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On this latest episode, Lisa Anderson, President of LMA Consulting Group joins the podcast. Lisa is one of the most respected voices in manufacturing strategy, supply chain transformation, and SIOP. She’s the author of a recently released book titled AI & Advanced Technologies in Manufacturing, where she explores how manufacturers are using AI and advanced analytics to drive real, […]
The post Where AI Is Actually Delivering Value in Manufacturing Supply Chains first appeared on Composites Weekly.
The post Where AI Is Actually Delivering Value in Manufacturing Supply Chains appeared first on Composites Weekly.
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All right, welcome back to another episode of Composites Weekly.
Before we get into this episode real quick,
I want to mention next week,
we'll be live streaming at JEC World,
but Tuesday and Wednesday, that's the 10th and 11th
we'll be doing live interviews on the show floor all day.
Well, actually not on the show floor,
we'll be in hall five at the TV studio area.
Our location will be in H-142,
but yeah, doing a lot of interviews all day with exhibitors,
also some of the Innovation Award winners
and finalists this year and then some of the startup booster
finalists as well.
So we'll get a nice mix of longstanding companies,
the part of the industry as well as some up and coming companies
and excited to talk about some of their innovative technology
that they'll be showcasing at this year's show.
If you happen to be near that area over at hall five
near the media area, feel free to stop by.
I'd love to chat.
We'll be back to back to back with interviews,
but feel free to stop in and say hello.
So save travels everyone and hope to see you next week.
So on today's episode, I've got Lisa Anderson joining me.
She is one of the most respected voices
in manufacturing supply chain strategy and sign up.
She's the author of a couple of books,
one of her most recent book is called AI and Advanced Technologies
and Manufacturing, where she explores how manufacturers
are using AI and advanced analytics to drive real measurable
results from demand forecasting to optimize production planning.
In our conversation today, we're going to dig into how AI is
actually improving manufacturing supply chains
and where companies are seeing real value versus hype.
So with that said, here's our interview
with Lisa Anderson, president of LMA Consulting Group.
Lisa, thanks so much for spending some time
with me on the podcast today.
I'm glad to be here.
So before we get in, I want you to share a little bit
about your background.
We'll do.
So I started off actually out of college
in working at Coca-Cola, in planning and distribution
management, and then worked my way up over the years
and my last job before consulting
was a vice president of operations and supply chain.
And then from there, I've now been consulting
for just over 20 years.
So I'm excited, it's been a while.
So you've seen some challenges in your time,
a lot of the way when it comes to supply chain, right?
That's for sure.
If anything was true, it's that the supply chain
is constantly changing and disruptions
and evolutions are commonplace.
Yeah, 2020 was a major challenge for our industry as well.
I probably just about every industry here in the US
in abroad.
Those were serious challenges and enough to awaken people
to the fact that I need to diversify or reshore.
I don't know what the answer was,
but apparently there needed to be a lot of change after that.
I mean, you're absolutely correct.
It was a pivotal change in the supply chain.
So the pandemic, prior to the pandemic,
there was a lot of discussion about Amazon like service.
And it was really all about quick 24, seven quick service
and being more like Amazon.
And then the pandemic changed the world.
And we realized that you have to be able to count
on your supply chain.
It's not as easy as just saying, you know, get it here quicker.
It became a lot more complex overnight in essence.
And so it's been that way ever since, especially with geopolitical risks.
Yeah, increasing.
Well, that's another thing.
Geopolitical risk and then we had tariffs last year.
And so yeah, there seems to be a lot of disruptions going on.
I find it interesting.
You've published a book on AI as a tool,
as a facilitator for improving or streamlining your supply chain.
It's a good time to write a book on AI,
but is there a particular reason that you wanted to address this issue at this time?
Well, as you said, we're seeing across the board with our clients
that, you know, they're struggling to keep up
with all these changing conditions, you know, the disruptions are coming
yet they still need to perform well, you know, be profitable.
They have to serve customers.
And it really is just not as easy in quotes like us as it used to be.
So, you know, they need to be utilizing AI and advanced technologies to be successful.
It's really become the norm to, you know, to better have a modern ERP system
and to be able to utilize additional functionality in features
because you have to go quicker.
I mean, the Amazon effect is still in place,
but you have to be quicker, global, you know,
and be able to gain visibility in your supply chain.
You have before thinking innovative.
I pretty much have to do everything all it lets to be successful.
Just to summarize, from this, you talk about how AI is changing the way manufacturers should think
about demand forecasting and production planning.
Where do you see companies still getting it wrong when it comes to, I guess,
these, you know, forecasting and planning?
Well, forecasting and planning are two hot topics.
Yeah, companies are realizing that it matters
as to, first of all, to support your customer's needs on time,
sounds relatively simple.
