In this article we take a look at disruptive business model innovations and how they disrupt the fashion industry. The focus of the article is on AI-enable forecasting and product design. Many more traditional retailers make use of a forecast-based, inventory driven push supply-chain system. This approach often causes large gaps between the forecasted demand and the actual consumer demand. In turn, this leads to excess inventory and markdowns. In fashion retail the demand uncertainty is especially high because of the uncertainty that is related to seasonal and fashion changes, sizes and personal preferences.
Changing the game using AI
Next to its possibilities of in store innovation, creating product recommendations and much more, Artificial iIntelligence presents new options for business model disruption. It has the potential to redefine what a product or service is and how it is provided to the consumer.
When consumer demands are constantly changing, companies should conduct demand forecasting closer to the time of selling to be more accurate. However, with the push supply chain in fashion, the design and production is typically finished far before the start of a season. To still minimize excess inventory or missed sales that are the result of inaccurate forecasting, there has been a search to shorten the lead time. One solution here is the use of artificial intelligence (AI) in forecasting and product design.
AI enables fashion companies to offer unique value propositions such as highly personalized styling services and product design closely related to actual consumer demands. This means that highly personalized styling services that suit to your consumers tastes and preferences can be offered with the help of AI algorithms. One step up is to actually use consumer feedback to combine design attributes from existing styles to create new products. This means that gathering customer data in the whole chain will play an important role. The algorithms can assess how will a set of attributes is likely to satisfy their consumers and then it can tell which sets of attributes have the highest potential to become best sellers.
New operating models
A first example of a new operating model using AI is from the company Stitch Fix. They do not require the development of a new collection for each season for unknown buyers or the need for eliminating unsold inventories each season since they act like a personal shopping service for their customers. These two pillars reduce two of the major concerns of inventory management in the traditional business models. Next to this, they create in-house styles that are the best match for their customers’ preferences.
Another innovator in fashion is Amazon’s on-demand clothing factory that completely removes the need to inventory management since products are manufactured only when an order is placed. Coupled with the use of AI algorithms an on-demand factory can tremendously reduce demand uncertainty because of the real-time analysis of trends, design and production would make the forecasting in advance of seasons unnecessary.
Jin, B. E., & Shin, D. C. (2020). Changing the game to compete: Innovations in the fashion retail industry from the disruptive business model. Business Horizons.