Missed approvals. Slipped deadlines. Teams chasing updates across email, spreadsheets, and suppliers in different time zones. For fashion brands, the result is clear: calendar misalignment and margin erosion on a scale no executive can afford to ignore. Industry reports suggest that seasonal delays can erode 10–15% of potential margin, compounding year after year.

PLM was supposed to fix this. And for a time, it did—connecting design, development, and sourcing in a single platform. But today, even the most sophisticated PLM deployments are stretched to breaking point. They can surface data, but they cannot act on it. The future demands more.

What’s coming is not another system upgrade. It’s a fundamental shift: the arrival of intelligent, autonomous AI agents operating inside fashion’s value chain.

From Tweak to Transformation

For more than two decades, PLM has been fashion’s digital backbone. But PLM was never designed for an era of ecosystems that change minute by minute. Its workflow engines rely on manual inputs, its approvals move at human speed, and its integrations are patchwork at best.

“PLM was never built to collaborate with every system in a brand’s ecosystem,” says Mark Harrop, founder of WhichPLM. “It requires manual inputs to support critical paths and workflows. The reality today is that workflow engines within PLM simply aren’t capable of managing the inputs and outputs of all the solutions and communications happening every minute, hour, or day.

“That means management teams are still relying on humans to constantly chase each and every approval—or disapproval. Without an AI-driven internal clock, connected via APIs to the ecosystem, we simply can’t know where we are in real time. And the result is inefficiency on a massive scale.”

This is why the next leap won’t come from tweaking PLM. Incremental gains won’t save brands from systemic inefficiency. The real transformation will come from connecting existing systems to intelligent, autonomous agents that can orchestrate work in real time.

Lessons From Fashion’s Past

Every leap in fashion has followed a leap in technology. The sewing machine industrialised garment-making, cutting production time from days to hours. CAD and CAM digitised design and pattern cutting, reducing waste and accelerating development. In the 1980s, PDM digitised garment specifications. By the early 2000s, PLM connected entire value chains.

What unites each of these shifts is not gradual improvement, but total reinvention. Once the leap happened, it became irreversible. And every time, the brands that moved first gained an advantage that laggards could never recover.

That’s the stage the industry is at now—with AI.

The New Colleagues: Near-Future Case Studies

In 2026, a global apparel leader pilots TimeClock, an AI orchestrator integrated into its PLM. A lab-dip approval in New York runs two days late. Before the delay cascades across the supply chain, TimeClock automatically pings the colourist, alerts sourcing, and updates the PLM in real time. By the time London wakes up, the calendar is back on track—no chasing, no firefighting.

Another brand tests TrendScout AI, monitoring cultural signals, social data, and engagement metrics. When it identifies a surge in Seoul-inspired tailoring, TrendScout matches it against design DNA and recommends reusing two existing blocks. Sketching begins before breakfast.

Meanwhile, CostWizard runs sourcing scenarios at scale, balancing freight, duties, and carbon impact across Vietnam, Bangladesh, and Turkey. Finance signs off in minutes, not weeks.

These aren’t sci-fi imaginings. In logistics, AI agents already reroute shipments in real time to avoid bottlenecks. In finance, they simulate risk scenarios across global portfolios. Fashion will follow—and soon.

Why This Change Matters

At the centre of every seasonal delay is the calendar. One missed approval, one late material, one overlooked update—and the entire season slides. The cost is real: each day of delay can erode a brand’s annual margin by several percentage points.

Yet PLM can’t prevent this. It can record delays, but it can’t resolve them. Which is why Harrop argues that AI agents must step in to handle the “spaces between”—those countless handoffs between systems, suppliers, and teams that humans struggle to manage at scale.

“If you can remove bottlenecks and keep every step in sync,” Harrop says, “you change the economics of a season.”

For executives, the advisory is simple: AI is not a shiny add-on. It is the missing orchestration layer that can restore discipline to calendars and resilience to margins.

The Window Won’t Stay Open

History makes one fact clear: the brands that hesitated on each past technology leap never caught up. The same will be true for AI.

Leaders must act now. Start small, with pilots—TrendScout, TimeClock, or EnviroGuard. Use each deployment to validate value. But don’t stop there. Create a cross-functional AI strategy taskforce spanning design, sourcing, finance, and sustainability. Treat AI adoption as structural, not experimental.

The decision is not whether AI agents will enter fashion. They will. The decision is whether your brand will lead with them—or chase from behind.

Fashion has always been about patterns—in fabrics, in culture, in the rhythms of seasons. AI is about patterns too—in data, behaviour, and choice. Together, they represent the industry’s next great leap.

And the call to leadership is clear: you can stitch the future on your own terms, or watch as others cut ahead, the clock is truly ticking.

Mark Harrop

The post From Threads to Thinking Machines: Fashion’s Next Great Leap appeared first on WhichPLM.

Since the Ecodesign for Sustainable Products Regulation (ESPR) came into force in 2024, the Digital Product Passport (DPP) has moved from legislative ambition to regulatory reality. While not yet mandatory across every sector, its phased introduction is already underway. Batteries are the first category to fall under these rules by 2026, with textiles, electronics, and furniture expected to follow soon after. By the end of this year, the EU will finalise detailed requirements for each category — marking the point at which the countdown truly begins.

In other words, the clock is ticking. And the reality for fashion brands is stark: the complexity of the value chain, combined with the length of time required for data cleanup and system integration, means that those who wait until the final deadlines are announced will already be too late.

The Cost of Inaction

Standing still is no longer safe. The risks are escalating on three fronts. First, the regulatory burden is real: fines under the EU Green Deal framework can amount to a percentage of global turnover — enough to sting even the most profitable multinational. Second, consumer trust is eroding. Seven in ten consumers say they no longer believe sustainability claims unless they are backed up by verifiable data. Third, inefficiency itself has become a liability. Across many design and sourcing teams, 40 to 50 percent of working hours are lost to chasing down data, reconciling spreadsheets, and correcting errors across the supply chain. Those lost hours don’t just drain morale — they cost millions in delays, missed launches, and shrinking margins.

The workflows that served the industry for the last two decades — static reports, supplier declarations, spreadsheet-led compliance — were never elegant, but they were functional enough. Today, in the face of regulatory complexity and market scepticism, they are simply not fit for purpose.

AI as the Connective Tissue

The fashion value chain is notoriously fragmented. Information lives everywhere — from CAD tools and 3D platforms, to PLM systems, Excel files, WhatsApp chats, Slack threads, and endless email chains. The challenge is not just that this data is scattered; it’s that it is formatted differently, updated at different times, and riddled with inconsistencies.

AI should not be misunderstood as a replacement for these existing systems. It is better understood as connective tissue — a layer that binds them together, weaving interoperability into a network of tools that were never designed to communicate. In doing so, AI preserves existing investments while making them fit for a future of compliance and competitiveness.

Imagine a supply chain agent that works overnight, gathering updates from hundreds of suppliers, validating them automatically, and delivering a clean set of results directly into PLM — without the need for a single email. Or picture a boardroom scenario, where an executive asks: “Which products have certifications expiring this quarter?” and an AI copilot delivers the answer instantly, backed with linked evidence ready for audit. These are not science-fiction visions. They are real applications of AI copilots, agents, and multimodal models already emerging in today’s workflows.

From Declarations to Living Records

Transparency is evolving. It is no longer enough to know where something was made. The coming era of compliance demands a living, machine-readable history of every material, every certification, and every decision made along the journey from design to consumer.

AI enables this evolution. Instead of static declarations, brands can move to continuous assurance. DPP submissions can be generated with linked evidence. Sustainability metrics such as CO₂, water, and energy consumption can be monitored in real time, broken down by supplier or by bill of materials. AI agents can proactively flag risks — certificates approaching expiry, or emissions exceeding benchmarks — before they become compliance failures.

This represents not just a technological shift but a cultural one. Compliance has traditionally been a backward-facing exercise: painful, periodic, and reactive. The future, however, is continuous, embedded, and predictive. It is the only way to satisfy regulators and to rebuild trust with consumers.

The Clock is Ticking

For fashion, the DPP mandate is not yet active — but it is no longer a question of “if.” The legislative roadmap is clear, with sector-specific deadlines already in motion. What is uncertain is not whether DPP will apply, but how quickly each category will be brought into scope. For brands, the only safe assumption is that enforcement is inevitable — and that waiting for final deadlines is a gamble most cannot afford.

The journey to readiness is long. Data cleanup alone requires 12 to 18 months, and AI layering another 6 to 12. For most organisations, that means beginning now if they hope to be compliant in time. If a regulator asked tomorrow, could you prove compliance in real time? Could you demonstrate traceability across every product and every certification? For many, the honest answer today would be no. But those who act now can ensure that by the time the mandates crystallise, they are not just ready, but ahead.

Conclusion: From Optional to Essential

The industry has reached a pivotal moment. Digital lifecycles are no longer a nice-to-have; they are fast becoming mandatory. Transparency is not a marketing slogan but a compliance requirement. Evidence is not an add-on but the foundation of trust.

The journey towards AI-enabled transparency is not without challenges, but it is both achievable and necessary. It begins with recognising that legacy systems are not obsolete, but under-utilised. It continues with the systematic work of data cleanup, system integration, and AI enablement. And it culminates in a value chain that is not only compliant but efficient, resilient, and future-proof.

The brands that start today will be the ones telling the success stories of tomorrow. The ones who wait risk discovering — too late — that compliance is no longer optional, and trust cannot be retrofitted.

Mark Harrop

The post Preparing for Transparency with a Flexible Value Chain, Backed by Data appeared first on WhichPLM.

For those readers who may not recall the static fashion trends of the Web1 era, in the mid-90s, trends were primarily dictated by magazines, luxury brand creative directors, and catwalks. It was very much a top-down, centralised approach, where style and messaging were concentrated in the hands of a few people, who had the luxury of dictating it to the rest.

The arrival of Web2 ushered in a new level of democratisation, breaking the traditional trend processes and spreading out power by allowing communities to connect, grow, and communicate through global platforms. This era also gave rise to disruptive trend-forecasting entities such as WGSN, Fashion Snoops, Mintel, and others e. WGSN was founded in 1997 and managed by my friends Marc and Julian Worth, before the business was sold in 2005 (it continues to operate today, aiming to predict trend and culture on a near-decade-long horizon), and those four letters quickly became synonymous with a new idea of what trend should be in the always-on, social media age. Companies like WGSN became prominent trend oracles for brand, retailers’, and designers across the world.

However, as time passed, the rise of this responsive trend model – where mass market brands chased consumers rather than setting the benchmark – translated into a feeling that high-street brands and retailers were homogenising their design DNA, all chasing the same transient fashion fads, and all dipping into the same forecasting buckets of silhouettes, materials, assets, colour themes, and styling detail.

This sentiment was not helped by the rapid expansion of social media channels such as Facebook, Instagram, Twitter, and YouTube, which prompted these trend forecasters to expand their capabilities, by harnessing big data, and artificial Intelligence (AI), to evolve trend forecasting into a quasi-science backed process of forecasting that has become today’s best-practice model, despite its limitations. For most brands, capturing trends from social media has become a purely reactive exercise – and one that’s conducted at an unmanageable scale, with organisations deploying all those data-driven insights just to try and stay one step ahead of what a constantly-changing global market wants.

The future, then, is going to have to land somewhere in between these two extremes. It should allow brands and designers the ability to set new creative directions at the same time as empowering micro-communities to create and own new trends.

Which is why, looking ahead to the future of Web3 in fashion, I believe that a transition from Web2 is not only inevitable, in fact, it’s already started.And my estimate places this shift to within a 3–5-year timeframe. This is not to say that the present model will totally shift during this period, but rather that new disrupters will continue to create new businesses, and platforms that will allow consumers to understand the value of their own data and how they share it with brands, and retailers that will start delivering hyper-personalised product options.

During this transformation period, we can expect greater emergence of businesses both new and existing – businesses that will leverage Web3 architecture, operating on decentralised internet platforms using blockchain technology, together with AI. Software developers will continue to harness this architecture to create decentralised applications (dApps), and these same businesses will create open Application Program Interfaces (APIs), leveraging other related ‘smart’ software and hardware that can contribute to a product’s smart lifecycle.

