrel. Music by Granmascope.
Speaker 1: Special thanks also to Kathy Callaghan and Kelly me LaBelle,
Speaker 1: Jacob Briceburg, Heather Fane, Eric Sandler, Maggie Taylor and the
Speaker 1: team's at eight Bar and IBM. Smart Talks with IBM
Speaker 1: is a production of Pushkin Industries and I Heart Radio.
Speaker 1: This is a paid advertisement from IBM. You can find
Speaker 1: more episodes at IBM dot com slash smart Talks. You'll
Speaker 1: find more Pushkin podcasts on the I Heart Radio app,
Speaker 1: Apple Podcasts, or wherever you like to listen. I'm Malcolm Gladwell,
Speaker 1: see you next time.