However, it's not as though they necessarily are giving you advanced notice
and not changing their mind to those types of things.
They still supply chain conditions evolve.
And so quotes and orders and pipelines change on a daily basis.
So you have to be able to not only keep up with it, but be predictive
of what's going to be coming down the pipe, which is where AI and advanced technology comes into play.
So from a sales forecasting point of view, you obviously want to be predictive
of what's going to happen instead of waiting for it to happen to you.
However, you also want to be looking at, you know, your predictive,
now what is happening so that you can adjust on the fly and adjust for changing conditions.
So it depends.
You have to be able to forecast for a company that's like highly big volume,
high volume, high promotions.
At the same time, you also need to be able to forecast at the product level
for like an engineer to order a custom manufacturing company.
So both of which there are techniques that you can utilize,
advanced technologies and AI, demand planning, software that you can utilize.
It depends on the situation that all software is created equal.
AI is in essence, the buzzword.
Yes.
Everyone incorporates it into the conversation, but what they're really doing is another story.
So most of the modern ERP software are incorporating AI into the software.
Now, of course, it depends.
Are we talking about like an Oracle or SAP?
They have a lot more AI features than some of the mid-tier software.
Although, all of them are going to have some level of AI features.
When it comes to demand planning and production scheduling,
some of the features can be incorporated in,
but a lot of them are additional software.
So let's just say for the topics that you brought up from a forecasting point of view,
CRM has incorporated some AI type capabilities in looking at.
It's a hot topic for AI, really.
Because you can see what's changing in your customer base.
You can pick up on trends and what customers haven't been ordered from in a certain period of time
or haven't contacted.
So that's meant for AI, if you will, or the topics are a marriage, maybe even if you will.
So basically, that's been incorporated to a lot of the demand planning,
sales forecasting type tools.
You also brought up production scheduling.
You know, it's interesting.
A lot of the improvements we make can be achieved by utilizing some common sense approaches.
However, AI can be utilized and should be utilized to gain visibility,
if you will, into what's coming down the pipe.
You brought up SIOP, sales, inventory operations, planning.
There are, there's features that you can use to say like an advanced planning system utilizes AI.
And that means like, let's say you have multiple facilities throughout the world
and you're saying, OK, how do I reallocate production among the facilities
to meet my changing sales forecast?
And do so in a way that, you know, do I have the people?
Do I have the equipment?
Right.
How do I like look at that equation?
And then also look at which ones will be the most cost effective?
And it can also relate to freight, right?
So you say from that facility, my freight to my customer is what?
So how do I, what AI does a really good job of is looking at multiple variables at once
and like doing its number crunching and then providing some information?
And then of course, in today's AI systems,
it also takes it a step further with like alerts and like it'll even, you know,
write emails to suppliers, if you will, to ask them for status,
because that's another piece of supply chain visibility.
Where is your order in the pipeline?
Yeah, and I find it interesting.
I'm backing up to what you said earlier on CRM.
Everybody is familiar with Salesforce.
I think they're kind of implementing a lot of the AI features into their platform.
So I know that's, that's helpful from a sales forecasting standpoint.
I think from a supply chain, it's very interesting because, you know,
I've talked to people who literally are using AI and it could be just, you know,
conversing with chat GPT, but talking about issues like this, for instance, the straight
of hormones, that's a critical choke point.
It could impact a lot of companies here in the US.
And it's a primary export route for the Gulf States.
So yeah, I mean, things like that are interesting that you can implement AI
to get feedback on how these geopolitical or these supply chain disruptions
when you're choking off certain routes, you know,
how those are going to affect supplies over season and the raw materials that we,
we depend on.
Yeah, no, you're absolutely right.
These days, there's actually quite a bit there.
You can utilize crowdsourcing with like supply chain visibility software to say,
where's the next choke point to your point?
Because like, there's always something happening.
What geopolitical risks might happen?
And where, which routes will it affect, right?
But then also AI is utilized in like SAP's advanced planning,
but you know, it's similar to like I said, like a lot of the, the Oracle and SAP's
out there are going to do this, but it, in essence, it's telling you, like I have,
where are, where are all the containerships that contain materials?
And they also contain products perhaps, right?
Because you have, you may have a global network and you're moving all, you know,
whip, finish goods and raw materials throughout your networks.
So it'll tell you where, where are they all and what containerships and, you know,
what potential disruptions are happening along the way.
And then it'll quickly do that rerouting calculations to say, you know,
how do I get best get to where it has to go?
Let's say it's bringing raw material.
How do I get best gets is a manufacturing facility in a way that's, you know,
the shortest route or more efficient, most efficient route at the same time, you know, we have,
you know, or do we need to move it to a different, different manufacturing facility?
And so the network could become quite complicated.
And that's where AI is particularly good because they can do what a human well could do,
but it would take a lot longer.