The Web3 era will focus on facilitating hyper-personalisation, utilising Generative Artificial Intelligence (Gen-AI) and real-time data to cater to individuals, and small fashion tribes, instantly responding to emerging trends rather than leading to brands being overwhelmed and left behind the curve when trying to cater to individuals, or a small tribes fashion specific needs.

How? I can imagine a near-term future where, instead of adhering to macro trends of today’s Web2 model, brands will leverage new Web3 models linked to micro-real-time, hyper fashion trends. This Web3 approach will allow brands, and retailers to analyse precise consumer data feeds, including consumers’ own avatars, fit measurements, styling preferences, and other data elements. It’s this vision and approach that will enable the transformation of trend analysis – moving from a single-brand mass-market approach to a detailed real-time micro-trend approach, culminating in not only mass-customised fitting products, but also serving the individual customer!

Mass customisation (MC) for those that are not familiar with the term, is a model that has been used for several decades, offering bespoke elements (waist, thigh, leg length) while maintaining production at scale, addresses the challenge of fitting products and understanding customer preferences. Mass customisation should not be confused with Made-To-Measure (MTM), and Bespoke Manufacture of a single garment, which is typically a wedding dress or a suit made for a special occasion. That individual tailoring remains a separate and viable sector.

The main difference with Mass Customisation is exactly that it caters to the masses (large groups of people sharing the same measurements), providing the consumer with a Made-To-Measure feeling, but obviously without a product being made in accordance with an individual’s specific body measurements.

Advancements in technology have overcome previous technological limitations of delivering on mass customisation, cost effectively, and are now able to propel the fashion industry into a new era where brands can now, using AI as a starting point, economically deliver on mass customisation, (Single Ply Cutting, Direct-to-Garment, or Direct to Roll dyeing, whole Knitted garments, 3D printing, etc.), resulting in further disrupting the current status quo by offering personalised designed and fitting products that are “tailored” for their loyal customers.

As that infrastructure is being built out, Web3 will also be changing the game on the consumer-facing and trend side of the equation, creating advanced AI models that filter down to the consumer’s real-time “trend oracle.”, and will even guide the product through localised sustainable manufacturing processes. This two-way interaction will also allow consumers to shape the design process based on their individual data types, owning and designing on their own avatars, and constantly developing their own fit preferences.

Web3 will predict future trends more accurately than previous models at the same time empowering customers to understand the value of owning their data, including personal avatars, purchasing history, style choices, lifestyles, their individual likes, and dislikes. Web3 customers will be able to choose which brands access their data, completely transforming their shopping experience. Furthermore, decentralised marketplaces, tokenized garments, and enhanced transparency will mark the future of Web3, opening doors to not only unparalleled personalisation, but it will allow all brands to deliver on their environmental sustainability goals!

As Web3 unfolds, questions will of course arise on how brands will adapt to a decentralised marketplace, the emergence of new e-commerce platforms connecting designers directly with customers, maintaining brand identity in a decentralised ecosystem, leveraging blockchain technology for end-to-end transparency and ethical sourcing. Brands will need to adapt their marketing and communication strategies to resonate with smaller communities and down to the individual’s level, where power dynamics will shift towards the consumer.

In conclusion, just as Webs 1 and 2 gave way to progress, Web3 is emerging fast, and I anticipate the fashion and footwear industry following suit by adopting a decentralised approach supported by Web3. This shift will not only support environmental sustainability in the Retail, Footwear, and Apparel (RFA) sectors but will also bring financial benefits through reduced product returns, derived from truly understanding your customer’s total needs.

Mark Harrop,
With nearly five decades as a technology advisor to the fashion industry, Mark has dedicated his career to helping the world’s renowned brands, retailers, and manufacturers achieve efficiency savings throughout their entire supply chain via informed technology investments.

The post From the Era of Web1 to the Rise of Trend Oracles: AI Unveils Fashion’s Web3 Era of Hyper-Personalisation appeared first on WhichPLM.

From transparency and trust to the next stage of virtual runways, 2024 promises to have more action than ever, with technology impacting brands, retailers, and stakeholders across the entire scope 1-3 fashion value chain. Let’s dive into what I consider to be some of the most promising areas, where innovation has the biggest potential to unlock tangible transformation.

Sustainability Storytelling: Data Democratisation, Transparency and Trust

Consumers aren’t just buying clothes anymore; they’re buying stories. And in that value exchange, transparency and data are the new currency. With properly captured, audited data as its source, Blockchain technology could soon pave the way for real-time tracking and traceability, ensuring ethical sourcing and sustainable practices throughout the extended value-chain. Imagine scanning a garment tag and witnessing its journey, from farm to factory to the store, and into your wardrobe. Talk about informed purchasing power and a new narrative!

Across sectors, organisations like Everledger are already using blockchain to authenticate luxury goods to help combat counterfeiting, building trust and encouraging responsible consumerism. Fashion and luxury goods -like clothing, shoes, and leather items- are some of the most counterfeited products, constituting 65% of the counterfeit luxury industry. The true value of fake materials is likely higher than estimated, as not all illegal activity gets detected or reported! The challenges of implementing these token-based solutions at scale might be high, but the potential is just as high – potentially giving the industry a way to prevent huge amounts of value from leaking out.

Digital Twins: Reimagining Design and Development

Forget prototypes gathering dust in storerooms, iterative samples for minor design changes, repetitive fit review sessions, and archives of over-ordered and unused materials. We’re now in the era of digital twins – virtual replicas of physical materials and products, that have the power to streamline design, development, and collaboration. Imagine tweaking patterns, testing materials, sampling, and optimising fit – all in the digital realm. 3D-DPC (digital product creation) companies are leading the charge, enabling brands to reduce errors, shorten lead times, and minimise waste. It’s a win-win not only for efficiency, cost, but also in enabling ESG (environmental, social and governance) goals.

Gaming Goes Couture: The Virtual World Beckons

Fashion is stepping into a new, dynamic space, blurring the lines between physical and digital experiences, and crossing over into other media. Imagine owning limited-edition digital sneakers or attending exclusive fashion shows in immersive virtual worlds, where virtual avatars become clotheshorses, showcasing unique garments and accessories.

Brands like Nike and Louis Vuitton are already playing in this digital sandbox, creating exclusive NFTs and virtual wearables. This has the potential to open new revenue streams and engage tech-savvy consumers, but questions about intellectual property (IP) ownership and value in the virtual world will need further exploration.

Companies like PhygitalTwin are helping those that are tired of overproduction and lengthy design cycles empowering brands to create fashion pieces digitally.

Their platform allows designers to design, customise, and produce clothes on-demand, minimising waste, and maximising agility. Using the brand’s own design DNA to explore new trends quickly, cater to individual preferences, and even bridge the gap to virtual fashion with Phygital Twins innovative tools. They are also enabling consumers to embrace the future of fashion by designing their own ultra-personalised products that are sustainable, and digitally driven.

Sustainable Savvy: Fabrics and Fibres for a Greener Future

Sustainability is no longer a trend, it’s a necessity. Bio-based fabrics derived from algae, mushrooms, or recycled materials are gaining traction, as are innovative dyeing techniques that help to minimise water and chemical usage. Patagonia and The North Face lead the charge with repair programs and take-back schemes, promoting circularity and responsible consumption. These advancements address growing environmental concerns and contribute to a more sustainable fashion ecosystem.

Augmented Shopping: Try Before You Buy (Virtually!)

Forget crowded fitting rooms and the “will-it-fit?” dilemma. Augmented reality (AR) apps are bringing virtual try-ons to your living room. Think visualising garments on your body, experimenting with styles, and finding the perfect fit before ever stepping into a store. Companies like Wannaby are making this a reality, empowering consumers to shop smarter and are helping to reduce returns. AR, as well as virtual reality (VR) can also provide rich product information and brand storytelling, creating a more informed and personalised shopping journey. Take Gucci’s AR app that provides a realistic representation of how shoes will look on your feet, helping you make informed purchase decisions in the comfort of your own home. The app also offers a fun and interactive way to explore Gucci’s latest collections and experiment with different styles.

The Tip of the Fashion-Tech Iceberg

As we continue to navigate 2024, prepare for even more mind-blowing advancements, collaborations, and innovative applications. Brands that embrace these disruptive technologies and adapt their strategies will be better positioned to thrive in the new tech era of fashion. Remember, technology is a tool, but the human touch remains essential. Let’s leverage these innovations to create a more sustainable, inclusive, and exciting fashion future for all of us.

From virtual runways to AI-powered design assistants, the tapestry of fashion is being woven with new threads in 2024. These disruptive technologies offer a tantalising glimpse into a future where fashion transcends physical limitations, embraces sustainability, and caters to individual expression like never before.

However, with every innovative stitch comes a knot to be unravelled. Questions about ethical use, environmental impact, and the very definition of ownership in a digital world demand thoughtful consideration. Are we creating a more inclusive and accessible industry, or exacerbating existing inequalities? Can we balance technological advancement with the human touch?

Ultimately, the future of fashion is not one predetermined design, but a collaborative project waiting to be stitched together. From policymakers and brands to designers, manufactures, manufacturing partners, and consumers, each stakeholder holds a digital needle and thread. Let us use them to weave a future where technology empowers creativity, sustainability becomes the guiding principle, and fashion, in all its forms, remains a vibrant expression of our humanity.

Mark Harrop
As a technology advisor to the fashion industry, Mark has worked for almost five decades to help the world’s best known retailers, brands and manufacturers achieve efficiency savings across their entire supply chain through informed technology investments.

The post From Digital Twins to Data Democratisation: The Disruptive Technologies Reshaping The Fashion Value-Chain appeared first on WhichPLM.

Fashion moves fast. And thanks to the accelerating effect of technology, this year we’re likely to see it move even faster.

Before jumping into my predictions for 2024, though, I want to compare the coming wave of change to the early 90s, when the World Wide Web was invented and then commercialised. Because for people like me, who were well into their careers at that time, the anticipation and uncertainty that’s everywhere at the moment is going to feel very familiar.

It goes without saying now, but the internet was a metamorphic moment of change for every industry, and one of the first industry movers taking advantage of this moment was the fashion industry. By 1995, several global businesses had launched their online marketplaces – businesses like eBay and Amazon, which moved quickly – followed by an explosion of e-commerce businesses over the next few years.

There were, of course, organisations that failed to see the real potential (and the true scale) of the internet in time, but history has shown that when a major technological revolution comes, the businesses that embrace it early are the ones that thrive.

Looking back also reminds us that, for all the exciting new possibilities, the most profound changes often come from figuring out how to deploy new disruptions in service of optimising existing business models, eliminating inefficiencies, and connecting people in new ways. Before the Internet came to the fashion industry, for example, we struggled with communications using paper-based systems, PDM (Product Data Management) for internal teams, telex, faxes, and clunky emails as our way to connect with external partners.

Then fashion moved to using the Internet and quickly started transitioning to instant messaging, video conferencing, followed by social media and cloud-native PLM (Product Lifecycle Management) – which, combined, revolutionised how we shared and connected with our internal teams, supply-chain partners, and consumers.

As much new possibility space as it unlocked, the real lasting impact of the Internet was to help democratise fashion’s ecosystem, swiftly tearing down brick-and-mortar walls and igniting global trends like wildfire. It empowered independent voices, elevated new creatives and new commercial models, reshaped marketing, kick-started fast fashion, and redefined fashion’s relationship with traditional seasons and styling. So much of what we take for granted in fashion today is younger than many people realise, as well as much of it being directly attributable to the dawn of the web.

Looking into AI, today, feels like stepping back into those heady days of dial-up Internet when we used 14.4k and 28.8k modems to communicate with our supply-chain partners. The technology isn’t ready for prime-time, just as it wasn’t in those early days of the internet, but it’s the same electricity of potential that I feel, the thrill of exploring a vast, practically uncharted territory.

Over time, the technology will mature (the jump from modem to ADSL, for instance, was made by the early 2000s) and every industry – but especially fashion – will see the same rapid-fire progress as we did from deciphering cryptic URLs to interacting with intuitive web apps, with the same delightful mix of brilliance and unexpected stumbles along the way.

