How Data-Driven Trend Forecasting Is Revolutionizing The Fashion Industry

While there are a multitude of challenges in collection planning, the main ones can be chalked up to inventory management and cross-team collaboration. 

Inventory management is an umbrella term for a list of other challenges: product assortment, under- and overstock, sustainability issues, consumer targeting, and demand planning, to name a few. Without accurate (and relevant) data, it becomes difficult for brands to plan accordingly. When a collection doesn’t include desirable trends and products – and in the right quantities – inventory goes unpurchased, leading to overstock and waste. When a brand lacks insights into their consumers, marketing teams can easily miss their target and sidestep opportunities to increase sell-through and create a connection with their respective consumer base. Challenges such as these require data to combat them: According to a 2020 report from McKinsey, fashion brands and retailers “who leverage analytics are outperforming their competition by 68 percent.”

Cross-team collaboration is another challenge faced by many brands and retailers. Oftentimes, creative and analytical teams don’t speak the same language or work in the same way. This can lead to friction between design and merchandising teams, for instance, due to misunderstanding one another’s processes. Useful data often remains in silos when teams don’t openly communicate with one another, slowing workflows and complicating decision-making. 

In the past, fashion brands and retailers have relied on multiple, decentralized sources to plan their collections. Designer opinions, past sales data, competitors’ collections, social listening, and more are just a few of the ways brands historically informed decisions on upcoming collections. But today’s industry landscape requires more centralization and quantitative precision than these methods. Why? Trends come and go more quickly than before; consumers demand more transparency and accountability from brands; social media is changing how brands and consumers interact; and digitalization has changed the landscape of the industry entirely.

Evidently, the fashion industry is no longer how it once was. Designer opinions, while necessary, need also to be backed by quantitative insights given the rapidity and unpredictability of trends – the pandemic inciting a sudden boost in loungewear is the perfect example. Past sales data is simply unreliable, because what sells well one year may not do so the following year – descriptive analytics cannot stand alone. Competitors’ collections remain an important point of comparison between fashion brands, but consumers increasingly seek out singularity and pioneering. Social listening is useful notably from a marketing perspective, but it can be improved with quantitative insights, too.

What can be done to plan collections better?

Heuritech works with brands in the luxury, sportswear, and fashion industries, including Louis Vuitton, Havainas, and Moncler. Simply put, we offer our clients trend forecasting and product analytics for better collection planning. Heuritech uses advanced artificial intelligence (AI) to translate real-world images shared on social media into meaningful insights, empowering fashion brands and retailers to forecast demand and trends more accurately, produce more sustainably, and achieve competitive advantage. Heuritech’s raison d’être is indeed to help fashion brands and retailers combat the many challenges that come with planning a collection, in the aim of guiding fashion brands toward efficiency, sustainability, collaboration, and success. 

As mentioned previously, the fashion industry’s main challenge is inventory management: Product assortment and quantity, as well as understock and overstock, are decisions which require precise planning prior to releasing a collection. Heuritech’s predictive analytics provide brands with the necessary insights to predict demand, market and product trends, optimal launch times, and consumer segmentation in order to create collections with optimal sell-through. 

Ultimately, this data helps to prevent overstock, in turn reducing waste and guiding brands towards a more sustainable approach. Recent feedback from a Heuritech client attests to the benefits of our trend forecasting platform: “This [platform] will help us quite a lot both to spot the big stories to include in our next collection and to balance our assortments based on future market demand.” As an example, we forecast the color medium green to increase in visibility by 7 percent this summer 2021 in Europe among women – these kinds of insights reduce the guesswork in planning a collection. 

The second major challenge I mentioned is cross-team communication. Heuritech’s trend forecasting platform aligns these teams, speaking a common language to each. Merchandising and planning teams can use data-driven insights to provide designers with the right guidelines for future best-sellers and to avoid missed opportunities, as well as optimizing product assortment and adjusting drops with data on market demand evolution. Design teams can prepare collection meetings with qualitative and quantitative insights about the relevance of trends, facilitating communication with analytical-minded teams on their trend intuitions and product choices. 

Finally, communication teams can anticipate the biggest trends to come and become more reactive to market demand, identifying the key trends in each collection to highlight to better reach the brand’s audience.

If you want to know more about Heuritech’s solution and its connection to SAP, its CEO Tony Pinville sat down for an interview with E-3 Magazine to explain what the company has to offer.