For global fast fashion retailers, it’s extremely challenging to quickly capitalize on consumer and market trends while ensuring consistent product quality, fit and overall sustainability of the collection. A lack of agility across the internal organization and external supply chain can lead to missing out on fast trends, a high rate of returns, or a pile of unsold inventory that has to be sold at mark down price.
With the rise of online players leveraging local supply chains and boasting lead times of as little as two weeks from design to store, how do the world’s largest fast fashion retailers with heavy bricks and mortar presence remain on trend to reduce the risk of underperforming collections?
In the era of the Internet of Things (IoT), there is a wealth of new data that helps retailers deliver products that are on trend, on time and on cost. Here are three ways that an IoT-connected product lifecycle management (PLM) solution can reduce unsold inventory levels.
Leveraging information from social media, loyalty apps, online forums and direct consumer feedback can help retailers better understand their customer and how products are (or will be) received by the market. Understanding what’s trending and what’s being said about the brand in real-time, while incorporating consumer feedback early in the design process, can help brands improve product performance, price and relevance.
Predictive analytics can analyze historical and real-time data to predict which products are most likely to be successful and which price points are optimal to maximize sales based on target market, geographies and demographic. Combining this with effective collection planning and execution in PLM results in higher performing and more relevant collections, and a reduction in the number of products being left on the shelf.
By leveraging the latest innovations in connected store technology, retailers can accurately measure customer engagement and significantly improve store operations and inventory control. By connecting disparate store devices and sensors like beacons, facial recognition cameras, heatmapping and RFID tags with PTC’s Retail Innovation Platform, critical engagement data can be fed back to merchants, designers, and developers in PLM. This enables a better understanding of how stores are performing, and which are likely to run into understock or overstock issues earlier in the process so corrective measures can quickly be put in place.
By connecting PLM data with supply chain data, retailers can better control the critical path and understand where potential bottlenecks may impact lead times. Real-time dashboards combining ERP supplier KPI data with collection timelines in PLM provide visibility into which suppliers are most likely to be delayed based on historical performance, order quantities and the supplier’s size/capacity to fulfill the order on time. Bottlenecks in the supply chain often result in fast trends being missed or not fully capitalized on, meaning products are out of fashion by the time they arrive in store and end up under selling.
Using an IoT-connected PLM system, retailers can avoid these costly issues and optimize their inventory levels by better understanding customer preferences, in-store engagement, and supply chain bottlenecks.
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