The key difference, though, is that I believe we’ll move through that maturity curve exponentially faster. And predicting what’s on the other side is easier in some ways (because the capabilities are already here) but harder in others, because building innovation on top of innovation is inherently unpredictable.
Back then, the Internet’s full potential was unknown. Could anyone in the mid-90s really have predicted TikTok – with all its positive and negative implications – with Netscape Navigator as their sole frame of reference?

AI is in the same position today, with concerns about security, privacy, and societal impact dominating the headlines. Similarly, we are still unsure how AI will evolve – and a lot of people, including some of its creators and custodians, are unclear on how it actually works. People have fears surrounding its development and application – some of which are entirely reasonable. There are potential long-term consequences of its widespread adoption: job displacements, algorithmic bias, IP protection, privacy & security, and a pressing need for transparency and accountability from the companies behind the major frontier models.

As we move forward, just like in the early days of the Internet, we will need to address each of these concerns with the help of researchers, policymakers, and the public, to ensure that AI can be effectively, safely, and successfully embedded across the fashion sector – since the scale of that embedding is already well underway.

With all that in mind, enough of the past: let’s look at some of the new trends that you can expect in 2024, all of which AI are either fundamental to, or which AI will serve to accelerate

Hyper-Personalisation

The future of AI in fashion trend analysis is brimming with exciting possibilities, promising to revolutionise how we understand and predict what’s going to sell and, perhaps more importantly, what’s not. Unlike humans, AI algorithms can sift through and surface insights from oceans of data from diverse sources, including runway shows, street-style photos, social media trends, tastemakers and influencers, e-commerce platforms, brands’ own real-time sales data, and search engine queries. They can deliver up-to-the-minute and continuous data that can, provided the right systems are put in place, feed an LLM (Large Language Model) that users can then interact with as a kind of trend oracle, and use to inform the next cycle of brand-wide design and development.

And the same principles can also be extrapolated into personalised product creation; AI can provide an accurate and comprehensive understanding of what people are wearing, buying, and talking about (good and bad sentiments), revealing hidden patterns and emerging trends, which consumers can then use to inform their personal style and which brands can offer as a consumer-facing service with on-demand production as the backend.

Brands that truly get to know their customers, gender, age, hobbies, body shapes, actual sizings, fit preferences, colour choices, product types, previous purchases, even the location that they live in will help brands provide hyper-personalised offerings. Brands that follow this path and that operate using personalised data will then be able to create new made-to-order, and to some extent mass-customisation models. Offering new benefits like high margins, positive customer satisfaction, reduced return rate, reduced stock to name just a few of the benefits.

Image recognition and understanding

Although it’s been employed for this purpose, AI can go far beyond simply identifying colours and patterns in images. It can analyse the nuances of silhouettes, prints, plains, textures, and even the emotions evoked by specific garments or footwear styles. This deeper understanding will lead to more precise trend forecasting and personalised recommendations.

Trend & Mood Boards

AI can analyse the cultural and social context surrounding fashion trends, considering factors like current events, (ESG) environmental and social sustainability, economic conditions at the regional, country, or city level, celebrity influencers, and even AI influencers! This all-round approach will lead to a more nuanced understanding of what drives trends and how they are likely to evolve.

Design & Development

As AI gains momentum (and, crucially, builds trust), design teams, with help from their IT departments, will build (LM) models that will ingest the latest trends (weekly, Daily, Hourly!) and use AI prompts (text descriptions) along with computer vision to generate new design inspirations in just a few minutes. Generative AI models will be used to illustrate stories and articles that automatically create design briefs and support product launch materials.

AI will dramatically upscale the value of 2D sketches, converting them quickly into photographic quality 3D images by training on combined 2D patterns, photographs & 3D data, and rendering techniques to spark ground-breaking designs that will accurately relate to given body measurements, the scale of prints, logos, design assets, or embroideries – and that, in turn, will be displayed on human-like Avatars.

Developers using PLM data will be able to access (LLM) to explore and analyse sustainable materials and processing methods that will help provide more excellent options for more sustainable design choices. AI will accelerate and inspire design & development teams using data-driven insights rather than solely human intuition.

AI image enhancements

AI image enhancement tools will be infused across design, development, and manufacturing teams, offering multiple use cases that will, in turn, drive significant value to all partners by upscaling low-resolution images and turning them into crisp, high-resolution photos driven via intelligent algorithms. AI tools like ColorLUT and VanceAI can adjust colour tones, boosting vibrancy and correcting lighting imbalances, ensuring garment photos radiate in their intended hue. Many use case examples include wrinkle removal, background replacement, creative scene settings, and material texture boost. These are just a few examples.

Digital Twins

The usage and the value of Digital twins will continue to grow, driven partially via the combination of AI’s powerful modelling linked with IoT (Internet of Things), physical devices, embedded sensors, and other technologies such as Blockchain software that will help collect data across the end-to-end value chain.

Text-to-Video

Text-to-video is another extension of generative AI that will move rapidly this year, and the use cases are widespread. Here are several examples: Brands can train their AI models to explain the benefits of a company’s product in moving video, rather than 2D or 3D imagery. Design teams can see their ideas come to life using text prompts (keywords), for example, “bohemian t-shirt.” The text-to-video model will generate a video that will include a collage of t-shirts and accessories, inspiring the team.

Virtual fashion shows are another text-to-video example that designers can use as part of their growing toolsets. Turning 2D Trend Forecast and Mood Boards into AI-generated dynamic video collages showcasing new designs, materials, and silhouettes will become a new reality. Many more use cases will benefit from text-to-video, especially for the downstream teams in marketing.

3D-Printed Garments, Footwear & Accessories

3D printing technology is rapidly advancing; imagine a future when you can print your clothes at home! 3D printing will open a world of possibilities for customisation and creativity. Design and development teams are already printing out shoes and garments. Companies like Stratasys, Materialise, and Nervous Systems lead the way in 3D printing.

Smart Fabrics and Wearables

I expect to see materials and wearables that do more than just look good. The possibilities are endless, from fabrics that can monitor your health and heart rate to garments that change colour based on temperatures or textures. Imagine a sports shirt that tracks your heart rate and adjusts the resistance for you, or a dress that changes colour to match your mood, or changes linked to sunlight. Footwear and Accessories: most people wear smartwatches, don’t they? So why can’t we embed sensors into our products beyond RFID tags and QR codes?

Sustainable Fashion and Upstream value-chain

AI will help optimise product planning, material, and resource allocation. At the same time, AI will streamline value chains and minimise waste through improved design eco-friendly printing, cutting, and manufacturing processing. AI will also help forecast demand with uncanny accuracy, preventing overproduction, bringing in new on-demand models, and ensuring the right products reach the right people at the right time.

AI will also assist in a future of agile manufacturing, where AI ensures every digital thread, and every digital stitch contributes to both profit and environmental sustainability impact. AI can help minimise waste and track the lifecycle of every product from seed to second-hand shop. AI’s influence will extend further up the value chain, guiding sustainable sourcing decisions and identifying ethical partners based on current KPIs (Key Performance Indicators). It will be able to detect potential disruptions in the value chain, mitigating risks and ensuring resilience.

Across all of these use cases, we should ensure that AI has a conscience, where transparency and responsibility become competitive advantages.

By embracing AI upstream, brands will not just be optimising processes but tapping into a wealth of innovation and foresight. Brands will be able to create a fashion ecosystem that is not only responsive but also responsible, respecting resources and valuing ethics, and pave the way for a more sustainable and adaptable fashion industry.

3D-DPC: From Click to Catwalk

On-Demand Fashion: Forget supply chain headaches and inventory nightmares. 3D-DPC is the fashion replicator, beaming bespoke garments from the digital realm to customer doorsteps (or, more likely, living room printers). 3D-DPC isn’t just about convenience; it’s about sustainability, slashing lead times, minimising carbon footprints, and offering instant gratification unlike anything before. But remember, with great power comes great responsibility. Invest in robust intellectual property safeguards, ethical sourcing practices, and responsible waste management to ensure your brand isn’t just fast; it’s ethical.

The Metaverse Makeover

Fashion beyond the physical is the Metaverse gaining new momentum; it’s another frontier of a brand experience. Virtual showrooms brimming with digital collections, accessible to global audiences 24/7. Think personalised avatars sporting outfits also available in-store or online, influencing trends that ripple through the real world. The Metaverse isn’t just about pixels and polygons; it’s about a whole new dimension of customer engagement and brand storytelling, potentially helping to generate new revenue streams. Embracing the Metaverse to build brand loyalty that transcends geographic borders and physical limitations is another channel to market.

The Ethics of Fashion’s Tech Takeover

Data privacy, intellectual property, and the potential for bias in AI-driven design are just some of the threads we must carefully build into our models. Brands should invest in robust data governance, responsible sourcing practices, and ethical AI development to ensure their brand is an innovative and socially responsible leader.

The takeaway?

The time to seize this opportunity is now; remember eBay and Amazon in the 90s. They were both early adopters of the web, and they are both major forces today. Both the Internet and AI are powerful engines of economic growth and innovation. While the Internet helped revolutionise information access and communications, AI promises to transform how we work, consume, and make decisions. Navigating their full potential and mitigating their potential downsides requires careful policy, education, and responsible development.

I’m convinced that in 2024, those c-suite first movers that truly harness AI’s potential across the entire value chain will shape the future of fashion and redefine its very essence. 2024 isn’t just about another year of fleeting trends. It’s about weaving your brand into the very fabric of the future. Embrace the technological threads, invest in strategic partnerships, and prepare to navigate the digital catwalk with confidence. The future of fashion is yours to stitch. Make it bold, make it sustainable, and make it yours.

Mark Harrop
As a technology advisor to the fashion industry, Mark has worked for more than four decades to help the world’s best known retailers, brands and manufacturers achieve efficiency savings across their entire supply chain through informed technology investments.

The post Fashion Technology In 2024: The Insider Perspective appeared first on WhichPLM.

Key Takeaways:

PLM solutions can help fashion businesses adopt eco-friendly practices and reduce their environmental impact. PLM offers a robust solution to track and report sustainability metrics, ensuring that fashion companies can demonstrate their commitment to sustainable practices.
By integrating sustainability criteria into the PLM process, businesses can align their product strategies with environmental goals and drive positive change.
Supply chain transparency is a critical aspect of sustainability in fashion, and PLM provides real-time data that helps build trust and accountability throughout the supply chain.
By leveraging PLM to drive sustainability initiatives, fashion companies can differentiate themselves from competitors and align with the values of their target audience.
Ultimately, PLM is a powerful tool that has the potential to reshape the fashion industry by empowering brands to navigate towards a more responsible future.

Environmental sustainability has become a top priority across industries in today’s rapidly changing world due to climate change. The fashion industry, in particular, faces increasing pressure to adopt eco-friendly practices and reduce its high environmental impact. As fashion businesses embrace the transformative potential of Product Lifecycle Management (PLM) solutions, also integrating sustainability solutions and practices into their operations is critical. This article explores the key drivers and benefits of combining PLM with sustainability initiatives in the fashion industry, many of which are helping businesses design and understand their impact on the environment in real-time. By harnessing the power of PLM to address ecological challenges, businesses can not only meet compliance requirements, but exceed them and pave the way for a more sustainable and responsible future.

PLM’s Role in Fashion’s Sustainable Future

PLM provides a centralised platform to manage and optimise sustainable design, product development, and manufacturing. Using PLM’s extensive data libraries can enable fashion brands to make eco-friendly choices, prioritise ethical sourcing, and improve supply chain transparency from design, from production to final delivery to the consumer. By integrating sustainability criteria into the PLM process, businesses can align their product strategies with environmental goals and drive positive change.

Meeting Sustainability Regulations and Global Goals

As environmental legislation and sustainability regulations become more stringent worldwide, PLM offers a robust solution to track and report sustainability metrics. By automating data collection and analysis, PLM streamlines the compliance process, ensuring that fashion companies can demonstrate their commitment to sustainable practices. Additionally, PLM provides a platform to show their alignment with global environmental and sustainability legislation, which only continues to increase, enabling businesses to contribute to broader sustainability initiatives.

