Supply chain planning too often relies on a simple assumption: the future looks similar enough the past to make historical demand a reliable guide. But the rise of GLP-1 medications is the latest phenomena to challenge that assumption.
Drugs such as Ozempic, Wegovy, Mounjaro, and Zepbound are no longer a niche healthcare story. They have quickly become a demographic force reshaping consumer behavior, product demand, and inventory requirements across multiple industries. What began as a treatment for diabetes has evolved into a global movement influencing weight management, food consumption, purchasing decisions, and even apparel sizing.
For supply chain leaders, the question is whether planning teams and systems are prepared to recognize and respond to the shift before inventory imbalances emerge.
A New Consumer Demographic
The scale of GLP-1 adoption is difficult to ignore. Research suggests that between 8% and 13% of Americans are currently taking GLP-1 medications, while as many as one-third of consumers express interest in using them. A recent study by the Hartman Group highlights this disruption, estimating the current number U.S. adults using GLP-1 medication at ~31 million.
The next wave of growth may accelerate even faster. Lower-cost alternatives, broader insurance coverage, generic options, and oral GLP-1 formulations are expected to expand access dramatically over the next several years.
Unlike many consumer trends, this one directly alters behavior, as users report reduced appetite, lower caloric intake, and increased focus on healthier choices. As adoption grows, these changes become visible across entire demand patterns. This means supply chains are witnessing the emergence of a new consumer segment with a distinct purchasing behavior across food, clothing, lifestyle and other categories that reflect this changed consumer attitude.
As the market evolves, organizations that fail to identify this shift risk carrying excess inventory in declining categories while simultaneously missing opportunities in emerging growth segments.
Food and Beverage: The Volume-to-Value Transition
The food and beverage industry has already begun to feel the effects. Studies show that GLP-1 users reduce overall food spending and significantly cut consumption of sweet snacks, salty snacks, baked goods, sugary beverages, and other traditional impulse purchases.
Many users report consuming hundreds of fewer calories per day. Research indicates that grocery spending declines within months of treatment adoption, with 72% report eating healthier foods and beverages, with savory snack spending and quick-service dropping 10.1% and 8.0%, respectively.
For FMCG manufacturers and retailers, this creates a planning challenge that goes far beyond forecasting changing volumes. The more significant shift is the redefinition of value.
Consumers are increasingly evaluating food purchases through a health and functionality lens. Products that combine enjoyment with nutritional benefits may gain share, while products dependent on habitual or impulse consumption face pressure.
For planners, aggregate category forecasts may conceal critical sub-category changes. It’s key to identify where demand is being redistributed rather than simply reduced.
Additionally, following the macro-trends on GLP-1 usage and the long-term impact on food and beverage choices should be modeled, with what-if scenario playbooks defined to follow the demand shift until we reach the next new ‘normal’.
Apparel and Retail: The Great Size Curve Reset
Perhaps the most overlooked impact of GLP-1 adoption is occurring in apparel. For decades, retailers have optimized size curves using historical sales distributions. Retail inventory allocations across the size scale (Small, Medium, Large, XL, and extended sizes) are deeply embedded in planning processes.
GLP-1 adoption is creating new challenges. As consumers lose weight, they are replacing wardrobes, purchasing smaller sizes, and refreshing apparel collections. Some retailers have already observed increases in exchanges and returns associated with downsizing.
This creates several unique inventory risks.
A retailer relying exclusively on pre-GLP historical demand data may continue buying inventory according to old size distributions, only to discover that customer demand has shifted toward smaller sizes. Excess stock accumulates in larger sizes while shortages emerge elsewhere. Markdown pressure increases and cost of returns rise. Working capital becomes trapped in inventory that no longer aligns with market demand.
Additionally, consumer purchasing is beginning to reflect a change, just like a seasonal Floor Set in retail. As consumers in previously larger sizes make one-time purchases of new wardrobes, size curve distributions and volumes are being inflated once new, trimmer bodies are achieved. Refreshing personal wardrobes will be a one-time anomaly, and subsequent purchasing volumes will remain more stable on the new, smaller sizes.
The challenge extends beyond apparel. Footwear, activewear, intimates, and other fit-sensitive categories may experience similar shifts.
For retailers, size-curve planning may become one of the most important forecasting challenges of the next decade.
5 Supply Chain Moves to Stay Ahead of the Shift
- Reevaluate Demand Drivers. Historical sales are no longer a reliable source of truth. External demand drivers, including GLP-1 user counts, health trends, demographic shifts, prescription adoption rates, and consumer sentiment, should be incorporated into forecasting processes.
- Revisit Inventory Policies. Inventory targets built around historical consumption patterns will increasingly miss the mark. Safety stock, replenishment strategies, and assortment allocations should be continuously evaluated against emerging demand signals.
- Monitor Category and Size-Curve Evolution. Retailers should actively track changes in categories and in size demand distributions by region, channel, and customer segment. What was once a stable assumption needs to become a dynamic planning variable.
- Proactively Segment Demand. Not all consumers are affected equally. Understanding where GLP-1 adoption is highest can help planners anticipate category, assortment, and inventory shifts before they appear in sales history.
- Use Scenario Planning. What-if analysis is critical as consumer behavior and markets evolve. Modelling multiple demand scenarios based on different adoption rates and behavioral outcomes allows companies to evaluate the impact and the trade-offs, and develop contingency plans
Advanced solutions like the Atlas Planning Platform by John Galt Solutions allow teams to incorporate external market signals alongside internal operational data. By combining external data sources (demographic trends, consumer behavior signals, economic data, market intelligence, etc.) Atlas enhances AI-driven demand planning with a more complete view of what is shaping future demand.
Atlas enables inventory optimization at a more granular level through intelligent segmentation and clustering, so teams can identify where demand patterns are changing fastest and apply differentiated inventory policies, safety stock targets, and replenishment strategies. The platform is also equipped with advanced what-if analysis, so teams can run scenarios to sense changes earlier and continuously align inventory investments with the realities of a rapidly changing landscape.
Ready to see Atlas in action? Let’s do it.
