Global supply chains have made headlines this year, with businesses in every industry and consumers all experiencing unprecedented volatility. How can companies stabilize this boundless bullwhip? In this episode of Smart Talks, Malcolm talks to Jonathan Wright, Global Managing Partner for Supply Chain Consulting at IBM, about demand forecasting and other technologies that manufacturers and vendors are using to make their supply chains more resilient. This is a paid advertisement from IBM.
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Speaker 1 (00:05):
Hello, Hello. This is Smart Talks with IBM, a podcast
from Pushkin Industries, our our radio 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,
(00:26):
I bring you an ode to the holiday shopping season.
Well not just a 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 gonna look at how the supply chain has
(00:48):
evolved since the late nineteen 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 uh strategic supply chains, strategic
(01:11):
relationships which are brought together through technology, and that 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 bull whip effect. Jonathan and
(01:33):
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.
(01:53):
It's is 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'm I
feel like you're one of the few people who can
actually tell me the big picture. I hope we can.
(02:13):
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. Is so much going on, and
we've got to unpack some some issues to 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 a word about the state of the
(02:34):
supply chain. Um, now people like me, do we hear
it all the time. Tell me what has happened in
the last say two years two to drive this disruption? Well, again,
I often say to people, it's like welcome to literally
we we've accelerated UM the kind of thoughts and the
(02:55):
innovation around supply chain by ten years. And the pandemic
has driven that. For sure, UM 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 UM when Wuhan went into lockdown,
and then a shock on the demand side when people
(03:18):
started buying fundamentally different things than they had been doing.
And and I think you know that's probably the biggest
shock UM to the supply chaine since the war. In reality,
is a supply chain system, right that has been disrupted.
Can you be a little more specific on what you
mean by disrupted? So you mentioned people started buying different
(03:39):
things and certain parts of the world were no longer
as capable of producing or moving products as did before.
But can you could have drilled down on the on
all of the sources here, Yeah, for sure, I mean,
you know, we were running out of of people, We
didn't have of toilet paper, all of the classic things
and um, and we went into survival mode and and
(04:02):
I think, you know, people roll their sleeves up, and
we're 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
(04:24):
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
(04:47):
you know, really we're in a in a situation where
we've got this very complex supply chain which is started
to be out of balance, and it's going to take
some work to get it rebalanced. Really, I was playing next,
you know, in doing this series with IBM. One of
the things that consistently been surprised about. Is the things
(05:09):
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 or
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 at
the time where we're seeing convergent technology having a real
(05:32):
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 we had
invested ahead of the curve coming out faster, being able
to respond quicker, being able to understand the supply base quicker,
(05:55):
and the and the exposures and the risk that they had.
UM So I think, you know, 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 splashing problems as as explicitly technological and data problems
(06:15):
as opposed to what you're talking about earlier relationships, you know,
practical kind of bricks and mortary kind of questions. When
does this transition to this notion of it, Oh, it's
just another complicated data problem. And I sort of said,
welcome to twenty that was a bit of the point,
you know, I think this has been a huge acceleration,
a huge jump forward, and the the interest now of
(06:39):
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 forward 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 collaborate action and security
(07:01):
into the supply chains. And I think now what we're
going to see is uh strategic supply chains, strategic relationships
which are brought together through technology, and that that vertical integration,
which once was through ownership, will now be through technology integration.
A couple of questions, super interesting when you said welcome
(07:22):
to did you mean that we are doing things because
of this crisis and especially today that we might not
have otherwise done until is exactly what I say, exactly
give me, give me an example, a really concrete example.
One of my one of my clients was I saying
it would take them maybe a month to onboard a supplier.
(07:46):
But if you if I got a new supplier, by
time I've worked with them, I've done due diligence, I've
figured out their systems and my systems have integrated them.