Reducing Waste in the Fashion Industry

PLM facilitates circular economy practices by enabling brands to design products with recyclability in mind, optimising resource utilisation, and minimising product waste. Fashion companies can explore innovative and eco-friendly alternatives by integrating sustainable material platforms and digital assets into PLM. PLM also helps businesses reduce their environmental footprint (greenhouse gas emissions) and embrace a more sustainable production model through better material selection, processing, planning, and inventory management.

Supply Chain Transparency

Supply chain transparency is a critical aspect of sustainability in fashion. PLM provides real-time data linked to material design, development, processing, sourcing, manufacturing processes, and fair labour conditions, all of which help build trust and accountability throughout the supply chain. By making this information accessible to consumers through Digital Product Passports that contain the information on how a product has been designed, developed, and fractured (environmental and sustainability lifecycles) fashion brands can build consumer trust and loyalty. Data can be stored on QR codes, NFC chips, or other transparency (blockchain) initiatives connected into the product. . Transparent practices resonate with consumers seeking to support ethically conscious brands, ultimately driving market differentiation.

Enhancing Energy Efficiency and Reducing Carbon Footprint

PLM streamlines product development workflows, using DPC (Digital Product Creation), reducing the need for physical samples (materials or finished products) and minimising energy consumption via intelligent process selections. By optimising processes and reducing waste, PLM helps fashion companies achieve energy efficiency and contribute to carbon footprint reduction. Leveraging digital prototyping, virtual sampling, and DPC3D visualisation, PLM also accelerates design iterations downstream into DAM (Digital Asset Management), PIM (Product Information Management), and helping to automate the e-commerce process, thus reducing the end-to-end environmental impact of physical selection to the store or website.

Driving Innovation in Sustainable Material Research

PLM enables fashion companies to explore and implement sustainable material choices and material processing. PLM can be integrated into smart technologies that, together, can support innovative, sustainable options. By incorporating material platforms and digital asset management, PLM supports the discovery and adoption of eco-friendly alternatives.. Through collaborative efforts with suppliers and industry partners, fashion brands can stay at the forefront of sustainable material design and processing research to help drive positive change across the industry.

Collaboration for Sustainable Initiatives

Sustainability initiatives often require collaboration now with their Tier 1 – T3 partners, and we can expect this requirement to extend from Tier 1 – T6 partners over the coming years. PLM facilitates seamless communication and data sharing, ensuring better coordination of sustainable practices across the supply chain. By creating a shared platform for collaboration, PLM enables stakeholders to work together towards common sustainability objectives, enhancing the overall impact of their efforts across the entire value-chain.

Differentiating Fashion Brands in the Era of Sustainability

Brands that demonstrate a genuine commitment to environmental sustainability build loyalty among conscious consumers. By leveraging PLM to drive sustainability initiatives, fashion companies can differentiate themselves from competitors and align with the values of their target audience. By transparently communicating their sustainability efforts, fashion brands can engage consumers and inspire them to be a part of their sustainable journey, creating a loyal customer base that supports eco-conscious practices.

Conclusion:

By combining the capabilities of PLM with sustainable practices, fashion businesses can align their strategies with global sustainability goals, meet regulatory requirements, and cater to the growing demand for eco-conscious products. By embracing PLM as a catalyst for change, fashion companies can drive innovation, transparency, and accountability throughout the product lifecycle. Ultimately, PLM is a powerful tool that has the potential to reshape the fashion industry by empowering brands to navigate towards a more responsible future.

Before I end this article, I would like to leave you with this question: Is your fashion business ready to leverage PLM to drive environmental sustainability initiatives, embrace circular economy practices, and cater to the rising demand for eco-conscious products, ultimately reshaping the future of fashion, and are you ready to take on the challenge?

Before I end this article, I would like to leave you with this question: Is your fashion business ready to leverage PLM to drive environmental sustainability initiatives, embrace circular economy practices, and cater to the rising demand for eco-conscious products, ultimately reshaping the future of fashion, and are you ready to take on the challenge?

Mark Harrop

The post The Power of PLM to Drive Sustainability in Fashion appeared first on WhichPLM.

The footwear and apparel industry is rapidly adopting digital tools to gain or retain a
competitive edge. Digital Twins hold great potential for businesses looking to
simulate, test, analyze, and optimize their products and processes without relying on
physical prototypes.

Utilising Digital Twins in product design and development can accelerate the design
process, reduce the number of physical prototypes required, and digitally test
sustainable materials, processing methods, patterns, and styling details.

Incorporating Digital Twins into supply chain management offers unparalleled
visibility and control over processes, enabling proactive planning and decision-
making, reducing lead times, optimizing inventory planning, and minimizing
production disruptions.

Digital Twins can help businesses reduce waste, work with sustainable materials, and
improve efficiency and accuracy in processes that contribute to returns related to
quality, performance, and fit.

In a market where a high-octane combination of speed, efficiency, creativity, price, and
quality are essential to success, the footwear and apparel industry is rushing towards digital
transformation and digital tools to gain or retain their competitive edge. And no one area of
technology holds more potential across all those areas than Digital Twins – virtual replicas of
physical products, materials, or process that allow businesses to simulate, test, analyse, and
optimise without being held back by the need to work with physical prototypes and fabrics.

As more footwear and apparel business work to build out and refine their end-to-end
workflows – connecting processes that have traditionally been disconnected from one another
– the use of Digital Twins is likely to prove key to them to model digital products,
revolutionise their workflows, streamline styling and manufacturing operations, optimise
costs, boost efficiency, and even transform the downstream customer experience.
Obviously each potential end-to-end workflow is unique, but I want to look at five different,
common areas where employing a Digital Twin will have a measurable positive impact on
workflows and business models of all shapes and sizes.

Enhanced Product Design and Development

The traditional approach to product design and development in the apparel and footwear
industry is time-consuming and costly – with a heavy reliance on physical prototyping and
numerous sample iterations, each of which extends time to market.

By shifting to a workflow centred on Digital Twins in place of sequential samples, businesses
can create virtual replicas of their materials and products, enabling designers and developers
to visualise and test in the design and development stage – in real time.
Here, Digital Twins will not only accelerate the design process but also reduce the number of
physical prototypes that will be required to move from an initial concept to an approved
production sample. Businesses will also be able to work together in real time with their
manufacturing partners, using a Digital Twin that – as the name suggests – accurately
represents the physical product, allowing them to visualise any issues that can be linked back
to design requirements.
Working this way, design challenges can then be resolved in the virtual world before the
prototype stage, leading to significant time and cost savings that would have otherwise been
incurred during multiple, iterative rounds of sampling. And what’s more: designers can
digitally test different sustainable materials, processing methods, Last or Block models,
patterns, and styling details, ensuring that only the most on-trend, well-fitted, and
aesthetically appealing options proceed to physical production.

Optimised Supply Chain Management

Incorporating Digital Twins into supply chain management offers apparel and footwear
businesses unparalleled visibility and control over their processes. Manufacturers can use
Digital Twins to simulate the entire production line, identify machinery or processing issues,
resolve potential bottlenecks, optimise capacity throughput, and fine-tune resource allocation.

Real-time data and predictive analytics also enable proactive planning and decision-making,
reducing lead times, optimising inventory planning, and minimising production disruptions.
Additionally, Digital Twins can facilitate seamless collaboration between different
stakeholders in the supply chain, fostering stronger eco-system partnerships and greater
efficiency by allowing stakeholders across the value chain to communicate and collaborate
based on a shared, digital representation of a physical product.

Environmentally Sustainable Practices and Waste
Reduction

Sustainability is a vital concern for both sustainably minded consumers and businesses in the
apparel and footwear industry, with both parties seeking the same thing: visibility,
transparency, and rapid improvement to the environmental and ethical profile of finished
products. By digitally simulating the entire product lifecycle, from design to disposal,
companies can quickly identify areas where the teams can reduce waste, working with
materials that help to minimise the emissions and all-round environmental impact of the
product, and generally cut inefficiencies and inaccuracies that contribute to returns related to
quality, performance, and fit.

To make the kind of measurable difference that needs to be made in an accelerated
timeframe, Digital Twins will also be essential as a tool for educating designers on how to
understand and optimise their workflows to take account of processing impact effects. Digital
Twins will also have a role to play in ensuring efficient and sustainable manufacturing

processes, materials and products and even predicting product end-of-life scenarios for better
recycling and circular economy initiatives.
Crucially, working with an accurate Digital Twin is one of the best possible routes the
footwear and apparel industries have to help model, improve, and communicate the kind of
data that needs to be disclosed on a digital product passport (DPP) – which will be used in the
future by consumers and businesses alike.

Personalisation and Customer Experience

In today’s Mass Customisation and Personalisation era, customer experience is a crucial
differentiator for apparel and footwear businesses. Digital Twins enable companies to create
virtual avatars of individual customers (rather than traditional sizing demographics that
deliver just an average person’s fit!), allowing consumers to virtually try on different products
and styles – not only bringing the retail experience more confidently into the comfort of the
shoppers’ own homes, but more importantly providing an effective guarantee that the
garment or shoe fits their body, or foot shape and size.

This level of Mass Customisation and personalisation enhances customer engagement and
will dramatically help reduce the rate of product returns, which we’ve already established
are a prime contributor to waste.
At the same time, this approach will strengthen customer loyalty. Moreover, by leveraging
customer data and preferences, businesses can create bespoke designs and targeted marketing
campaigns catering to the unique tastes of their clientele.

Predictive Maintenance and After-Sales Support

Digital Twins also offer significant benefits in terms of maintenance and after-sales support.
Footwear businesses can use a Digital Twin of a shoe to monitor wear and tear, enabling
enterprises to offer proactive maintenance recommendations to customers. Digital Twins will
help enhance customer experience, satisfaction, and at the same time will help to prolong the
lifespan of the product. Additionally, for apparel manufacturers, Digital Twins can simulate
fabric degradation, assisting businesses to predict the durability and longevity of their
products and offer informed guidance to their consumers.

Conclusion

Integrating Digital Twins into the end-to-end workflows of apparel and footwear businesses
will help revolutionise the industry. The benefits are everywhere: from streamlining product
design and supply chain management to fostering sustainable material usage, process best
practices, and enhancing customer experience. Embracing this digital transformative
technology will allow businesses to remain agile, responsive to market demands, and poised
for long-term success in a rapidly evolving industry – as well as insulating brands, retailers,
and manufacturers against the uncertainty that continues to plague fashion.
As we evolve and mature workflows linked to DPC-3D, it makes perfect sense that we should
continue to evolve the Digital Twins workflow maturity both downstream (e-commerce,

consumers) and especially into the upstream (manufacturers, mills, and component suppliers)
workflows.

Mark Harrop

As a technology advisor to the fashion industry, Mark has worked for almost five decades to help the world’s best known retailers, brands and manufacturers achieve efficiency savings across their entire supply chain through informed technology investments.

The post Why Digital Twins Will Be Essential To Building End-to-End Workflows appeared first on WhichPLM.

Key Takeaways:
Proof of value is a robust evaluation process that measures the concrete benefits of implementing a PLM solution, providing data-driven evidence of how a future PLM solution will positively impact your business operations and pave the way for sustainable growth.
One of the primary benefits of proof of value lies in its ability to drive continuous improvements within your organisation by identifying bottlenecks and inefficiencies in current processes and streamlining workflow.
Proof of value provides insights into the various maturity levels of a PLM implementation, from manual processes to an automated measured and managed level with database-based operations and eventually to the advanced level with workflow automation and seamless supplier collaboration.
By evaluating the gains in productivity, reduced time-to-market, cost savings, and improved collaboration, businesses can gain a clear picture of the value derived from their PLM investment, which is a key component of proof of value.

In the dynamic world of Product Lifecycle Management (PLM), understanding the tangible return on investment is crucial. The concept of “proof of value” stands at the forefront of assessing the effectiveness of PLM implementations and other best-of-breed solutions. This article delves into the significance of proof of value and how it serves as a compass for unlocking the true potential of your PLM strategy.

In the realm of PLM, proof of value refers to a robust evaluation process that measures the concrete benefits of implementing a PLM solution. It serves as a means to determine how well the investment aligns with your business objectives and whether it truly propels you towards enhanced efficiency and productivity.

