From Hurricanes to Stockouts: Applying Probabilistic Demand Forecasting To Retail

A recent breakthrough in weather forecasting has sparked exciting discussions about the power of AI and machine learning (ML). Google DeepMind's innovative AI forecaster has outperformed traditional, physics-based simulation systems, highlighting the potential of probabilistic forecasting.

Using a diffusion modeling approach, this AI produces faster and more accurate estimates than standard approaches and excels in capturing uncertainty and risk. Picture traditional weather forecasting like solving a giant physics puzzle — scientists use complex equations to track how air, water, and heat move around. Now, Google DeepMind has created an AI system that's like having a super-smart forecaster who learns from millions of past weather patterns.

So what does this have to do with the apparel and footwear industry?

When Stockouts Hit Like Hurricanes

Predicting consumer retail demand can often feel as unpredictable as tracking a hurricane's path. Stockouts — the retail industry's version of a natural disaster — can disrupt inventory allocation and devastate sales performance.

Traditionally, retailers mitigate this risk by leveraging intricate mathematical models and solving complex equations under the watchful eye of analysts. However, they struggle to capture the many interacting features that drive demand in these equations, which range from the concrete (historical transactions, like-product sales, promotions, holiday events) to the fuzzy (social media trends, local weather, economic shifts, acts of nature).

With machine learning, we can extract more powerful and accurate outputs from data without needing to hand-solve each equation (or program Excel to do so on our behalf). Machine learning models analyze millions of leading indicators — observing even difficult-to-spot, sudden shifts in demand ("viral moments") — and can determine the relationship between features and targets on analysts' behalf.

Probabilistic demand forecasting for fashion, much like DeepMind's approach to weather, provides a way to anticipate unpredictable events and optimize supply chains effectively. Think of this modeling approach like a game of "telephone" played in reverse: instead of messages getting more garbled as they pass along, the AI starts with fuzzy predictions and gradually makes them clearer, while tracking all possible outcomes.

This is particularly valuable because it helps us understand not just what might happen, but how confident we can be about our predictions. By understanding the range of possible outcomes, brands can make smarter decisions about inventory and allocations.

It's like having a local weather station that knows exactly how weather affects your specific neighborhood, but for article-level demand.

The key takeaway from DeepMind's success is the importance of creative problem-solving in AI. The diffusion modeling approach showcased in the weather study exemplifies how rethinking established methods can yield significant improvements — exactly what we aim to do at Syrup.

What Will Probabilistic Forecasting Mean For Your Retail Business?

At Syrup, our approach combines cutting-edge modeling methods with unparalleled access to rich customer data. While DeepMind's AI leverages publicly available datasets to achieve its results, Syrup's strength lies in its proprietary data.

This allows us to uncover patterns in fashion trends and events that others might miss. By blending innovative methodologies with unique datasets, we produce demand forecasts that are both precise and actionable.

And much like Google, Syrup applies inventive AI strategies to tackle complex challenges — challenges that currently rely on status quo approaches with diminishing performance outcomes.

Our focus isn't just on improving accuracy but also on enhancing speed and scalability, ensuring our solutions meet the industry's evolving needs.

As we look to the future, the potential applications of probabilistic forecasting in retail are vast. From mitigating the impact of unexpected demand surges to refining allocation strategies for seasonal launches, AI offers a clear path forward.

Just as AI is revolutionizing how we predict hurricanes, it's poised to transform how brands navigate the unpredictable terrain of consumer demand. At Syrup, we're excited to lead the charge in leveraging these advancements to create a more resilient and responsive retail ecosystem.