Would you trust your investment portfolio to “gut feelings”? Probably not. Yet, consumer brands and manufacturers worldwide still base a significant portion of their demand forecasting on intuition, historical performance, and fragmented data. The result? Inventory distortions (stockouts and overstocks) lead to an inventory gap that costs brands and retailers over $2 trillion in potential sales every year.
From toilet paper shortages to empty olive oil shelves, recent events have shown how unpredictable supply chain disruptions can cost industries billions. The world’s ability to predict demand and manage inventory has failed to keep up with the complexity of today’s markets – until now.
Open Commerce is a new way of trading that is powered by emerging technologies like AI and redefining how brands and distributors handleforecasting of supply and demand.
By enabling businesses to make real-time, data-driven decisions at scale, these innovations provide a critical competitive advantage. This powerful technology equips businesses with the precision and agility needed to navigate challenges, optimize operations, and stay ahead in an increasingly dynamic market.
The Problem with Traditional Demand Forecasting
When inventory forecasting goes wrong, the consequences are severe. According to Harvard Business Review, stockouts alone cost global retailers nearly $1 trillion annually – not just lost revenue, but also damaging customer loyalty and damaged brand reputations. What makes this even more troubling is that traditional forecasting methods often exacerbate this issue.
For many supply chain intermediaries, profit margins are already slim, leaving little room for error. Buying or transporting the wrong quantities to the wrong location or at the wrong price, then storing it for too long – especially during economic uncertainty – is a recipe for disaster.
Why Traditional Demand Forecast Methods Fall Short
Most businesses rely on traditional demand forecasting techniques like Economic Order Quantity (EOQ) or Just-In-Time (JIT) inventory management, which offer little flexibility. These models often fail to adapt to:
- Shorter product lifecycles;
- Rapidly changing consumer behaviors;
- Disruption induced by geopolitical or natural phenomena in the supply chain.
Traditional statistical approaches like moving averages or exponential smoothing simply can’t handle the complex, dynamic nature of today’s markets. Their inability to address real-time variables leads to either excessive overstocking or chronic understocking – contributing to that staggering $2 trillion “inventory gap”.
This inadequacy in demand forecasting also amplifies global inflation. According to IMF research, supply chain disruptions caused inflation rates to jump by two percentage points between 2020 and 2022. The ripple effects are felt across every layer of the supply chain, from manufacturers to consumers.
AI-Powered Demand Forecasting Offers a Game-Changing Solution
Demand forecasting powered by AI marks a transformative shift away from outdated guesswork to a new era of precision and accuracy. Unlike traditional approaches, AI-powered supply chain technology can adapt dynamically, leveraging advanced algorithms and data-driven insights to deliver solutions that aren’t only reliable but also far more efficient.
Driving Precision and Profitability with AI
According to McKinsey, a 10% improvement in forecast accuracy can reduce inventory levels by up to 20% while mitigating the costs of stock outs. By leveraging advanced machine learning algorithms, AI-driven systems analyze patterns across countless variables, offering businesses granular insights into demand surges, regional preferences, and global market trends.
FMCG companies can now use AI-powered tools like Open Commerce platforms to plan for seasonal spikes. Instead of guessing how much ice cream to stock in the summer, for example, AI analyzes historical data, consumer behavior, and even weather forecasts to refine its recommendations – resulting in fewer empty freezer aisles and increased product supply to satisfy consumer demand.
Open Commerce Democratizes Demand Forecasting
But here’s the catch: to truly harness AI’s potential, access to high-quality real-time data and insights are essential. Open Commerce technology generates a wealth of accurate data and insight, and is redefining how businesses, both large and small, share and access data across the supply chain.
Open Commerce is a new type of digital trading model that delivers comprehensive, end-to-end visibility across the entire supply chain. Open Commerce platforms built on this model empower businesses to proactively identify and address potential disruptions deeply embedded within their operations. This level of visibility is critical, as most FMCG and retail brands are typically limited to only insights from their immediate supply chain partners.
Open Commerce Levels the Playing Field
Emerging markets – representing 80% of the global population – have long suffered from outdated, opaque systems that favor monopolistic giants. Open Commerce breaks these barriers by democratizing access to data and AI-driven tools.
Through real-time data sharing, Open Commerce platforms empowers smaller brands, distributors, and retailers to make smarter decisions. No data analysts? No problem. Open Commerce platforms powered by Generative AI can use natural language processing to provide actionable insights without requiring technical expertise.
For example, smaller brands can now tap into Open Commerce’s AI-powered analytics features to simple ask “What SKUs should I restock and where”. With the power of AI, the platform can intelligently understand the context of the question and provide actionable insights based on real-world data gathered across thousands of live points. This can help the retailer avoid overstock at lower-performing areas while doubling down on high-demand regions to reduce out-of-stocks.
Financial Impact of AI & Open Commerce
The adoption of AI-powered demand forecasting and Open Commerce isn’t just about optimization – it’s also a major financial driver.
Here are the facts:
- AI could generate $1.2–$2 trillion in value for supply chain management globally.
- U.S. retailers collectively lost $82 billion to out-of-stock items last year–a problem AI could mitigate significantly.
- Even marginal gains – like a 10% improvement in forecast accuracy – can translate into tens of billions in reduced working capital and higher service levels for businesses worldwide.
The Future of Commerce is Open, and It’s Here
The age of intuition-driven demand forecasting is over. AI and Open Commerce have rewritten the playbook, providing solutions as precise as they’re scalable. From slashing costs and minimizing inefficiencies to democratizing access for small players, this technology is reshaping the future of global commerce for the better.
The next round of industry leaders won’t be those who follow the old rules – they’ll be the ones who challenge them.
Let’s do this together – get in touch.