And customers are not willing to wait for you to go, you know,
how we call your what's happening.
You know, I would think for manufacturers, especially in industries like composites,
complex industries like what we work in and who want to start using AI to optimize supply chains
and production plans, you know, what would be a practical first step if they haven't started
already? Where should leaders be focusing when they're looking at investing in new technology like
I mean, it's a really good question actually because you can get very carried away
with with AI and not do something that's actually going to bring value to the bottom line
right time soon.
So I would say one area that's pretty robust and it's also been around for quite a while
because it's an early use is what you got up originally and that's the, you know,
demand planning sales forecasting because it's just so ideal for this situation.
You can have it through, you know, at different product groupings or, you know,
different site levels so that you can see where your demand is and how it's changing and
trending right because you want to make sure that say it's trending up in a certain region.
Well, you need to make sure that the whichever suppliers relate to the production that relates
to that region are prepared because maybe they don't have capacity.
So how do you take that to your end ends by changing? So I would say first is one area to start
with is your sales forecast. Sure. And then from there, I think you're absolutely right actually
as many times you can make significant improvements with your production schedule and it could just be
in like, for example, like we actually built like a sia platform that's like a simpler version
that has some AI type features. Sometimes it's just a correct, like you don't have data throughout
all of your systems or like all your fields are not filled in. And how do you do that in a way
where you can rely upon the information in your system without saying, oh, we have to update all
of our data to be 100% correct. Well, that is by then you will have lost all of your customers.
So how do you like update on the fly in a directionally correct way? There are some, you know,
data type softwares or you can, you know, you can even incorporate some of that logic
in like power queries or you can do it in like, you know, like we built a platform that kind of
relates to sia that does that same type of function. So I would say like solve the production
scheduling also relates to not just keeping the data updated, but it's what sequence do you run in?
How do you optimize inventory among your facilities? And the good news about that topic,
similar to demand planning is that you have known factors so that it can optimize among known
factors. It's easier to get started with because like you know your inventory, you may be able to
calculate, you know, the service level you're looking for the lead time. So, you know, to some
degree it takes like an MRP type system to the next level of being able to say like how do I
optimize further, take it step further than like base functionality. So I would stick with something
like that so that you can be successful because you want a directionally correct result.
If you want a timely, a timely basis, like I said, you, I've seen many clients that spend way too
much time trying for the ideal solution, but they never make a step forward, you know, in that case.
And so that's that's that's an issue. And so you have also have another you have you've authored
another book on it's sia creating predictable revenue and be to gross. I mean what if you could
summarize that for us real quick before we close out and sia process is in essence what we've
been talking about today. So it's a good way to wrap up right. So it's you take your sales forecast
or your picture of demand because it could just be you'll have orders quotes. There's always
something more in demand than you realize. So you take the inputs to customer demand and then you
say what does this mean in terms of people equipment distribution networks facilities and
and then it depends on your situation of course, how many facilities and those types of things you
have. But how do I make sure how do I get these the demand through my operation through my operations
in a way that's most, you know, it'll serve customers and is most profitable. That's really what
sia is about. And it allows you to make the changes between, you know, should I make this product
or buy it? Should I produce it from X facility or why? How do I how do I optimize my network?
And how do I optimize the inventory and forecast inventory? That's another key piece to
this equation. Lisa, how can our listeners learn more about you? What is the I've got the website
pulled up. I believe that's LMA that's not consulting. It's LMA dash consulting group.com,
right? That's correct. LMA hyphen consulting group.com is the perfect place to go.
They have many several newsletters podcasts. And you know, LinkedIn is also another great
way to reach me. So that's going to be very cool. So you have a podcast too that they could
subscribe. Yes, absolutely. It's called supply chain chats. So you can buy them.
Awesome. That's fantastic. Well, thank you, Lisa. I appreciate you spending some time and we'll
certainly be posting links for people to check out on the on your latest book on AI. Certainly
want to our listeners to go there and check it out that download that. That's an ebook, correct?
That's correct. Access. Yeah. They're both ebooks actually. You can pay for or just download
the SIAP ebook as well. Lisa, thank you so much for spending some time. Really good conversation.
AI is changing so much of how we do business from sales to inventory to supply chain manager.
You know, I think it goes both ways. A lot of people talk about AI taking jobs, but you know,
I think it's also in one sense that may be the case. Yes, but it's also enhancing, you know,
productivity for a lot of people in their jobs, making things a lot easier to navigate these
disruptive times. Oh, I couldn't agree more. It's it's absolutely allowing for companies to be
more productive and to manage by exception instead of having to have a kind of people
fill this down with each other. Lisa, thanks again. Hope you have a great week and look forward to
getting this out to our listeners and best of success with you and your company moving forward.
Great. I enjoyed it as well. Thank you.
