Utilising novel data in demand forecasting to solve Fashion product launches

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We are solving demand forecasting & decision optimisation in fashion, through the untapped power of pre-selling data.The fashion industry operates a business model that has remained largely unchanged for the last century. Large amounts of stock are manufactured in low-cost geographies with long lead times (6-9 months).This time lag means brands take huge forecasting risk at time of ordering and merchandisers make billion-dollar decisions on the basis of little more than secondary school maths and gut based forecasting. Applying instinct, not analytics.This model has led to an industry that destroys 15% of products that get made due to insufficient demand. In total, inaccurate demand forecasts result in supply-demand mismatches that cost the industry $1trn/yr.The cost to the environment is enormous. The fashion industry is set to reach 26% of global CO2 emissions by 2050\.The solution requires an accurate picture of product demand. There is a gap in the market for a solution that provides an:1. Initial read on demand for new products: ideally from real transactions2. Accurate mapping of this early demand signal to a lifetime demand forecast3. Optimisation of this demand forecast to produce actionable recommendationsIn June2022 we launched our new software product for pre-selling, enabling brands to test demand prior to the main launch by pre-selling a portion of inventory directly to consumers. This project delivers the 2 remaining missing links (points 2 and 3 above).Academic research demonstrates that this pre-selling data is more predictive of lifetime demand than anything currently on the market, generating forecasts that are 50-70% more accurate.We aim to unlock pre-selling data's predictive capacity, building on an idea inspired by the research conducted by two professors of demand forecasting that sit on our board. Transforming decision making from intuition to rigorous optimisation, maximising profit & minimising waste.