Released in the definitive instalment in fashion’s longest-running dedicated PLM Report, this executive interview is one of a nine-part series that sees The Interline quiz executives from major companies on the evolution of product lifecycle management, and ask their opinions on what the future holds for what has long been sold as the core of the fashion technology ecosystem, and the heart of design, development, and supply chain processes.
For more on product lifecycle management in fashion, download the full PLM Report 2023 completely free of charge and ungated.
Key Takeaways:
- PLM providers should work to make PLM as easy as possible for other technologies to connect to, and consider how data is used and shared with other solutions up and down the entire value chain.
- Sustainability strategies are critical in fashion, and businesses need to use data from a wide variety of technology solutions to deliver on greenhouse gas emission claims.
- PLM providers should build the bill of process (BOP) to enable brands and retailers to understand the end-to-end processing and complete the full picture.
- Machine learning and generative AI will likely be incorporated into PLM within the next 1 to 2 years.
The places software begins and ends are constantly changing as market demands shift, new innovations emerge, and fresh capabilities and integrations are added. Can you tell us what PLM means to WhichPLM Advisory, and how you believe that definition has evolved over the last few years?
As I’ve stated many times over the last 24 years since we first brought PLM to the market: PLM is a methodology, first and foremost, therefore it encompasses a universe of software solutions, each operating within its own sub-ecosystem. Today, businesses should recognise and educate themselves on this fact, and should look at the entire circular workflow from consumer trend, to design and development, costing, sustainability, sourcing, manufacturing and eventually back to the consumer.
You wrote a piece for this report talking about the positive impacts of generative AI for PLM users. What do you believe is the timeline for this? And which areas will we see AI-driven transformation the soonest, versus the areas that are likely to take longer?
We’ve all experienced some form of artificial intelligence – the likes of GPT – but many more have recently come to the market offering solutions. Many of these software solutions have developed different levels of maturity in building generative AI using machine learning. Unlike the bigger companies, they have limited data and language models, but this has not stopped them developing forms of automation. I would expect to see elements of machine learning coming into PLM within the next 1 to 2 years.
Where do you believe sustainability fits into the PLM picture? Should organisations be looking at it in a modular way – better materials as one step, more transparent supplier relationships and reduced physical sampling as the next – or working backwards f rom a more comprehensive target and encouraging (or mandating) everyone who uses PLM to make choices that contribute to that target?
The industry is now required to provide scientific evidence when making greenhouse gas emission claims, and to deliver on this, it’s critical that we use data coming from a wide variety of technology solutions, business processes, learning models, and upstream (Tier 1-6) data providers. We need to move quickly, decisively across all tiers.
Staying on sustainability, a big piece of the puzzle is still missing in that few brands really know the makeup of their multi-tier supply chain. What role can PLM play in connecting those different stages and providing real visibility and transparency?
PLM providers should move quickly to build the bill of process (BOP); this will enable brands and retailers to understand what happens based on the choices of materials, finishes, colour options, and the end-to-end processing. The bill of process should work together with the bill of materials (BOM) and the bill of labour (BOL) to complete the full picture, which will then enable scientific impact calculations to be completed accurate.
In a market where PLM is an important part of a brand’s technology stack, but definitely not the only part, how do you see the advisor’s role changing? Because there’s less of an emphasis today on solution selection and much more weight being placed on strategy, ecosystem integration, and vision.
When it comes to problem-solving, I don’t look at PLM. Instead, I look at the processes and the unique software solutions that support each of those processes. I also consider the bigger picture and attempt to connect data elements between each of those data inputs and outputs. If you can only see PLM as the solution, you are missing the bigger picture. PLM is only a small piece of the picture!
How do you see PLM’s role in the fashion technology ecosystem evolving in the near future? How can it best support fashion’s ongoing digital transformation?
PLM vendors need to work hard and accept that PLM is the data repository and is not the end-to-end solution. They need to make PLM easy for other technologies to connect to in the same way that we use apps on our mobile phones. We’ve arrived at the time when we need to look at which solution really owns that data, how it is used and how it’s best shared with other solutions up and down the entire value chain.