For fashion brands, retailers, wholesalers, and manufacturing value-chain partners operating under the Retail, Footwear & Apparel (RFA) umbrella, proof of value becomes an indispensable tool for justifying implementations to key stakeholders. It provides data-driven evidence of how a future PLM solution will positively impact your business operations and pave the way for sustainable growth.

Driving Continuous Improvements

One of the primary benefits of proof of value lies in its ability to drive continuous improvements within your organisation. By assessing the impact of PLM on your existing business processes (the ‘As-Is’ state) and envisioning the future (the ‘To-Be’ state) through process maturity improvements and seamless integration with best-of-breed digital solutions, you can unlock the potential for ongoing growth and optimisation. For instance, consider a fashion brand struggling with disparate data sources (Excel / Workbooks), and manual product tracking, or at best via emails. Through proof of value, the brand identifies the bottlenecks and inefficiencies in their current processes. By implementing PLM, they streamline their workflow, and automate data exchange, not only within the PLM backbone, but via open APIs to other critical solutions that combine support planning, creative design, development, and manufacturing. They also introduce real-time collaboration across the extended value chain, resulting in faster time-to-market, reduced errors, and improved product quality.

Moving Beyond Ad-Hoc Practices

Many businesses operate with ad-hoc methods, relying on spreadsheets, workbooks, emails, and file attachments to manage product information. With proof of value, you can transition away from such fragmented approaches and embrace structured, documented, and efficient business processes.

For example, a brand grappling with disconnected data silos and communication gaps implements PLM with a focus on proof of value. As a result, they centralise product data, establish a single source of truth, and enable teams to collaborate seamlessly. This transformation streamlines the design-to-production journey, reducing lead times and fostering better cross-functional communication.

Advancing Through Maturity Levels

Proof of value provides insights into the various maturity levels of a PLM implementation. Moving away from manual processes to an automated “measured and managed” level with database-based operations and critical path triggering, and eventually to the advanced level with workflow automation and seamless supplier collaboration.

Consider a manufacturer seeking to optimise its production processes. Through proof of value, they evaluate their current manual operations and identify areas for improvement. By adopting advanced PLM with workflow automation, they digitise their production planning, reduce manual errors, and optimise production schedules. As a result, they experience increased production efficiency and decreased time-to-market, helping to support their customer objectives.

Measuring Return On Investment

Understanding the return on investment (ROI) is a key component of proof of value. By evaluating the gains in productivity, reduced time-to-market, cost savings, and improved collaboration, you gain a clear picture of the value derived from your PLM investment.
For a global brand, retailer, or manufacturer the proof of value analysis shows substantial ROI through decreased markdowns, reduced stock-outs, and streamlined inventory management. With PLM’s help, they identify emerging trends, shorten their design cycles, and collaborate seamlessly with suppliers, resulting in higher revenue generation and improved profitability.

Cultivating a Culture of Success

Implementing PLM with a focus on proof of value fosters a culture of success within your organisation. It encourages a data-driven approach to decision-making, empowers teams to streamline processes, and inspires continuous innovation. A forward-thinking brand embraces proof of value as part of its PLM implementation journey. This approach instils a culture of innovation and efficiency, where employees are empowered to leverage PLM data for strategic decision-making. As a result, the brand stays agile, adapts quickly to market changes, and maintains a competitive edge.

Top Ten Things to Consider When Implementing a PLM Solution

As you embark on the journey of implementing a PLM solution for your fashion business, keep in mind the top ten considerations that will set the stage for success:

· Clearly Define Your Business Objectives: Begin by identifying your specific business goals and how a PLM solution aligns with them. Clearly defined objectives will guide the entire implementation process.

· Involve Key Stakeholders: Engage stakeholders from different departments, including design, product development, sourcing, and IT, to ensure all perspectives are considered in the PLM selection process.

· Assess Your Current Processes: Understand your ‘As-Is’ state of business processes and identify pain points that need to be addressed through PLM implementation.

· Plan for Process Maturity: Visualise the ‘To-Be’ state and the process maturity improvements you want to achieve through PLM. Set realistic milestones for measuring success.

· Look Beyond Ad-Hoc Methods: Recognise the limitations of ad-hoc practices and opt for a structured PLM approach to centralise data, enhance collaboration, and streamline workflows.

· Choose the Right PLM Vendor: Conduct thorough research and select a PLM vendor that not only meets your current needs but also aligns with your long-term growth strategy.

· Focus on User Adoption: Ensure your PLM solution is user-friendly and tailored to meet the needs of different user groups. Encourage user training and provide ongoing support to drive adoption.

· Integrate with Best-of-Breed Solutions: Consider how PLM will integrate with other software systems, such as CAD/CAM, Pantone, Adobe, and 3D, to create a seamless digital ecosystem.

· Embrace Supplier Collaboration: Facilitate effective collaboration with suppliers through PLM, fostering better communication, and accelerating time-to-market.

· Measure and Analyse ROI: Regularly assess the tangible returns on your PLM investment through proof of value and leverage the data to refine your PLM strategy for continuous improvement.

The concept of proof of value plays a pivotal role in validating the efficacy of your PLM strategy. By measuring tangible returns, driving continuous improvements, and nurturing a culture of success, you can harness the full potential of PLM and elevate your business to new heights. Embrace proof of value as your guiding light and pave the way to a successful and future-ready PLM implementation. By embracing these considerations and focusing on proof of value, your PLM implementation journey will pave the way for transformational growth and success in the competitive world of fashion and sewn product.

Mark Harrop

As a technology advisor to the fashion industry, Mark has worked for almost five decades to help the world’s best known retailers, brands and manufacturers achieve efficiency savings across their entire supply chain through informed technology investments.

The post Unveiling the Power of Proof of Value; Realising Tangible Returns appeared first on WhichPLM.

What started as a regular fireside chat with a good friend of mine, Kelly Vero from Nak3d, quickly spiralled from having no fixed agenda to being a lively debate about how digital product creation (DPC) and gaming – a space that Kelly has been involved in for 30+ years – are on a collision course.

We discussed what’s been driving these sectors to collaborate more openly and with greater focus than ever before. This was a high-energy discussion, sharing lots of ideas around the topics of DPC-3D and gaming – so much so that we agreed it would be interesting to capture and share our thoughts on what’s likely to happen when these two worlds – which The Interline first started writing about in 2020, in a two-part series – converge.

Kelly and I have been involved in our respective worlds of gaming and 3D fashion and apparel for long enough to have witnessed evolution and revolution, several times over. And we’ve also seen the acceleration of hardware and software solutions enable both sectors to deliver amazing high-fidelity ‘life-like’ results. In recent years, Kelly has worked much closer to the fashion sector, which is how we met, and she now oversees the technical workflow inside Nak3d – which is a games-first fashion content engine turning physical apparel to digital items with the push of a button. 

During our 2-hour long chat, we discussed many topics related to the world of fashion DPC-3D and gaming ecosystems that have been ever-evolving—and I’m sure we’ll pick up again in future articles; but for now, we started by exploring some of the main motivations for why fashion and gaming companies are starting to partner together, including the downstream and upstream use-cases that together make up what we call the digital twin.

Before we jump into the details, let’s share some of the differences between DPC-3D in the fashion and gaming sectors. If we roll the calendar back to circa 2001, [TC]2, an offshoot of AAMA (American Apparel Manufacturers Association) developed a body scanner that Fashion brands and retailers used to conduct Britain’s first national sizing survey called SIZE UK. The survey consisted of leading High Street brands and retailers that each invested around £80,000 (approximately) to conduct a national size survey. 

Then, in 2002, the body scanners were used to scan 10,000 Americans (SIZE USA) which was the first significant study of the size and shape of Americans since the original ASTM study during WWII. ASTM, formerly known as the American Society for Testing and Materials, is an international standards organisation that develops and publishes voluntary consensus technical standards for a wide range of materials, products, systems, and services. 

These surveys enabled fashion designers to use the survey data to develop avatars that resembled human body measurements related to their target consumers. In the late ’90s, the original DPC-3D Avatars in Fashion resembled square-pixelated-shaped robots more than humans! We’ve come a long way since those early days of DPC-3D and have now arrived at a point where meta-humans are almost indistinguishable from real human photographs. 

That massive leap in fidelity was the reason that Kelly and I went on to talk about the rise of Unreal Engine’s MetaHuman technology, which was developed initially for the gaming sectors and is based upon scans of real people’s faces with a vast range of facial features and skin complexions. 

The challenge for the fashion sector is that MetaHumans are based on a person’s facial rather than whole-body scans. With the announcement of the partnership between CLO Virtual Fashion and Epic Games (who own the Unreal Engine), perhaps we will start to hear of new developments that will help to combine body measurements from fashion’s DPC-3D ecosystems and gaming’s MetaHuman faces, coming together to deliver the full Virtual Twin?  

And it’s not just Kelly and I talking about these futures; here’s a direct quote from Simon Kim, CEO of CLO Virtual Fashion. “We strongly believe that digital garments will play a significant role in the future of digital entertainment and metaverse platforms,” he said, “We are building toward a future where we imagine the digitization of everything, the convergence of Fashion with entertainment and the metaverse. Our visions are aligned, and we are committed to building the future that we envision.” 

We hope both companies will address the issue of connecting body and facial scans to create a complete human virtual twin that reflects realism! 

But before we get too deep into the modern era, though, Kelly and I spent some time talking about the basics:

Mark: So, what is a games engine, Kelly? And why is it suddenly so important to the fashion industry?

Kelly: It’s a software development program or environment that we initially developed to create video games. Today, game engines are used for visualisation (as with the development of fashion digital twins), collaborations, and more. Unlike the fashion use-case, game engines focus on loads of things all at once: characters, mechanics and dynamics in games—such as sound and high definition art whilst handling millions of lines of code with ease and rendering to near perfect physical quality!

Mark: Yes, and the fashion industry is now playing catch up with rendering, not only in making the product itself look picture perfect but also in placing the garment or wearable item into a realistic background to support product marketing. 

Kelly: How has fashion technology aligned with the evolution of DPC-3D to use game engines? 

Mark: It’s clear to me that both the fashion and video games sectors are starting to recognise the potential to reach new audiences by tapping into each other’s customer bases but these industries have been comfortable doing their own thing up to this point. 

Kelly: Yes, but collaborations with fashion brands allow games companies to engage with individuals who may not be your traditional gamers but are interested in fashion and pop culture. 

As you can see, we agreed that both fashion and gaming solution platforms will eventually offer integrated ecosystems that share common assets, and file formats, enabling designers from both worlds to coexist and share digital seamlessly. These joint developments will enable fashion brands to licence virtual twins to gamers who can then choose their brand identity, worn on their avatars within the games they’re playing. 

This is something that even casual observes will have heard being promised already, so where is that vision actually up to?

Kelly: A couple of luxury brands have tried to minimal success, largely due to their narrowed campaign vision where most brands are working on a platform-by-platform or game-by-game relationship. The proliferation of fashion as games content means that the sharing of common assets means a faster route to market for assets. The fashion sector will be able to reach a more significant market audience, both in the physical and digital worlds. Isn’t that exciting?

Mark: It completely changes the way we think about fashion, moving it from the physical development process to effectively going digital first.

Kelly: Where games have always lived and gamers know what to expect!

The other key consideration in this coming-together of industries is the principle that fashion and gaming DPC-3D ecosystems must work together to help designers from both industries sectors (Fashion & Gaming) to produce life-like, accurately measured hi-fidelity digital fashion garments, footwear, and accessories that will be used seamlessly across both platform-ecosystems. Popular games like Fortnite have collaborated with renowned fashion brands such as Nike, Louis Vuitton, and Balenciaga to create exclusive in-game outfits and accessories, so I asked Kelly what she believed would come next:

Mark: How should fashion get started?

Kelly: Working in formats that work between platforms is a great first step because it’s easier to digitise brands and apparel when the shared language is a digital one.

AFSHA IRAGORRI, 3D FASHION SOLUTIONS.

Kelly: Absolutely! At Nak3d, that’s exactly what we’ve been doing since we started. My background in the games industry means that I can help to identify where fashion can thrive in the sector, and likewise, fashion brands help us to reach new marketplaces. 