Maybe it takes a month or longer, could take even
three months. And through the pandemic, um there was this
necessity to bring in the supply straight away. And guess
what if you really break down some of those orthodoxes
(08:07):
of the past and there's 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
(08:30):
last yesterday, last week, last month, last year, will happen
next month, next week? Right? And and now what we
see is, um, that's not not the case. You know,
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
(08:51):
that impact demand. The drivers could be a people working
from home or not. You know, have I got another
spike happening at school? Is open? Are? You know? 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 skew level, at
(09:11):
a product level, you know, what is the demand and
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 last quarter. I can now
start thinking about all the external data. I can look
(09:32):
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
(09:55):
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 but
not a motivation? Is that what you're saying, 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,
(10:19):
it was less less important. Let's go back to two
years ago as a as A for example, was three
years ago? What have you? How many people would have
had a deep map of their supply chain back then?
Very few of the fortune the top two did not
have the picture and the map that they needed. And
(10:42):
what percentage now and have the picture of the map
I needed? I say, 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, you know, kind of up the game. Ye,
(11:06):
your phone must have been bringing off the hook for
the last two years. 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 you know, supporting clients
with vaccine distribution and working through the issues of transparency
(11:31):
and making sure that we understand how how to do
that through too just supply issues and um and and
helping clients navigate this volatile PERIODI is certainly one of
the one of the positives that I think will come
out of this is is more interesting supply chain and
therefore us being able to attract new talent because one
thing that we have got to do to solve these
(11:52):
complex issues is have diverse talent. And I I personally
believe that and 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
(12:15):
take to build one of these maps. Let's say I
come to you unfortunate for one reason another though I
have simply neglected, I have the 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
(12:36):
go gold standard as fast as possible. I'm a company
with sales of I don't know, fifty billion dollars. Okay,
let's assume complex international, you know, like not an easy kisse. Um,
how tell me how long? Tell me how many people
would work on this problem? Tell me tell me how
(12:58):
you would start? Yeah, it's actually, um, 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.
(13:22):
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, a view of their deep supply chain,
that's of their key suppliers in their supply chain. People
are willing to share that kind of data. Yes, absolutely,
(13:44):
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. Um,
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
(14:06):
and 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 um and use
that much more effectively. So what are my internal processes?
And that's actually where the potentially the harder piece comes,
which is reorganizing and getting people to to use data
(14:26):
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 you have
a virtual as system at home, we should all have
one in the supply chain. We can interact with natural
language and we can ask what's and hey, you know,
tell me what happens if if there's an issue at
Malaysia Airport, what are my suppliers are going to be affected?
(14:48):
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 acquires a different way
of working. But if we get that right to me,
he can have a cool, cool environment. We can attract
more talent because instead of doing mundane, dull tasks transactional task,
(15:12):
they can actually be doing value adding tasks. Do you
walk me through this? You mentioned this little bit about
what you do with the information. So I'm I'm the
same company with this large, complex business. You've not given
me this much more detailed, accurate map of what my
(15:33):
supply him looks like. And we see a problem one
of my suppliers, suppliers, supplier deep somewhere on the other
side of the world. Who this is one of my
critical components. And I see, Oh, it's supposed to come
next week. I don't think it's going to come for
two months. What what do I do with that information?
(15:56):
How do I react to it? Well, that back in
the year two thousand not here and Ericsson, if you remember,
they were market leaders in mobile phones UM before before
the world changed. They had two two very different strategies
here around supplier management and UM. And actually Ericsson failed
(16:17):
big time when there was a fire in Albuquerque, in
New Mexico at a Philip's 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 had got you know,
soaked and saturated and smoked damage, and UM and a
mid manager at Ericson had had kind of got in
(16:40):
contact with Phillips 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, this could be a real issue here.
I don't trust that information. I'm not going to be
(17:00):
too complacent and and literally flew over, went down, did
the risk assessment, said no, this, this is not going
to be up and running in any near term. Um
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
(17:23):
and ultimately failed and the company who were no longer
making 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 will
handled very differently, and so so you had both of
(17:44):
them had the same quantitative information. One of them though
added a qualitative layer on top of that where they
went and made an assessment of whether the the supplier
was was being trustworthy in their assessment of how to
interesting to work correct. And this is this is where
the organization design and the skills and the capability will
(18:08):
always be super important. And I think, yes, we've got
to make sure that we have the right um that
the number of suppliers and we've got kind of the
balance of de risking a 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 that
(18:32):
listens to risk and risk management and and is is
absorbing that versus a culture of maybe complacency and trust
which could lead to some failure. M hmm. I think,
I think, I think you do get some are hard moments.
