How to Handle Viral Demand: 4 Data-Sharing Solutions to Boost OSA
Forecasting consumer demand has never been more challenging. Today, it’s driven not only by historical trends, but by external signals — from influencer content to viral consumption moments. Take matcha, for example. TikTok and Instagram have transformed it into a “clean caffeine” symbol for Generation Z, sending retail sales up 86% over three years. Meanwhile, raw material prices in Japan surged 265%, and supplier lead times stretched from two to six months.
A similar phenomenon unfolded with Labubu toys. The plush character from Pop Mart became a global sensation after being spotted with a K-pop star, driving a 726% sales spike in just one year.
Viral content like this creates unexpected demand, testing the limits of the entire supply chain. Traditional forecasting based on historical sales data often reacts too slowly — trends are noticed only after products have vanished from the shelves. The result? Retailers fail to meet a core customer expectation: having products available at the peak of interest.
Modern forecasting tools and better data-sharing practices, however, offer a solution. They allow businesses to anticipate trends and convert insights into tangible product availability, improving the overall customer experience.
How Technology Is Transforming Demand Forecasting
For decades, demand planning relied on historical sales patterns and seasonality — an approach suited to gradual market shifts. Today, demand can spike in an instant, forcing companies to balance rapid responses with long-term strategy. According to PwC, 82% of executives report facing this exact challenge.
In response, the concept of the "TikTok supply chain" has emerged — an approach that integrates signals from digital platforms directly into demand forecasting.
One particularly effective tool is demand sensing. This AI-driven, short-term forecasting approach uses high-frequency data — from POS systems to weather indicators and digital trends — to detect demand changes before they appear in traditional sales reports. For instance, PepsiCo ran a weather-triggered Uber Eats campaign. When temperatures in a region crossed a set threshold, customers were prompted to order a Gatorade drink.
Manufacturers can also leverage social listening tools to capture early signals of future demand. By analyzing social media conversations, forum discussions and media coverage, companies can spot shifts in consumer interests, attitudes toward products and emerging trends. These insights help answer critical operational questions: where might shortages emerge, which SKUs are at risk and do the production or distribution priorities need adjusting?
While these tools provide suppliers with richer market insights than ever before, forecasts only become actionable when paired with retailer data. Retailers have a real-time view of how demand unfolds and how consumer behavior evolves.
Data Sharing and Retailer Readiness for Viral Demand
Data-sharing technologies can combine supplier analytics with a retailer's real sales picture, creating a unified view of demand. Yet, in my experience, many retailers are still unprepared for this level of integration — whether due to privacy concerns or limited digital maturity. The consequence: decisions are reactive, and responses to demand shifts are delayed.
But the impact on customer experience is clear: from whether shoppers can find the products they want to whether those products are available at peak demand, data sharing directly influences satisfaction.
Key areas where supplier-retailer data integration drives results include:
- Visibility Into Real Demand: POS data shows which products are selling, where, and how quickly. Suppliers can adjust production or delivery volumes accordingly, while retailers can respond to shortages faster, reducing lost sales.
- Shelf Availability Control: Smart shelves with cameras, sensors or RFID tags track on-shelf availability (OSA) and flag cases where products are in stock but not accessible on the floor. Shared via data platforms, this enables suppliers to distinguish true shortages from operational errors and coordinate next steps with retailers.
- Delegated Inventory Responsibility: Vendor-managed inventory (VMI) gives suppliers access to sales and stock data and the authority to manage replenishment directly. This minimizes stockout risks without increasing inventory levels.
- Coordinated Commercial Planning: Unified supply chain and retail planning platforms allow suppliers to align with promotional schedules, adjusting production and distribution ahead of demand spikes. This reduces the risk of promotions driving demand that exceeds available stock.
When suppliers and retailers operate from a shared view of demand, responses can be precise — targeting specific SKUs and locations — instead of relying on broad inventory increases to cover uncertainty. For consumers, this means more consistent product availability. For businesses, it means better cost control and fewer losses due to stockouts or overstock.
Yuri Bykoriz is the managing director CEE at Kormotech, a global company with Ukrainian roots. Kormotech's U.S. presence is led by Optimeal, a super-premium brand currently focusing its American strategy on the cat wet food segment. It reaches customers through Amazon, Chewy and its own DTC store (optimeal.com). Bykoriz is responsible for sales and brand development in the Central European markets. Yuri has 25 years of experience in the FMCG industry. He began his career at Carlsberg Ukraine, rising from intern to vice president of operations. He joined Kormotech in March 2024.