Mark: Is the games industry open to working with the fashion industry?

From Unreal Engine and Unity to digital PLM systems and design tools, then, fashion collaborations are not just about making garments. They create opportunities for gaming companies to align their brand with well-established and influential fashion brands—this creates additional revenue streams for both parties. Phygital collaborations often generate hype and demand among both gamers and fashion enthusiasts, leading to increased sales and brand profitability. Fashion collaborations often generate hype and demand among both gamers and fashion enthusiasts, leading to increased sales and brand profitability as well as improving engagement and retention for players and consumers.

Fashion is the driving force in bridging the gap between the gaming world and mainstream popular culture where trends and influencer culture have a significant impact on consumer behaviour—from cosplay and esports, to virtual fashion shows and AR try-ons; technology is there for us to use rather than take our creativity away from us. It’s a tool, not a way of life… Well, not yet, anyway.

The post What’s Coming When Games And Fashion Converge? appeared first on WhichPLM.

What is SROI, and why do we need it?

Preparing For Transparency With A Flexible Value Chain, Backed By Data

Defining The ‘How’ And The ‘What’ Of SROI – Part 1

In this, the second part in our focus on defining what a Sustainability Return On Investment (SROI) looks like, we want to provide four distinct examples, each corresponding to a process taken from each of the 1 – 4 tiers of the supply chain. From a brand’s perspective, these examples correspond closely to real-world challenges and scenarios, and all are areas in which consumer and regulatory scrutiny is high, meaning that the potential return on making a measurable improvement is any of them is high.

First, though, some statistics for context. We all know the fashion industry generates colossal waste issues, contributing to an estimated 8% of global greenhouse gases. How do we tackle such a significant issue? The answer is ‘one piece at a time’. For example, let’s focus on the traditional sample-making process, which uses considerable resources to generate large quantities of discarded physical samples and is, by any definition, not sustainable.

Fashion Tech Week 2023 and Apparel Resource supporting statistics from the current traditional sample-making process that emphasises the opportunities to improve both sustainability and the bottom line;

• The fashion industry currently spends USD$ 6-8 billion on physical sample-making per year.
• Over 30% of materials are wasted during the seven stages of sample-making for a single piece of clothing.
• Most physical samples go directly to storage and ultimately to a landfill.
• If brands and factories created only one physical sample for every garment style currently manufactured, they would reduce the sample-making cost by USD$ 4.5-6 billion.

We’d love to tell you how to remove all physical samples and waste from ‘unselected’ prototype styles and deliver the USD$ 4.5-6 billion savings estimated above, but that is unrealistic. After all, designing, prototyping, and manufacturing remains an iterative, analogue process that is almost never “right first time”.

The fashion industry has already begun the sustainability improvement journey, and it’s just getting ‘serious’. However, this will be a decades-long journey if we ever complete and reach 100% sustainable practices.

The examples below are not a ‘silver bullet’, but merely practical examples of candidates for sustainability improvement initiatives. Each company must prepare their tools, map supply chain processes, collect associated primary data and prioritise the sustainability initiatives to execute for its business based on its own SROI assessment of each initiative.

Using IoT to help improve irrigation practices

If we investigate the water required to grow cotton, we find that one kilogram of conventional cotton requires 10K-20K litres of water to produce.
And if we list the top Global cotton producers during 2022, we see the massive volume of water used to grow these cotton crops.

That’s up to 420 billion litres, or 420 million m3 (cubic metres) of water used to grow cotton in those 8 countries. It’s also important to note that most cotton is grown in countries already facing water stress, making this resource utilisation especially unsustainable at both a humanitarian and environmental level.

Higher Cotton Yields with Less Water

Today, farmers are starting to implement computer vision and IoT technologies (Internet of Things) to help map their fields, measuring soil moisture via IoT devices to alert farmers to where water is needed to ensure healthy crops and at the same time, ensure they are not over-watering areas with the precious resource. These IoT devices supported by AI/ML (Artificial Intelligence & Machine Learning) help farmers to deliver precision-targeted watering. Different types of irrigation systems for cotton production; surface irrigation, sprinkler irrigation and drip irrigation systems. Each of these systems can utilise IoT devices to manage the water supply in the most efficient manner; examples would include watering during darkness to prevent the evaporation of water from the soil. The latest irrigation trend is a drip system where tubes run below the surface of a field, giving water directly to the crop’s root zone.

Initiatives such as the Better Cotton Stewardship have produced significant results showing that Better Cottom Farmers in four countries have used less water for the irrigation of cotton than Comparison Farmers, ranging from 6% less in Tajikistan to 13% less in India. For example, suppose we use the cost of a cubic metre (m3 / 1,000 litres / 1 kiloliter) of water in Maharashtra of $0.92. In that case, we find that a 13% potential saving of up to 16 million m3 of this precious resource applied across India would also save a cash value of USD$14.6M.

Digital dyeing of Thread and Yarn

Digital dyeing of thread and yarn supports on-demand production runs and sampling needs, producing significant sustainability benefits, with significantly reduced energy, 90% water reduction on average, and little or no waste materials, plus improved speed to market, the accuracy of colour matching, and quality.

• No MOQs (minimum order quantities) and material waste linked to DTM (dyed to matched) order requirements.

• JIT (Just-In-Time) on-demand production dyeing and sampling needs.
• Dramatic reduction in set-up time and energy resources linked to traditional dyeing methods.
• Greatly reduced stock and cost of materials using a standard greige thread/yarn.

If we consider sewn small garment orders and sampling, thread in an exact colour match is essential. Similar applies to yarns used in knitted products. Brands’ and retailers’ time constraints require the ‘nearest’ catalogue colour, but often, and colour matching isn’t good enough; the process completes several cycle iterations before final approval.

Issue

The key issue is matching the designers’ seasonal colours with a limited stock of thread/yarn catalogue colours. Several obstacles arise when a thread/yarn with a new DTM colour standard is required. The wet dye process requires a lead time of around 7-12 days to deliver the sample thread/yarns. On average, the thread MOQ is often 40 km (kilometres), compared to a sample requirement of 1-2kms. This results in the potential waste of 38kms of thread, or 95% of the order if the colourway is not selected.

The same issue applies to limited yarn colours in stock. Additionally, multiple sections in socks often require multiple yarn DTM colours. The yarn waste for one section of a sock ranges from 30% for production runs to 99% for sampling when a few grams of yarn are required, but MOQ is 1kg. The waste multiplies when several yarns in one sock style require a new colour standard. Like threads, the wet dye process for yarns requires a minimum lead time of around seven days or more, plus a shipping duration. For production, yarn(s) will be over-ordered as a contingency, leading to excess inventory.

Wet dyeing waste for 10 pairs of sample socks & 2,800 pairs of batch production

Process change

Adopting digital dyeing technology, using greige undyed threads/yarns to deliver DTM (Dyed-To- Matched) materials that, in turn, can be used to deliver On-Demand (PLM, Bill of Materials) orders, and ‘exacting’ sampling requirements. Greige stock threads can be dyed in any colour standard, with 1-2 kilometres of sample threads produced in 30 – 60 mins.

Small orders of garments, socks (around 3,000 pairs), bags, footwear, accessories, and related soft-sewn textiles or knitted products can be made available for shipping within 2-3 days.

Benefits

In addition to the listed improvements, a reputational enhancement is linked to the improved quality of service provided. Timelines for raw materials with new DTM colours are reduced by over 80% on average. The digitally dyed materials can be available within 30mins onsite. If shipping is needed, factories and knitters can reduce their lead times from 7-12 days to 2-4 days.

Using greige thread/yarn dramatically reduces a factory or knitter’s stock levels and waste by avoiding MOQs, saving more than six thread cones per colour. Avoiding the wet dyeing process enables a >90% reduction in water usage and effluent creation, and a >90% reduction in Co2 equivalent greenhouse gas emissions.

We have been made aware of On-demand production and sampling lead times reduced by 30-70%. Digitally dyed sample yarns can be available within 1-3 days compared to a minimum of 7 days for wet dye processing, excluding shipping. The digital dyeing process enables a >90% reduction in water usage and effluent creation and a >50% reduction in Co2 emissions.

You can learn more about digital thread and yarn dyeing here.

Traditional Fabric Printing vs Digital Fabric Printing

When designing printed fabrics, there are constraints when considering the traditional fabric printing process. The root of these issues is the cost and time required to create the different screens for multiple colour separations. Cost may constrain the designer to a maximum of 3 or 4 colours per print, and there will be an average 3-month lead time for bulk printed material.

Wet dyeing issues and efficiency limitations

The traditional printing process ‘efficiency threshold’ is around 1000 units, with the efficiency of energy and water use improving as volumes increase. Above 5000 units per print run, the waste produced per item is dramatically reduced. However, as the average industry order size decreases, the number of print runs above 1000 units, never mind 5000 units, per run is lowering.

When balancing constraints vs efficiency in traditional wet-dye printing, the ‘efficiency’ side of the ledger doesn’t prevail until there are large unit numbers per print run. Therefore, a more efficient and cost-effective alternative to traditional printing is needed for small production orders and all print sampling.

Companies are developing compelling benefits cases for digital printing. As the Direct To Garment (DTG) and Direct To Roll (DTR) install base continues to increase, and the technology is road tested and proven to be stable, there are more use cases for Print On Demand developing in traditional retail. Several factors are driving this interest.

1. Speed to market – The ability to design a new print and make it ready for sale in days rather than weeks or months is a real game changer.
2. Low MOQs – Removing the restrictions of MOQs makes the ordering process a lot easier.
3. Sustainability – Reducing waste by only printing to fulfil the actual order, resulting in fewer products in landfills.
4. Reducing water usage – Direct To Textile (DTT) is a waterless process, removing the gallons of water it takes to prep a screen for printing.
5. Reduced carbon footprint – Producing and shipping from the closest point to order delivery.
6. Risk-averse – Removing risk from the concept and design process. With DTG, colour is only limited by RGB. You can design with total freedom and are not constrained by the number of colours your manufacturer can produce.
7. Test new markets – Try a new market with little or no risk, which may not be your core customer.
8. Reduced stock holding – Running your business 100% on demand is now possible by taking advantage of the deep plain stock available and the ‘JIT‘ (Just in Time) principle.

Yes, digital printing machines, on the face of it, appear expensive. Still, plenty of digital printing service bureaux offer this capability, and when you measure the ‘true benefits,’ you might find that the value of the machine outweighs the cost.

Lessons learned from mills’ efforts to reduce greenhouse gases

Like every partner business operating in the fashion supply chain, mills work hard to achieve sustainability goals. Some have reduced their energy resources, implemented water purification projects, and installed solar panels, spending six-figure sums that have helped transition 50-60% of their electricity to renewables, linked to SROI paybacks estimated in 3-5 years.

However, it has been discovered that projects of this nature to improve sustainability for the high energy processes required by mills and wet dye processes have limited impact on GHG emissions, many only resulting in single-digit reductions.

For these processes, a large element of emissions is derived from the generation of heat. To achieve double-digit emission reductions, mills will need to focus on reducing heat wastage, such as alternative energy generation from alternative fuel sources and efficient heating systems, with the best energy recycling and repurposing capabilities and IoT controls to ensure consistent energy usage.

This demonstrates the holistic approach that must be taken to find the best solution for the specific process to enable management and mitigation of ecological impact.

Design-By-Impact – is a new software tool that allows brand or retail designers to use process data to model a garment assembled with the materials and different manufacturing partners. In this scenario, several T1 factories may each use different types of machinery, or electricity consumption will vary and be charged at another value based on the country’s electricity (wattage) charges. Then you might want to consider the factory efficiency levels, fair labour rates, not to mention the type of transport (Air vs Sea) and miles/kilometres distance from the factory to the brand’s warehouse and ultimately down to the store location(s).

Design-to-impact tools will allow designers and developers to go deeper; for example, Fully Factored (responsible for obtaining and testing of materials, components & trims) vs CMT (cut, make & trim), ultimately each will have different costs of resources and transportation that in turn will impact the overall sustainability scores.