I do think, you know, particularly when you start to
look into um as you say, the deep supply chain map,
(18:54):
you start to realize where those bottom necks 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 your one one location.
So I think it's when you do that modeling of
the supply chain um both in terms of physical flows,
(19:14):
network modeling and the deep network, that you you start
to see those vulnerabilities and nobody. The way that organizations
are set up, you 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 on this? In these kinds of
(19:35):
you said one part of it you already said, well,
it can be surprisingly easy if your suppliers have maps themselves.
What's the hard part? I think that there's there's to
the two hardest parts. M One is is the cleanliness
of data. Right, It's it's very it's very typical in
large organizations for the data to be dirty. And like oil, right,
(19:59):
if you've 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 UM. Then it's a
problem I have. You know, a client, a retailer couldn't
understand why they couldn't UM have on shelf availability. They
(20:20):
couldn't they couldn't replenish the shelf quick enough. And the
reason was that in the system it was recorded as
the shelf was recorded as ten centimeters not not a meter.
So who you know, 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 you why how long had that
(20:45):
error existed in? There have been going on for a
while for a while, and and then they have sort
of manual workarounds. But but you know, if you lose
that tribal knowledge, you use that manual work around, then
you start to realize, you know, what's actually happening, and
then to find the systemic solution. How how long into
COVID before you realized that your world was going to explode? Well, actually,
(21:11):
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 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.
(21:32):
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 the
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's nobody
(21:53):
going to work. Instead, they would be their family packs
were going to go up by because people would be
would be gorging on them at home. So that signal
was super important for that consumer products company, um of
Food Food Company to to then repurpose their manufacturing lines
to move from singles to family packs. And if they
(22:15):
could get that signal ahead of the retailers giving them
that signal, they could get the ground truth. Then they
could they could proactively sort out that was happening in
April time. But it was new technology and new new analysis,
and within a month they had that new analysis. It
was it was an incredible piece of work. Well, so
within a month they had they had reconfigured their manufacturing
(22:40):
lines to do more family packs than singles, absolutely and
with and within a month they had the data and
the facts behind it to to help them, you know, um,
get them to get the balance right, to stay with
that example that over the last let's just say six months,
they would be monitors and gradually readjusting their mix as
(23:00):
people start going back to work. Well, and then and
then we come back to this this problem which is
the bullwhip effect, right, and the bull whip effect is
a real problem that we have at the moment um.
What is the bullwhip effect? The bullwhip effect says that
I can see a demand signal for maybe extra five units,
(23:24):
so I forecast I'm gonna 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 ten units. So they
put that back onto their supply and say, hey, you
know this company is now gone, is gone extra ten years.
They say, oh, we'll make that twenty and then their
supplies says, oh, they typically, you know, I don't want
to go short here, so we'll make it fifty. Before
(23:46):
you know it, my five units of demand further down
the supply chain is fifty 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 inflated a little bit um. And so what's happening
at the moment, We've got problems on both sides. As
I said, when with that, that demand signal is hard
(24:08):
to understand because we don't really know what what the
new sort of behavior is. And the supply signal, we
know is disruptive because we've got this repurposing going on
and rebalancing in the supply. So what happens now is
I'm going, Hey, I'm going to order ten, not five.
I'm gonna attend because you know, I'm worried about my
supply in fact and my order the whole season's worth
(24:30):
in one go. I'm instead of having weekly orders, I
might put monthly orders in all quarterly order. And so
then you get this bumper bullwhip effect where oh, they
put in a whole quarter of wow demands picking up.
