How TikTok, Supply Chains and Viral Demand Impact Forecasting

June 04, 2024
By Siddharth Priyesh

Procurement leaders rest many successes on their ability to forecast demand well, and respond quickly, when necessary, should unforeseen circumstances arise — a common happenstance and a new level of “status quo”.

What the profession’s seasoned professionals may not have considered in the past is how the rise of social media, particularly TikTok, can impact supply chain forecasting. The numbers present a compelling story.

The Power of TikTok

As the world came to know the importance of supply chains soon after the global pandemic left an indelible mark on society, so too did the magnitude of social media and its ability to sway the masses.

Between 2019 and 2020, TikTok realized a 654-percent increase in revenue growth; it is currently the most popular social channel used by business brands to support their marketing efforts. According to Vancouver, British Columbia-based Hootsuite, a global social media management platform, TikTok is expected to reach 2 billion monthly active users by the end of 2024, and take the lead in total daily minutes spent (by adults) on a social app in 2025.

Consumer behavior often dictates the product sales funnel and can, without warning, disrupt supply chains. Social media posts and campaigns greatly influence subscribers, and it would be foolish to underestimate the power of TikTok on supply chains. Sudden spikes in demand for certain products create unpredictability — necessitating quick fulfillment of trending goods, which is manageable if the business is prepared.

A Case in Point

The Starbucks and Stanley Quencher pink Valentine’s Day mugs released on December 31, 2023, sent crowds rushing into Target stores for their chance at purchasing the limited-edition product, part of a collection exclusive to the retailer. Due to their social media popularity, the mugs sold out within minutes and were later relisted for sale on eBay for thousands of dollars.

The small quantity release did not shake up the supply chain much, but what if Starbucks and Stanley decided to produce more to capitalize on the mug’s popularity? A massive, ripple effect on the sourcing of raw materials, mug manufacturing, and retailer distribution down to the end consumers would ensue. In the process, product stockouts, long waiting lists and unsatisfied customers would surface, reducing levels trust and revenue.

Leveraging AI to Fulfill Viral Demand

To anticipate and fulfill abrupt demand surges, players must actively build resilience within the supply chain.

By leveraging AI-powered demand-sensing technology, manufacturers and procurement teams can harness real-time analytics to accurately predict customer demand and change preferences over time when needed. Customer behavioral insights, market events, pricing, localized weather reports, external economic factors and other critical data points help seek out patterns across various channels to enhance demand forecasting, inventory optimization and production planning accuracy.

Concurrently, logistics service providers (LSPs) like warehouses and freight forwarders, should implement strategic supply planning to determine the most efficient methods to satisfy the demand.

Demand planning. Social listening tools facilitate the prediction of trends and, therefore, demand for manufacturers, distributors and retailers. Using machine learning (ML), natural language processing and statistical modelling, AI can thoroughly analyze a current situation (through conversation volumes, themes, sentiments and more), as well as how a particular situation changes over time.

These aggregated social media conversations can then be transformed into powerful actionable insights that guide short- and long-term decisions on the optimal quantum of inventory increase, production schedules, business priorities and untapped sales opportunities.

While stockpiling inventory may be a good idea, doing it in excess would be costly. When companies rely on smart technology for inventory levels, they can avoid the issue of overstocking, thus saving unnecessary costs on holding inventory, manufacturing raw materials, and manpower.

Supply planning. On the supply side, freight forwarders and carriers can use route optimization software whereby advanced predictive analytics decide which route(s) would be the quickest and most cost-efficient to manage transportation fleets and maintain high uptime. Factors such as fuel consumption, arrival times, canal blockages, geopolitical factors, extreme weather and estimated manpower hours are considered in the decision-making process.

With AI capable of digesting a multitude of data points, this helps both businesses and end consumers make the most informed choices and effectively manage cost and time. Warehouses can use IoT sensors for real-time tracking of stock-keeping unit inventory levels and share this visibility with manufacturers and distributors, enabling a higher-precision view than before.

Other considerations. Freight booking platforms provide visibility to manufacturers, distributors and freight forwarders on the cost and time required for shipping via particular routes, empowering decisions that most align with their business objectives.

Apart from using AI, it is also imperative for all parties to form strategic partnerships, leveraging each other’s expertise and resources to build robust contingency plans that can withstand stresses on the supply chain and support the increased demand, hand in hand.

Diversify Sourcing in the Age of Unknowns

In this volatile and unpredictable climate, alternative sourcing relationships are key to business survival, boosting supply chain resiliency and protecting it from sudden demand shocks.

Diversification plays a crucial role in manufacturing productivity by mitigating the impact of such shocks, as well as reducing disruptions stemming from unpredictable shortages and the subsequent compromised quality of raw materials and equipment. Sourcing to a wider net enables business to fulfill orders promptly, to the greatest extent possible.

AI at Scale

When it comes to implementing AI in planning and operational workflows, the scope required depends very much on the specific objectives and needs of each organization.

In terms of scalability, AI-powered solutions can easily scale to accommodate growing data volumes, increasing complexity and evolving business requirements. Cloud-based AI platforms offer scalability by providing on-demand resources and flexible pricing models, allowing for faster turnaround and efficient cost management. The result gives companies the ability to budget for capital expenditures to purchase new equipment or provide additional wages for new teams supporting the technological infrastructure.

The amount of time required for launching AI-powered demand forecasting and supply chain planning initiatives depends on several factors: the availability of data, the complexity of the supply chain, the readiness of AI technologies and the willingness of the organization. Pilot projects, phased implementations and robust cybersecurity architecture facilitate rapid testing, issue resolution and risk mitigation to maximize benefits quickly.

Though integrating AI into supply chains is not about keeping up with the latest buzz or TikTok trend — it’s about making smarter, more informed business decisions that will benefit company planning, operations and customer satisfaction, ultimately increasing the bottom line.

(Photo credit: Pexels/Cottonbro Studio)

About the Author

Siddharth Priyesh

About the Author

Siddharth Priyesh is vice president of CrimsonLogic, a Singapore-based global trade technology enabler.