The power of process breakdown combined with primary data

As we have discussed, one of the most significant improvements in environmental impact and growth to the bottom line is understanding the effects of all processes.

Let’s consider the sewing operations in a CMT factory. Each sewing operation involves multiple sewing machine types, each with different sewing motors and different apps/wattage. This adds to potentially significant energy usage variations across factories. This variation has an impact on CO2e Kg and cost.

For example, if we assume the wattage of all machines used to manufacture a garment in 2 factories is the same, and we used the published average $/kWh for businesses in June 2022, we see variations between neighbouring countries.

• China is ~22% more expensive than Indonesia or Vietnam.
• Pakistan is 25% more expensive than India and 45% more costly than Bangladesh.
• India is 16% more expensive than Bangladesh.
• Mexico is 42% more expensive than the USA.
• Nicaragua is 14% more expensive than Guatemala.
• Honduras is 29% more expensive than Nicaragua.

Additionally, if we considered textile mills in Europe, using the same published average $/kWh for businesses in June 2022;
• Italy is 178% more expensive than Spain.

These examples are a tiny element of the enormous quantity of processes and primary data that could be leveraged to provide our teams in the digital value chain with options for more sustainable and profitable products through informed decisions.

Design-By-Impact tools

The fashion industry needs the tools to capture the primary data and provide a simple and effective user interface for your team to compare processes and evaluate options.

The example below is a GHG Design-By-Impact tool that compares GHG impact for two supply chains. The data example applies to a suit with three linings, using the same fabric supplier in Italy, two alternative CMT factories (China and Romania), separate packaging, and Gate to Site (G-t-S) to the same warehouse in New Jersey via sea freight.

The CO2e Kg is calculated using Primary data collected from all associated supply chain processes and is summarised for each of the Tiers 1-4 plus Packaging (PCK), the Cumulative to Gate (C-t-G) volume for all the Tiers and Packaging, Gate to Site (G-t-S) shipping, and the total for the delivered product.

Comparison for each of these processing groups is provided, with insights into the environmental differences between the two variations of the supply chain. It becomes easy to identify the ecological benefits between 2 options, whether they are different locations with the same processes, different styling on the same product, or you are identifying improvements between processes. The team would combine this GHG data with other primary data, such as cost, fair wage, timescales and other ESG data, to make the final informed decision.

Design-By-Impact provides the team with the environmental ‘facts’ of each option, or equally, to enable your project team to assess, prioritise and validate environment process improvement in a phased approach. One of many tools that captures an element of primary data and provides insights to help make an informed decision. There is an enormous opportunity to combine all these insights to provide holistic insights to power the fashion industry into a new era of sustainability.

Conclusion

An enormous depth of information is embedded in the fashion industry supply chains. The work to extract and leverage this primary data is vast and is not something one company can do independently.
Specialist companies are leading the science-based collection and analysis of trusted primary data. The fashion industry must act to work together to agree on all the variations of primary data and create solutions to contribute to the holistic view of selected supply chains.
The good news is that solutions can be leveraged to enable compliance with the imminent legalisation. In addition, the same tools can be used to improve profits and substantiate sustainability credentials. However, the clock is ticking, and companies need to make a move before they are forced to do so.

Authors: Mark Harrop & Chris Jones

The post Defining SROI: Examples, Part 2 appeared first on WhichPLM.

Although fashion needs more time to comply with current (let alone future) legislation, there is always time to begin and profit from a sustainability-related project. This is the third article in our series on Sustainability Return on Investment (SROI); previously, in article one, we discussed the drivers for SROI. In article two, we discussed the priorities for SROI. Now we get deeper into the practicalities of obtaining a return from investing in sustainability.

Due to the depth of the subject matter, we decided to split this article into two parts. Part 1 considers the changes required for environmental improvements to be achieved and sustained. And without giving away all our conclusions up-front, although profound change is needed, a phased approach can indeed generate SROI. In Part 2 – coming soon – we’ll provide some examples of measurable sustainability improvements in each supply chain Tier, 1 to 4, with results for brands and their partners.

Understanding resources and processes

To understand the impact of implementing sustainable business practices, we must first understand the origin of the resources used in product creation, and how we can select these processes to help deliver the most sustainable products to retail channels.

As discussed over the series of articles, methods and related techniques for the entire supply chain must be mapped for at least 50% of your supply chain partners to comply with the New York State Fashion Act. Still, it’s reasonable to assume that, eventually, fashion brands will need to map all supply chain processes to operate within the US, EU, and UK markets.

To put it another way, right now building that understanding of process, operation, and resource utilisation is a smart pragmatic step – but very soon it will be a mandatory one.

Leveraging process knowledge

To achieve that process and resource mapping, external and internal teams will need to work together to map each process, along with measurements captured for materials and resources. But once that mapping is done, there are many ways that designers, developers, and manufacturing teams can leverage the resulting data.

One of the most significant benefits will be educating designers and developers on depth of manufacturing methods across all tiers to enable teams to design and develop products transparently and sustainably. The traditional route of storyboards, sketches, and styling details on their own, by comparison, doesn’t answer whether this season’s collection has a lower environmental impact than last season, or which of the improved manufacturing processes will achieve the desired goals.

The industry needs to bring change at the design & development stage, designing with a capital ‘S‘ engrained in people’s minds, and with the support of benchmarks that can be quantified as they evolve from one collection to the next. In addition to the sketches and styling details, the design brief should include material options with the lowest environmental impact. Styling details and manufacturing methods should be related to processes and techniques, to identify the ecological impact measurements.

Using the approach of ‘less is more’, there should be conscious decisions taken on bringing to market fewer colours, producing smaller volumes, and capturing and communicating transparent information on materials & processes. Armed with the right data, these decisions can collectively deliver style-level profitably at the same time as enabling a simple focus on environmental impact at a detail level, but one that also rolls up to a significant effect across the collection. Products should be ‘designed to be both sustainable and profitable’.

One of the obstacles to this approach has always been the different teams’ ‘right brain vs left brain’ characteristics. Today’s ‘right brain’ creative designers need to gain the manufacturing knowledge of the ‘left brain’ team within the factories and mills (as well as wherever pattern-making expertise sits). Technical designers or developers are often the bridge to this knowledge. When manufacturing was in our home countries, it was easy to connect with the local factory to understand any specifics of the manufacturing process. However, over the last 30+ years, this technological know-how has moved away from the western world. Over recent decades, know-how has dramatically reduced in brands and retailers operating outside of Asia – a technical knowledge ‘brain drain’.

To deliver on building the required understanding of what resources and processes it actually takes to bring a product to market, we need to improve fashion’s shared understanding of the mechanics of sourcing and production. To enable designers, developers, and manufacturers to apply a design approach with more significant insights into the sustainability and profitability of the proposed products, the industry must counter this knowledge drain. One of the ways to fill this gap is via mapping and sharing processes and primary data collected across the supply chain and ‘recirculated’ across the entire digital value chain to allow brands and retailers to make those sustainability choices accurately and simply at the earliest point in the product lifecycle. The result of this work will enable supply chain partners to find and create sustainable options for new styles at the earliest opportunity, with dynamic data growing constantly.

Access to near-time science-based sustainability and economic ‘data insights’ of all product processing options is the only realistic way to leverage the fashion industry’s environmental creativity.

Investment in the supply chain

Forward-thinking brands, retailers, manufacturers, and supply chain partners are already investing in deeper supply chain data ventures to create the foundations for a new level of mutual understanding. These investments will fund the ‘global’ essentials for compliance and end-to-end visibility, such as the tools, science-based methods, standards, certifications, and primary data required to measure individual processes’ environmental impact and fund the technology-based solutions to support streamlined and more sustainable practices.

This kind of investment might seem prohibitive for some organisations, but the fact remains that fashion, at a whole-industry level, must stop theorising and move to deliver the actual transformation from the analogue supply chain to a digital value chain. This delivery must start with the essential tools to capture and analyse processes and trusted primary data.

Considering all business processes

As with any transformation, we must map and measure the current situation and the improved change(s) we wish to implement. We are enabling the creation of a practical and realistic plan to execute, including accurate measurement and validation of the successful change’s environmental, social, and economic impact.

The list of processes and activities for the entire lifecycle of a collection of products delivered over the season is long and complex. Not only direct sampling or manufacturing processes impact the environment. Methods considered should include brand & retailing processes over the season. Planning orders, store drops, and replenishment is essential; for example, we all know air freight is expensive economically and environmentally, but how much and which are the best options to choose? Using DEFRA UK conversion factors to calculate the CO2e Kg impact for 1Kg of product shipped from Hong Kong / Yantian to London / Felixstowe, the air freight CO2e Kg impact is 9.78, and the sea freight CO2e Kg impact is 0.10; shipping products by air freight has 9,680% greater impact on the environment than sea freight!

It’s important to note that these are estimated values based on the Defra methodology. The actual emissions may vary depending on several factors, such as the type of cargo, carrier efficiency, and other operational factors. Other bodies provide conversion factors to calculate CO2e Kg, so if we take the example of shipping from Hong Kong / Yantian to New Jersey, the IATA (International Air Transport Association) estimates the air freight impact to be ~3.0 CO2e Kg. The Clean Cargo Working Group provides a standardised methodology for calculating CO2 emissions from ocean shipping and calculates the sea freight impact to be ~0.2 CO2e Kg. Whilst a smaller difference than the previous example, air freight has a 1,400% greater impact than sea freight.

Managing the processes that lead to change benefits

As the saying goes, ‘Rome wasn’t built in a day’! There are many processes and activities to map and measure and many options to consider when improving sustainability. The volume of change and effort required can appear overwhelming, so it’s important to know that we don’t need to change all processes simultaneously with a ‘big bang’ approach. Instead, these changes should be phased and linked to a new digital value chain, according to the priority of impact on the business, its employees, environment, and consumers/society as calculated by SROI.

Process decomposition modelling methods allow you to maintain a high-level view of your macro processes and enable drill down to those processes and measurements deemed as a high priority. New modules within PLM, such as the Bill of Process (BOP), are essential to helping designers, developers, and manufacturing engineers not only manage processes and measure their sustainable practices in combination with the Bill of Materials (BOM) and extended to the Bill of Labour (BOL), but also to provide a manageable method for implementation in phases. These combined modules will help to enable process measurement and analysis of primary data at a pace.

Drill down to the details.

So far, we have discussed the high-level processes, but there is an enormous quantity of detail and many deeper sub-processes and tasks that operate below this level. There are and will be MILLIONS of options to define and measure.

To illustrate the point, let’s estimate a typical supply chain.

Let’s ‘start at the top and consider ‘macro processes’, such as ‘commercialising a product’. There are many milestones, processes, and tasks within each macro function, and then many levels of what we would call sub-processes before we complete individual activities.

It’s easy to see how the number of processes within the business and across the supply chain partners will ‘explode’ exponentially.

Businesses must map their high-level process structure carefully and methodically drill down through macro-processes, and related sub-processes, to the individual tasks. The management of this type of project can be streamlined, with supporting tools and methods to document activities, measure and analyse the millions of data points required to assess each task’s environmental, societal, and economic impact.

There are tens of millions of data points, but don’t panic! Technology providers are already capturing vast amounts of design, development, manufacturing, and shipping data. The measurable ‘benefits’ happen when we bring these data points together!

Measurement of environmental impact

Whether you are measuring existing processes for compliance purposes or measuring SROI for proposed initiatives to support improved sustainability, how do you generate accurate and consistent science-based measurements for comparison across different partners, product categories, countries, and regions?

Measurement should enable the assessment of the impact of each activity and specific variations rather than using generic ‘template’ values whilst being able to roll up the appropriate level, whether process, material, product category, partner, or country. The potential improvements could include reducing process duration or quantity of materials or resource effort. Work study solutions can be used to calculate the labour effort (Standard Minute Values) linked to the design and development options. However, how do you assess the reduction of resources such as energy and water and their environmental impact? Businesses will need specialist third-party assistance to capture primary data details for each step of our ‘Bill of Process’, using a science-based, standardised measurement for selected processes, materials, machine types, energy costs, etc., which we can then use to compare and calculate the SROI for proposed sustainability improvements and enable validation once implemented.