I'm gonna double that. I'm going to triple that. So
I'm worried about this amplitude effect that's happening as people
start to say I'm gonna put bigger supply points in
(24:51):
because they 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 um. 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,
(25:14):
but I don't trust you trust your data, right, So
I behave strategically and say, well, I don't know what
Jonathan is doing. He could be he could be holding
this thing. So even though I only need five units,
I'm going to return. Yeah, exactly, But how do you
restore trust systemically? Then? Yeah, you you have to build
(25:36):
trust I think through technology, because 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, is
my supplier, right, that that you have got the capacity
(25:57):
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 thirty, 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
(26:23):
me to get to create a far more accurate assessment
of what my true demand for something is. But but
everyone has to have trust in our own estimates in
order for the system to work again and for hoarding
to be prevented. So I don't how do you get
how do you go from individual act or trust two
(26:47):
everyone in the marketplace trusting everyone else's estimates. I I
think you have to do it pace pace by pace,
and I think you have you get your own demand
signal clear. UM. You have to build the relationships with
your suppliers, make sure you build trust with them, and
(27:10):
you put technology in place to share information with them.
And over time you have to you have to just
start working working through that UM and hopefully we we
will start to see the supply base rebalancing UM and settling,
the vibrations calming down a bit, the bullwidth perfect calming
(27:31):
down a bit, and we'll have a more secure supply
of products. And then we'll be able to trust the
demand signal. The holiday season is a big, big effect
at the moment, right. You know, some of the analysis
that we've seen says that the shoppers are more likely,
as you would expect, to start shopping earlier right than
they have in the past, and one in four global
(27:54):
consumers have already started shopping, so you're starting to see
this early consumer demand picking up now. At the same time,
where what we're seeing in analysis is that they're unlikely
to spend more this year than they did last year.
So it's interesting or only marginally more. So they're shopping earlier,
(28:15):
but they're not going to shop shop more. So one
of the interesting things here is again is understanding the
behavior is does that mean I pick up that signal earlier,
that demand is increasing, that I've got a big, big
economic bounds, or does it mean that people are just
buying earlier because they're worried about the supply point those
two forecasts is huge. One is bumper crop, the other
(28:38):
is the same crap but very very different demands on
your manufacturing distribution correct, and that's where this more sophisticated
driver based analysis of demand becomes really important. And then
building that type relationship with my supply base, so I'm
keeping them up to speed as to what we're seeing
(28:58):
because any sort of drop up off means, hey, we're
not seeing the massive recovery that we might have been.
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. So, now that we have some
incident into the holiday season, what should consumers do and
(29:22):
what should suppliers and ants do? The tough one on
on customers because you know, I think, you know, the
natural statement from MA would be, you know, please don't
go out there and buy too early. Don't don't think
there's a rush. Right, But then you say that and
then natural thing is people are going to go out
and rush and buy things early. So, you know, any
(29:43):
any communication wherein the consumer is a tough message. You know.
I think 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
(30:03):
make sure that we avoid any kind of surge hoarding
happening from from a customer perspective. So I think for me,
I put the reliance onto the onto the retailers and
the suppliers to just work really closely together, to really
collaborate and make sure they're listening and watching the supply
signal at a increased level so that they can really
(30:27):
understand where you know, where the where the demand is going, um,
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. Jon has been so much fun. Um,
(30:47):
I really appreciate you taking the time, and I disregard
what you say and rush from this interview in order
everything I care in the next fifteen minutes because now
I'm petrified exactly. But maybe by next Christmas your magic
will have transformed the marketplace. Really really enjoyed the conversation, Malcolm,
and you know, just wonderful to spend time with you.
(31:08):
So thank you for your time. Thank you again to Jonathan.
Right 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
five G and empathetic AI. IBM and its partners are
(31:30):
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 Sosha, with Carli Migliori and
(31:53):
Katherine Gurrodo. Edited by Karen shakerge engineering by Mauran Gonzales
and Unamrera, mixed and mastered by Jason Gambrel. Music by Granmascope.
Special thanks also to Kathy Callaghan and Kelly me LaBelle,
Jacob Briceburg, Heather Fane, Eric Sandler, Maggie Taylor and the
(32:17):
team's at eight Bar and IBM. Smart Talks with IBM
is a production of Pushkin Industries and I Heart Radio.
