AI / MACHINE LEARNING

Ocado on forecasting the future: using deep learning to optimise online grocery supply chains

Ocado’s latest article highlights how its AI-powered demand forecasting system uses deep learning to help retailers reduce waste, improve product availability, and drive greater efficiency across the online grocery supply chain.

(Image Source)

Ocado

Ocado, a global leader in online grocery technology, recently published an article highlighting how AI-driven demand forecasting is transforming the retail landscape. The piece emphasizes that in a sector where margins are tight and freshness is non-negotiable, precision forecasting is not just a technical challenge — it’s a business-critical capability. The main idea centers on how Ocado’s deep learning–based forecasting system enables retailers to reduce waste, enhance product availability, and create a more efficient, sustainable supply chain.

Precision Matters in Online Grocery

In the fast-moving world of online grocery, precision isn’t optional — it’s everything.

Forecast too little, and customers face out-of-stock frustrations. Forecast too much, and you’re left with wasted food, lost revenue, and inefficient use of storage.

Striking the perfect balance is one of ecommerce’s toughest — and most crucial — challenges, particularly when perishable goods are involved.

At Ocado, we’ve developed a demand forecasting system designed to tackle this challenge directly. It empowers retailers to reduce waste, improve availability, and unlock efficiency across every stage of the supply chain.

The Challenge: Why Traditional Forecasting Falls Short

Historically, retailers have relied on spreadsheets, manual rules, and basic statistical models to estimate demand. While these methods served their purpose in the past, they simply can’t cope with today’s retail complexity:

• Vast and constantly changing product assortments

• Short shelf lives for fresh produce

• Rapid shifts in customer behavior due to weather, holidays, or major events

• Diverse fulfillment and delivery networks

Legacy systems also tend to depend on years of historical data, making them ineffective in new markets, for new product launches, or when rapid adaptation is required.

Online grocery operations now need forecasting tools that are scalable, granular, and self-learning — capable of thriving in a fast-changing retail landscape.

The Solution: Deep Learning and a Global Forecasting ‘Control Centre’

At the core of Ocado’s forecasting engine lies a shared deep learning control centre, trained on billions of sales data points across multiple markets and retail partners.
Every day, it generates over 70 million supply chain forecasts.

This global model architecture allows Ocado to:

• Transfer insights between retailers, giving new partners instant access to proven intelligence

• Predict demand accurately without relying on long sales histories — even for brand-new products

• Continuously adapt to evolving consumer behaviors and market trends

Unlike conventional approaches, Ocado’s neural networks don’t require manually cleaned or aggregated data. They seamlessly process:

• Static attributes like product type, size, and storage conditions

• Historical variables such as sales patterns and stockouts

• Future drivers like promotions, holidays, and delivery slot availability

These are analyzed through encoder-decoder architectures that build a detailed understanding of how products behave over time.

Real-Time, Integrated, and Intelligent

Ocado’s demand forecasting integrates seamlessly with the Ocado Smart Platform, where webshop, fulfillment, supply chain, and last-mile operations are fully connected.

This integration enables features other systems simply can’t match:

• Real-time availability updates triggered by live inventory movements

• Adaptive forecasting that allows retailers to prioritize availability or minimize waste based on strategy

• Comprehensive control dashboards, where planners can override forecasts, review accuracy, and track outcomes — all in one place

The Impact: Tangible Results at Scale

Ocado’s AI-powered forecasting isn’t theoretical — it’s delivering measurable results:

• Up to 40% higher accuracy compared to traditional forecasting models designed for physical retail

• Up to 98% of stock ordered automatically with minimal human intervention

This translates directly into higher availability, reduced waste, and better operational efficiency across the supply chain.

The Road Ahead: Smarter, More Adaptive Systems

Even with a state-of-the-art platform, innovation never stops. Ocado’s teams are actively exploring:

• Human–machine feedback loops to continuously enhance model performance and support demand planners

• Real-time responsiveness to fast-changing market signals such as social media trends, promotions, or weather impacts

Ocado’s guiding principle remains the same: to help retail partners deliver on their promises, delight customers, and run smarter, more sustainable operations.

Forecasting may be invisible to shoppers, but when it works, everything runs seamlessly — the right products are in stock, waste is minimized, and the supply chain performs at peak efficiency.

At Ocado, advanced AI is transforming the art of forecasting into everyday operational excellence — and this is only the beginning.

Source: Ocado