Conclusion

An enormous depth of information is located and used in fashion supply chains, and the work to extract and leverage that data is vast. Obtaining it will take time and will be managed in phases with careful control, and many companies and tools can assist.

In part 2 of this article, we’ll share some examples of process improvements that are candidates for sustainability initiatives, and that can provide positive SROI, quantifying sustainability improvements as well as measuring the benefit to the bottom line.

The post DEFINING THE ‘HOW’ AND THE ‘WHAT’ OF SROI – PART 1 appeared first on WhichPLM.

It’s clear that brands and retailers that operate in the US, EU, and UK must define sustainability improvement initiatives – a recognised scientific-based method of measurement across the entire supply chain – and will be required to publish timelines with regular, or even auditable evidence of reduced social and environmental impact to continue to compete in these markets.

A key element overlooked is the vast range of process types and associated data managed by the Tier 1 to 6 manufacturers, raw materials, and chemical suppliers. The logistics for brands and retailers to directly gather this data will be extremely difficult, which is leading to new organisations, with software and data acquisition methodologies to capture this data on behalf of the brands and retailers. In reality, many brands and retailers currently do not know their Tier 3 – 6 supply chain partners, with some struggling to identify Tier 2 partners.

Therefore, the majority of brands and retailers will initially focus on Tier 1 – 4 partners, with only the largest, forward-thinking organisations driving down mapping and traceability to Tier 5 & 6 partners.

Although it’s early days, work is already underway collecting primary data from partners across Tiers 1, 2, 3, and 4, and over time we expect brands and retailers to go deeper into their value-chains, reaching Tiers 5 and 6. We would also expect to see this data being gathered dynamically via IoT devices connected to machinery, raw materials (smart labels), finished products, various software solutions, APIs to associated partners, and suppliers that will participate in the collection, analysis, and publishing of these primary datasets.

This is going to have a large impact on Tier 1 to 4 partners; to ensure sustainability measurement, brands and retailers could not work with a manufacturer and associated supply chain partners that are not participating in the collection, analysis, and publishing of trusted primary datasets.

In this article, we take a deeper dive into the drivers behind the need to improve and measure sustainability, identify the priorities when defining sustainability initiatives, and the SROI that is going to be required to help justify the investment.

What are the drivers?

Generating growth via new sales, incremental revenue generation, cost saving, and profitability are key drivers for almost every company. However, we’ll first focus on some of the coming legislation that will enforce companies, and their supply chains, to implement science-based sustainable process improvements, measurement, and publication in the US, EU, and UK.

Drivers in the US:

New York state bill, the Fashion Act, will affect all companies, and their supply chain processes, associated with the operations generating over $100M in annual revenues. This covers all the usual global brands.

The proposed bill has 3 main elements;

1. Binding targets: targets defined by the governing body, and must be published by each qualifying company
2. Complete supply chain mapping: full mapping of the supply chain associated with operations in New York state, with the objective of traceability of products. The initial requirement is: “a minimum of 50% of suppliers by volume across all tiers of production shall be mapped”.
3. Social and Environmental impact disclosure: regular publication and comparison to binding targets which will be assessed by an objective and independent body

For those brands and retailers that are not compliant, the punishment is proposed as 2% of annual revenues.

The key aspect of this bill is that it will not be self-governed by the fashion industry, so it’s not going to be a matter of brands and retailers marking their own homework. There have been many self-governed initiatives – just one of the many reasons why an industry-wide standard of data gathering and systems collaboration has not been achieved to date. The independent assessment and enforcement will provide a greater probability of success.

All standards for compliance with the bill will be defined by the legislature, which is a significant change from past industry-managed initiatives.

One thing that we can be assured of, is that those brands and retailers that wish to continue to operate within New York state, will need to develop new processes and methodologies to scientifically capture the required data. Regarding full traceability of their supply chains, are global brands really going to manage the supply chain differently in New York versus London or Paris? Once a brand or retailer decides to comply with delivering on the required data points, then they will most likely do it once and on behalf of all global requirements. The only exception to this rule will be for those that operate in a single state, or country.

Publication of social and environmental impacts aligned to the legislature’s binding targets is a game changer; the brand will not be able to pick and choose targets. Therefore, the acquisition of science-based standardised data from all Tier 1 – 4 companies in the supply chain is essential. Brands and retailers do not have the capability to acquire this data directly, so will need to work closely with each of their third-party partners, to ensure that the data and methods of capture are acceptable to the legislatures, and become the de facto standard. Initially, we would expect that data models will be built as part of vendor surveys and questionnaires, using primary (first-hand) data, completed by each of the partners, and shared with each of the brands and retailers. In the future, we would expect that this data would become dynamic, meaning that it could be collected in real-time from many of the IoT devices connected to machines and solutions that are used within the connected value chain.

Smaller brands and retailers operating outside New York may think they don’t need to comply with legislation in the near future. However, this bill is being assessed at the Federal level in the US, so similar requirements will eventually be applied nationally, and impact a significantly wider group of brands and retailers, that not only operate within the USA but also sell internationally.

In addition, California Garment Worker Protection has recently announced that it will ban the use of piecework, and will revert to hourly minimum wage. It’s not just a ‘stick’ approach, but rather that the US also plans to provide a ‘carrot’. There is the aim to create an American apparel industry with a 30% tax credit incentive for brands, retailers, and manufacturers.

Drivers in the EU:

The E.U. Green Deal was approved in 2020 as a set of proposals to improve policies in line with greenhouse gas emission targets. One of these is the Sustainable Products Initiative (SPI), a new regulation to improve E.U. products’ circularity, energy performance, and other environmental sustainability aspects published in March 2022. The SPI was set to have a public consultation on priority product categories in 2022, but this has been delayed. Ultimately, the SPI is set to affect brands starting 2024, however, brands will need to take action in 2023 to avoid penalties.

The Digital Product Passport (DPP) initiative is part of the Ecodesign for Sustainable Products Regulation (ESPR) and one of the key actions under the EU’s Circular Economy Action Plan (CEAP).

The DPP is key to the EU’s transition to a circular economy and will provide information about products’ environmental sustainability. It aims to improve traceability and transparency along the entire value chain of a product and to improve the management and sharing of product-related data which are critical to ensuring their sustainable use, prolonged life, and circularity.

The DPP will help consumers and businesses make informed choices when purchasing products, and should also help public authorities to better perform checks and controls.

Therefore, brands and retailers with operations in the EU are in a similar position to their counterparts operating in the US and need to be prepared for 100% transparency.

It’s time to transform fashion’s traditional analogue supply chains into modern data-driven value chains!

Commentators expect to process and data to be the key focus in 2023, to enable brands and retailers to collect and offer data transparently.

Some companies are already transforming their value chains.

There has been reporting of human rights, and other social and environmental violations, resulting in a reduction of production orders, in areas such as Xinjiang. However, some brands were already taking action, and shifting their production. These brands have been working with supply chain partners to improve sustainable processes in each of their facilities, but have also been working with those partners to create a flexible and adaptable digital value chain that can mitigate risk and provide sustainable options in times of regional crisis. When a crisis hits the supply in a specific region, the supply can be switched to another region, whilst still using the same verified and sustainable processes.

This flexible and adaptable digital value chain can also enable a greater balance between long-distance sourcing and near-proximity sourcing. Core items can be sourced at distance based on longer lead times with optimised cost and environmental impact, whilst time-dependent products can be sourced closer to the market for a faster response without high environmental cost.

What does this mean for the prioritisation of sustainability initiatives?

Priority #1 for most companies is cost-saving and/or additional revenue generation. However, there is a commonality between your company’s financial objectives and the imminent legislation.

These are:

1. Detailed mapping of your supply chain partners (all Tier levels), and their processes
2. Capture and analysis of primary data generated by each of the processes, raw materials, human resources, energy, waste, water, and created products.

Detailed mapping of supply chain processes is essential to both understanding and defining the changes required to implement more sustainable business practices. One way to measure the greenhouse gas impact of fashion is by using lifecycle assessment (LCA), which is a technique used to evaluate the environmental impact of a product or service throughout its entire lifecycle, from raw material extraction to disposal. LCAs can be used to assess the greenhouse gas emissions associated with different stages and processes of the fashion industry, such as the production of raw materials, manufacturing, transportation, and end-of-life disposal of clothing. the current process must be mapped to identify the inefficiencies and enable the definition of a new process that improves sustainability. Comparison of the existing and proposed processes will enable the estimation of cost-saving and revenue generation. Crucially, the new legislation discussed above also requires the publication of the mapping of processes across all tiers of supply chain partners for compliance, and this is a prerequisite for traceability throughout the supply chain.

This exercise is not a small effort, and again, is not possible for a brand or retailer to achieve alone. Assistance from third-party expertise and strong partnership with all tiers in the supply chain is going to be essential to satisfy the initial process mapping, and ongoing verification of process for every new facility or facilitator added to the supply chain in the future. However, once this mapping is completed, significant improvements will be more easily defined, planned, and executed.

As stated already, step one will be to work with your partners to define and gather primary data. More forward-thinking businesses will consider real-time data collection, that can be mapped and measured for improvements in real-time. These methods will also enable over time Track & Trace, linked to the lifecycle of raw materials to the finished products.

More information on the challenges and opportunities for aligning the Bill of Process to the Bill of Materials and the Bill of Labour can be read here.

The capture of data generated by these processes, raw materials, and resultant products is a prerequisite to understanding the impact of current processes and compliance with targets. A measure of environmental and social impact is already provided by many brands and third-parties. However, as previously discussed, these current measures are self-governed within the fashion industry, which leads to the use of various measures. Worse, some measures often use generic secondary data in template form which has raised concerns about flawed calculations and resultant measurements. Imminent legislation calls for objective and standardised measurement, and in order to deliver on the greater accuracy required to satisfy the proposed legislation, more accurate primary data is required from each of the brand’s or retailer’s Tier 1 to 4 supply chain partners. This primary data includes the details of their machinery, processing capabilities, throughputs, resources used, etc. Unfortunately, this is something that most brands and retailers will find very difficult to collect.

The good news is that there are many new organisations that have been formed to assist brands and retailers in collecting this primary data. Examples include management of industry-standard terminology, and capturing and processing the operation-specific and traceable data to support the accurate calculation of the environmental and social impact of processes. There are many other organisations in this space, that are now managing millions of data points, and providing brands and retailers with the capability to collect this data from each of their Tier 1 to 4 supply chain partners. This data is required to enable science-based calculations relating to the processes, that in turn will help provide the objective and standardised impact measurement required for both an independent assessment of sustainability, and the real-time data insights that the brands need to inform their sustainability choices.

These two prerequisites are the essential ‘foundation’ for creating the SROI. More reading on how processes and data are essential in combination with existing technology, such as PLM, can be found here.

The first steps in documenting a potential SROI

How do you prioritise your list of sustainable initiatives? The general advice, given the short timescale, is that brands and retailers should understand the processes across all tiers of their supply chain in detail, and focus on providing transparency of those processes, whilst applying small prioritised changes very thoroughly with clear and accurate goals.

As mentioned, the Fashion Act requires that 50% of suppliers across all tiers of the supply chain must have their processes mapped. The EU Sustainable Products Initiative proposes full mapping and traceability across the entire supply chain. The ‘AS-IS’ process mapping will be required for this initial compliance, but then working towards implementation of more sustainable processes, and transformation to a digital value chain, will require re-engineering of ‘TO-BE’ process mapping. This effort will require working closely with all your supply chain partners. One of the considerations for performing this mapping is that not all brands and retailers currently know who their supply chain partners are beyond Tier 1, or Tier 2 at best.

Next, you must make logical assumptions on the efficiencies of the TO-BE process, but it’s essential that the calculations made from those assumptions must be based on how you will measure the new process. For example, if you are using secondary data (historic templates), will that data give you the accuracy to correctly measure the sustainability improvements either to confirm SROI, or enable compliance with the imminent legislation?

The fashion industry is running out of time, but it’s never too late to start. By starting now, brands, retailers, and their supply chain partners will be able to get ahead of legislation, avoid related penalties, and turn a problem into an opportunity!

In our next article, we’ll examine some example processes where more sustainable practices could be implemented, and examine the potential benefits for the SROI.

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