This is a paid advertisement from IBM. You can find
more episodes at IBM dot com slash smart Talks. You'll
find more Pushkin podcasts on the I Heart Radio app,
(32:39):
Apple Podcasts, or wherever you like to listen. I'm Malcolm Gladwell,
see you next time.
Hello, Hello. This is Smart Talks with IBM, a podcast
from Pushkin Industries, our our radio 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,
(00:26):
I bring you an ode to the holiday shopping season.
Well not just a 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 gonna look at how the supply chain has
(00:48):
evolved since the late nineteen 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 uh strategic supply chains, strategic
(01:11):
relationships which are brought together through technology, and that 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 bull whip effect. Jonathan and
(01:33):
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.
(01:53):
It's is 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'm I
feel like you're one of the few people who can
actually tell me the big picture. I hope we can.
(02:13):
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. Is so much going on, and
we've got to unpack some some issues to 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 a word about the state of the
(02:34):
supply chain. Um, now people like me, do we hear
it all the time. Tell me what has happened in
the last say two years two to drive this disruption? Well, again,
I often say to people, it's like welcome to literally
we we've accelerated UM the kind of thoughts and the
(02:55):
innovation around supply chain by ten years. And the pandemic
has driven that. For sure, UM 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 UM when Wuhan went into lockdown,
and then a shock on the demand side when people
(03:18):
started buying fundamentally different things than they had been doing.
And and I think you know that's probably the biggest
shock UM to the supply chaine since the war. In reality,
is a supply chain system, right that has been disrupted.
Can you be a little more specific on what you
mean by disrupted? So you mentioned people started buying different
(03:39):
things and certain parts of the world were no longer
as capable of producing or moving products as did before.
But can you could have drilled down on the on
all of the sources here, Yeah, for sure, I mean,
you know, we were running out of of people, We
didn't have of toilet paper, all of the classic things
and um, and we went into survival mode and and
(04:02):
I think, you know, people roll their sleeves up, and
we're 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
(04:24):
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
(04:47):
you know, really we're in a in a situation where
we've got this very complex supply chain which is started
to be out of balance, and it's going to take
some work to get it rebalanced. Really, I was playing next,
you know, in doing this series with IBM. One of
the things that consistently been surprised about. Is the things
(05:09):
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 or
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 at
the time where we're seeing convergent technology having a real
(05:32):
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 we had
invested ahead of the curve coming out faster, being able
to respond quicker, being able to understand the supply base quicker,
(05:55):
and the and the exposures and the risk that they had.
UM So I think, you know, 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 splashing problems as as explicitly technological and data problems
(06:15):
as opposed to what you're talking about earlier relationships, you know,
practical kind of bricks and mortary kind of questions. When
does this transition to this notion of it, Oh, it's
just another complicated data problem. And I sort of said,
welcome to twenty that was a bit of the point,
you know, I think this has been a huge acceleration,
a huge jump forward, and the the interest now of
(06:39):
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 forward 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 collaborate action and security
(07:01):
into the supply chains. And I think now what we're
going to see is uh strategic supply chains, strategic relationships
which are brought together through technology, and that that vertical integration,
which once was through ownership, will now be through technology integration.
A couple of questions, super interesting when you said welcome
(07:22):
to did you mean that we are doing things because
of this crisis and especially today that we might not
have otherwise done until is exactly what I say, exactly
give me, give me an example, a really concrete example.
One of my one of my clients was I saying
it would take them maybe a month to onboard a supplier.
(07:46):
But if you if I got a new supplier, by
time I've worked with them, I've done due diligence, I've
figured out their systems and my systems have integrated them.
Maybe it takes a month or longer, could take even
three months. And through the pandemic, um there was this
necessity to bring in the supply straight away. And guess
what if you really break down some of those orthodoxes
(08:07):
of the past and there's 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
(08:30):
last yesterday, last week, last month, last year, will happen
next month, next week? Right? And and now what we
see is, um, that's not not the case. You know,
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
(08:51):
that impact demand. The drivers could be a people working
from home or not. You know, have I got another
spike happening at school? Is open? Are? You know? 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 skew level, at
(09:11):
a product level, you know, what is the demand and
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 last quarter. I can now
start thinking about all the external data. I can look
(09:32):
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
(09:55):
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 but
not a motivation? Is that what you're saying, 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,
(10:19):
it was less less important. Let's go back to two
years ago as a as A for example, was three
years ago? What have you? How many people would have
had a deep map of their supply chain back then?
