NEW YORK, June 17, 2024 (GLOBE NEWSWIRE) -- The effects of the increasing use of GLP-1 diabetes drugs including Ozempic and Wegovy for weight loss has triggered an expensive problem for retailers: incorrect size curves. Impact Analytics, an AI-based retail planning and forecasting company, announced today that size small has become the most popular size for women on Manhattan’s Upper East Side, the epicenter of non-diabetic use of GLP-1 drugs. Compared to 2022, sales of women’s button-down shirts in small sizes (XXS, XS, and S) has increased in 2024 by 12%; and sales of large sizes (XXL, XL, and L) has decreased by nearly 11% (10.9%). This data has broad bottom-line implications for high-end clothing retailers that primarily serve women over the age of 30 in urban areas.
“The slimming down of America will have an enormous impact on retailers and could cost them approximately $20 million each year due to incorrect size curves. These losses will only accelerate as more people take GLP-1 drugs for weight loss,” said Prashant Agrawal, Founder and Chief Executive Officer at Impact Analytics. “Retailers generally make buying decisions for upcoming seasons at least six months in advance, and if this impact to the curve isn’t addressed, it will have ramifications on retail sales that will extend well into the holiday season and beyond.”
New York City leads the world not only in fashion but also in GLP-1 drug usage. Nearly 44% of the city’s GLP-1 prescriptions go to New Yorkers who do not have a Type 2 diabetes diagnosis. This demographic skews younger and nearly 75% are female. Impact Analytics observed that the GLP-1 drug prescriptions in New York City coalesce in the affluent neighborhood of Manhattan’s Upper East Side. This usage concentration provided a unique opportunity to examine its retail impact.
The Impact Analytics data scientists examined multi-year sales from 2022 to 2024 at flagship stores of fashion apparel retailers prominently situated on NYC’s Upper East Side. In 2022, sales of women’s button-down shirts in size small (S) were 25% of sales and have increased in 2024 to 31% of sales. A similar shift in the size curve was seen across women’s and men’s apparel. This data spurred Impact Analytics to focus their analysis on shifts in clothing size curves, which reflect both the absolute and relative amounts of particular apparel sizes bought by consumers. Shifting size curves indicate a change in customers’ body sizes.
“Most retailers have clung to the same size curves for years despite evidence suggesting their inaccuracy,” said Agrawal. “The impact of that will continue to erode retailer margin integrity unless immediate action is taken to update them.”
Size curves are specific to each product type and influence which sizes are included in the assortment as well as the quantity of each size ordered. Poor size curves directly impact the buying and allocation processes, resulting in lost sales due to stockouts and excesses in inventories that are subsequently marked down. For a billion-dollar business, over the next five to ten years, even a 2 percent transition to lower sizes can significantly impact profitability, potentially turning margins negative. This could result in a reduction of tens of millions of dollars.
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Methodology
Impact Analytics implemented a comprehensive methodology for calculating size curves to ensure robust and consistent insights at both the product and category levels. Focus stores in specific geographies, such as NYC's Upper East Side, were considered. The calculation of size curves started with sales data (units), which was then supplemented with lost sales data. Lost sales were meticulously calculated at the most granular level—product x size x store x day—to ensure accuracy. Adjustments for stock-outs were made to prevent misinterpretation of size curves due to inventory shortages. This methodology included a multi-year analysis, covering 2022, 2023, and up to April 2024, allowing for the identification of insights over time.
About Impact Analytics
Impact Analytics offers a holistic suite of solutions to help retailers and brands future-proof their businesses using predictive analytics. With tools for planning, forecasting, merchandising and pricing, Impact Analytics enables retailers to make smart data-based decisions rather than relying on last year’s figures to forecast and plan this year’s business. The company also offers tools to automate functions the industry has long managed manually by spreadsheet and to unify and streamline reporting, so executives can rely on a single source of truth when making data-based decisions. The company has been pioneering and perfecting the use of AI in retail forecasting, planning and operations for nearly a decade. Impact Analytics was founded and is led by Prashant Agrawal, a former senior consultant at McKinsey and Boston Consulting Group and current Adjunct Professor at Columbia University who teaches about the use of AI in retail.
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