Introduction

I'm going to talk a little bit about the present as well.

And I'm going to talk about not my company, but a company that Plug and Play invested in.

And if that's OK with you, I'll just sit down as well.

Speaker Background

I'm Zoë Chrysostom, I've been an investor at Plug & Play for the past three years and I focus mainly on looking at innovations and new technologies in fashion, retail, e-commerce, luxury in general and I do that to support brands and retailers innovate and to remain competitive and also think about new products, services so that they can continue growing.

We do that with large corporations.

Plug and Play Ventures

Plug and Play is both an investor itself. So we're a venture capital firm.

We invest in tech startups and pre-seed, seed and series A. So very early stage, which allows us to be able to detect those innovations and recommend them to clients like LVMH, Kering, Nike, Walmart. Really, we work with 600 corporations globally, and that's kind of how we work.

Just wanted to give a bit of background.

And we invested in this company that I'm going to talk a little bit about right after.

AI and Its Impact in Fashion

Obviously, AI has been, I'd say, probably the main topic for clients for the past two years. Obviously, it's been for many, but especially these past two years.

And if I focus on fashion, because this was supposed to be the focus of the talk, We see the main project being mostly in marketing optimization and content creation for e-commerce.

This has been projects for Lacoste, L'Oréal, even clients like Bacardi, Danone. It's been the main one because it's so easy in terms of impact that you can see directly.

Essentially, we are seeing AI impacting the whole value chain from manufacturing to e-commerce, but it's just about prioritizing and choosing the use cases where you will see the most impact. So definitely marketing and content creation has been the key one.

Use Cases in Marketing

If I give a couple of examples, with a fashion brand.

They're currently using a company, a solution called Digital First AI, which is a marketing automation tool that basically automates the whole marketing activity. So they plug to all of your different sources of data in a company and they will do the market research for you based on that market research, create a strategy for your marketing campaign based on that marketing campaign, then create the content for TikTok, different social media platforms.

So from like end to end.

And we also look at many other use cases that are more like backend and HR, fintech, etc. But marketing has been the big one.

Use Cases in Manufacturing

But actually, another one that we really look into at Plug and Play is around optimizing manufacturing processes.

And that's why we see this right behind me. We see it as an opportunity to make conditions in factories better for workers, but also just more efficient in general to reduce overproduction.

Because if we take the angle, and that's going to be the focus for the next, I'd say, five, seven minutes, if we take that angle from the other side, If we talk about fashion's impact on the environment, a lot of it is due to its overproduction.

According to many sources, including McKinsey, BOF, Business of Fashion, 40% of unused or unsold clothing is thrown into landfills. And so that overproduction is actually A lot of it is due to very outdated production models.

Challenges in Manufacturing

And that's production that outdated production model is due to a couple of things. And main one is, first of all, long lead times, long lead times within these manufacturers is due to the fact that a lot of it is manual still. Let's say, well, actually the first part is that In general, you need to do large bulks of ordering, right?

It's cheaper, it's more logistically also efficient. And that is do why long lead times between like 60 days to 120 days.

That's because a lot of it is manual and so it requires a lot of resources, a lot of time. Why is it manual?

Today if you, as a brand or a designer, I send my technical packs to a manufacturer, they will manually check all of the information for all the different brands. Then they will manually create a production scheduling with post-its, with Excel. And that takes a lot of time.

And so usually to kind of, because of that, you need to order more in order to make sure that you have enough. And a lot of also how the industry works is that it bases on and I'll show you as well its basis on forecasting models on what consumers might want but it can help in some point but not only right and so

Digitizing Manufacturing Processes

And so in order to find a way to make a shorter lead time and to make it more efficient, it's about digitizing all these processes and automating all of these processes.

Investment in Manny AI

And so that's why we invested in a company called Manny AI. They're basically a manufacturing optimization tool that offers solutions for manufacturers and for brands at the same time.

And I'll go over it a little bit and happy to answer any questions afterwards.

Factory Tools for Digitization

So on one hand, it offers factories a tool that can digitize their whole shop floor, where the machines are, where the workers are, where the fabric is. Where are the different materials?

And on the other, it helps also brands have all of that information and better communicate with manufacturers.

Fabric Inventory Digitization

1Today, many AI allows to digitize a whole inventory of fabrics in a factory. And that allows designers and buyers at fashion brands to know in real time the volume of the fabrics, what they have used in the past, and also that allows them to better associate the fabrics with the garments that they want to make and also not order fabrics that the manufacturer might already have.

So fabric digitization, which is cutting a lot of time.

Technical Pack Standardization

The second one would be around technical pack standardization and translation.

Today, as a fashion brand, let's say Lacoste or even ASOS, they have their own fashion brands. As a designer or buyer, I would send the technical packs to the manufacturer and manually they would check If there are errors or if all of the information, so technical packs maybe for non-fashion people, it's the documents that you send to manufacturers that tells about what you want to produce, what garments you want to produce, all the details and measurements etc.

And if there are manual errors, that decreases the quality of the garment that you produce, that creates well, increases the time for productions.

And so with many AI, basically with their AI model, they're able to just predict all of the different gaps of measurements and details and auto-generate that in the documents that are being sent to the manufacturers. And that can be confirmed by the brand and the manufacturer in order to reduce the time also on the sampling.

And another part, if I can show you,

Optimized Production Planning

And the final piece would be, and I'd say this is the most impressive one, is the fact that based on all of the information that is sent by the brand, the solution can create a whole production planning minute by minute, while before it was by day and it was not digitized. So you couldn't collect any data, you couldn't optimize your processes.

So think about what this person A with this machine at this time needs to do this step in order to make this garment, in order to achieve this delivery time. And so that allows us to create smaller batches because you're reducing your time of production. And that allows you to cut costs and be more efficient and essentially allows you to create smaller batches of productions in order to react more closely to customers' demand and essentially reduce overproduction.

Benefits of Manufacturing Optimization

So how efficiency, making the processes within a factory more efficient, cutting time, cutting lead time, and creating smaller production batches. And hence, obviously, the effect is obviously cost degrees and also better work condition, et cetera.

But it's also good for the planet, if I'm a bit cheesy.

Conclusion

I'm gonna stop here.

I'm happy to answer more details about the solution, but this is one example that I wanted to highlight because usually these topics in fashion on the manufacturer level is, is not really covered by a lot of investors and venture capital firms.

And it's still so, so manual, so much work to do. And this is a great example of how I can improve processes within a factory and also for brands.

Thank you.