Very few of the fortune the top two did not
have the picture and the map that they needed. And
(10:42):
what percentage now and have the picture of the map
I needed? I say, 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, you know, kind of up the game. Ye,
(11:06):
your phone must have been bringing off the hook for
the last two years. 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 you know, supporting clients
with vaccine distribution and working through the issues of transparency
(11:31):
and making sure that we understand how how to do
that through too just supply issues and um and and
helping clients navigate this volatile PERIODI is certainly one of
the one of the positives that I think will come
out of this is is more interesting supply chain and
therefore us being able to attract new talent because one
thing that we have got to do to solve these
(11:52):
complex issues is have diverse talent. And I I personally
believe that and 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
(12:15):
take to build one of these maps. Let's say I
come to you unfortunate for one reason another though I
have simply neglected, I have the 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
(12:36):
go gold standard as fast as possible. I'm a company
with sales of I don't know, fifty billion dollars. Okay,
let's assume complex international, you know, like not an easy kisse. Um,
how tell me how long? Tell me how many people
would work on this problem? Tell me tell me how
(12:58):
you would start? Yeah, it's actually, um, 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.
(13:22):
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, a view of their deep supply chain,
that's of their key suppliers in their supply chain. People
are willing to share that kind of data. Yes, absolutely,
(13:44):
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. Um,
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
(14:06):
and 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 um and use
that much more effectively. So what are my internal processes?
And that's actually where the potentially the harder piece comes,
which is reorganizing and getting people to to use data
(14:26):
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 you have
a virtual as system at home, we should all have
one in the supply chain. We can interact with natural
language and we can ask what's and hey, you know,
tell me what happens if if there's an issue at
Malaysia Airport, what are my suppliers are going to be affected?
(14:48):
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 acquires a different way
of working. But if we get that right to me,
he can have a cool, cool environment. We can attract
more talent because instead of doing mundane, dull tasks transactional task,
(15:12):
they can actually be doing value adding tasks. Do you
walk me through this? You mentioned this little bit about
what you do with the information. So I'm I'm the
same company with this large, complex business. You've not given
me this much more detailed, accurate map of what my
(15:33):
supply him looks like. And we see a problem one
of my suppliers, suppliers, supplier deep somewhere on the other
side of the world. Who this is one of my
critical components. And I see, Oh, it's supposed to come
next week. I don't think it's going to come for
two months. What what do I do with that information?
(15:56):
How do I react to it? Well, that back in
the year two thousand not here and Ericsson, if you remember,
they were market leaders in mobile phones UM before before
the world changed. They had two two very different strategies
here around supplier management and UM. And actually Ericsson failed
(16:17):
big time when there was a fire in Albuquerque, in
New Mexico at a Philip's 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 had got you know,
soaked and saturated and smoked damage, and UM and a
mid manager at Ericson had had kind of got in
(16:40):
contact with Phillips 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, this could be a real issue here.
I don't trust that information. I'm not going to be
(17:00):
too complacent and and literally flew over, went down, did
the risk assessment, said no, this, this is not going
to be up and running in any near term. Um
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
(17:23):
and ultimately failed and the company who were no longer
making 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 will
handled very differently, and so so you had both of
(17:44):
them had the same quantitative information. One of them though
added a qualitative layer on top of that where they
went and made an assessment of whether the the supplier
was was being trustworthy in their assessment of how to
interesting to work correct. And this is this is where
the organization design and the skills and the capability will
(18:08):
always be super important. And I think, yes, we've got
to make sure that we have the right um that
the number of suppliers and we've got kind of the
balance of de risking a 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 that
(18:32):
listens to risk and risk management and and is is
absorbing that versus a culture of maybe complacency and trust
which could lead to some failure. M hmm. I think,
I think, I think you do get some are hard moments.
I do think, you know, particularly when you start to
look into um as you say, the deep supply chain map,
(18:54):
you start to realize where those bottom necks 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 your one one location.
So I think it's when you do that modeling of
the supply chain um both in terms of physical flows,
(19:14):
network modeling and the deep network, that you you start
to see those vulnerabilities and nobody. The way that organizations
are set up, you 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 on this? In these kinds of
(19:35):
you said one part of it you already said, well,
it can be surprisingly easy if your suppliers have maps themselves.
What's the hard part? I think that there's there's to
the two hardest parts. M One is is the cleanliness
of data. Right, It's it's very it's very typical in
large organizations for the data to be dirty. And like oil, right,
(19:59):
if you've 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 UM. Then it's a
problem I have. You know, a client, a retailer couldn't
understand why they couldn't UM have on shelf availability. They
(20:20):
couldn't they couldn't replenish the shelf quick enough. And the
reason was that in the system it was recorded as
the shelf was recorded as ten centimeters not not a meter.
So who you know, 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 you why how long had that
(20:45):
error existed in? There have been going on for a
while for a while, and and then they have sort
of manual workarounds. But but you know, if you lose
that tribal knowledge, you use that manual work around, then
you start to realize, you know, what's actually happening, and
then to find the systemic solution. How how long into
COVID before you realized that your world was going to explode? Well, actually,
(21:11):
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 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.
(21:32):
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 the
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's nobody
(21:53):
going to work. Instead, they would be their family packs
were going to go up by because people would be
would be gorging on them at home. So that signal
was super important for that consumer products company, um of
Food Food Company to to then repurpose their manufacturing lines
to move from singles to family packs. And if they
(22:15):
could get that signal ahead of the retailers giving them
that signal, they could get the ground truth. Then they
could they could proactively sort out that was happening in
April time. But it was new technology and new new analysis,
and within a month they had that new analysis. It
was it was an incredible piece of work. Well, so
within a month they had they had reconfigured their manufacturing
(22:40):
lines to do more family packs than singles, absolutely and
with and within a month they had the data and
the facts behind it to to help them, you know, um,
get them to get the balance right, to stay with
that example that over the last let's just say six months,
they would be monitors and gradually readjusting their mix as
(23:00):
people start going back to work. Well, and then and
then we come back to this this problem which is
the bullwhip effect, right, and the bull whip effect is
a real problem that we have at the moment um.
What is the bullwhip effect? The bullwhip effect says that
I can see a demand signal for maybe extra five units,
(23:24):
so I forecast I'm gonna 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 ten units. So they
put that back onto their supply and say, hey, you
know this company is now gone, is gone extra ten years.
They say, oh, we'll make that twenty and then their
supplies says, oh, they typically, you know, I don't want
to go short here, so we'll make it fifty. Before
(23:46):
you know it, my five units of demand further down
the supply chain is fifty 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 inflated a little bit um. And so what's happening
at the moment, We've got problems on both sides. As
I said, when with that, that demand signal is hard
(24:08):
to understand because we don't really know what what the
new sort of behavior is. And the supply signal, we
know is disruptive because we've got this repurposing going on
and rebalancing in the supply. So what happens now is
I'm going, Hey, I'm going to order ten, not five.
I'm gonna attend because you know, I'm worried about my
supply in fact and my order the whole season's worth
(24:30):
in one go. I'm instead of having weekly orders, I
might put monthly orders in all quarterly order. And so
then you get this bumper bullwhip effect where oh, they
put in a whole quarter of wow demands picking up.
I'm gonna double that. I'm going to triple that. So
I'm worried about this amplitude effect that's happening as people
start to say I'm gonna put bigger supply points in
(24:51):
because they 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 um. 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,
(25:14):
but I don't trust you trust your data, right, So
I behave strategically and say, well, I don't know what
Jonathan is doing. He could be he could be holding
this thing. So even though I only need five units,
I'm going to return. Yeah, exactly, But how do you
restore trust systemically? Then? Yeah, you you have to build
(25:36):
trust I think through technology, because 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, is
my supplier, right, that that you have got the capacity
(25:57):
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 thirty, 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
(26:23):
me to get to create a far more accurate assessment
of what my true demand for something is. But but
everyone has to have trust in our own estimates in
order for the system to work again and for hoarding
to be prevented. So I don't how do you get
how do you go from individual act or trust two
(26:47):
everyone in the marketplace trusting everyone else's estimates. I I
think you have to do it pace pace by pace,
and I think you have you get your own demand
signal clear. UM. You have to build the relationships with
your suppliers, make sure you build trust with them, and
(27:10):
you put technology in place to share information with them.
And over time you have to you have to just
start working working through that UM and hopefully we we
will start to see the supply base rebalancing UM and settling,
the vibrations calming down a bit, the bullwidth perfect calming
(27:31):
down a bit, and we'll have a more secure supply
of products. And then we'll be able to trust the
demand signal. The holiday season is a big, big effect
at the moment, right. You know, some of the analysis
that we've seen says that the shoppers are more likely,
as you would expect, to start shopping earlier right than
they have in the past, and one in four global
(27:54):
consumers have already started shopping, so you're starting to see
this early consumer demand picking up now. At the same time,
where what we're seeing in analysis is that they're unlikely
to spend more this year than they did last year.
So it's interesting or only marginally more. So they're shopping earlier,
(28:15):
but they're not going to shop shop more. So one
of the interesting things here is again is understanding the
behavior is does that mean I pick up that signal earlier,
that demand is increasing, that I've got a big, big
economic bounds, or does it mean that people are just
buying earlier because they're worried about the supply point those
two forecasts is huge. One is bumper crop, the other
(28:38):
is the same crap but very very different demands on
your manufacturing distribution correct, and that's where this more sophisticated
driver based analysis of demand becomes really important. And then
building that type relationship with my supply base, so I'm
keeping them up to speed as to what we're seeing
(28:58):
because any sort of drop up off means, hey, we're
not seeing the massive recovery that we might have been.
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. So, now that we have some
incident into the holiday season, what should consumers do and
(29:22):
what should suppliers and ants do? The tough one on
on customers because you know, I think, you know, the
natural statement from MA would be, you know, please don't
go out there and buy too early. Don't don't think
there's a rush. Right, But then you say that and
then natural thing is people are going to go out
and rush and buy things early. So, you know, any
(29:43):
any communication wherein the consumer is a tough message. You know.
I think 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
(30:03):
make sure that we avoid any kind of surge hoarding
happening from from a customer perspective. So I think for me,
I put the reliance onto the onto the retailers and
the suppliers to just work really closely together, to really
collaborate and make sure they're listening and watching the supply
signal at a increased level so that they can really
(30:27):
understand where you know, where the where the demand is going, um,
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. Jon has been so much fun. Um,
(30:47):
I really appreciate you taking the time, and I disregard
what you say and rush from this interview in order
everything I care in the next fifteen minutes because now
I'm petrified exactly. But maybe by next Christmas your magic
will have transformed the marketplace. Really really enjoyed the conversation, Malcolm,
and you know, just wonderful to spend time with you.
(31:08):
So thank you for your time. Thank you again to Jonathan.
Right 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
five G and empathetic AI. IBM and its partners are
(31:30):
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 Sosha, with Carli Migliori and
(31:53):
Katherine Gurrodo. Edited by Karen shakerge engineering by Mauran Gonzales
and Unamrera, mixed and mastered by Jason Gambrel. Music by Granmascope.
Special thanks also to Kathy Callaghan and Kelly me LaBelle,
Jacob Briceburg, Heather Fane, Eric Sandler, Maggie Taylor and the
(32:17):
team's at eight Bar and IBM. Smart Talks with IBM
is a production of Pushkin Industries and I Heart Radio.
This is a paid advertisement from IBM. You can find
more episodes at IBM dot com slash smart Talks. You'll
find more Pushkin podcasts on the I Heart Radio app,
(32:39):
Apple Podcasts, or wherever you like to listen. I'm Malcolm Gladwell,
see you next time.
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