Demand forecasting and inventory optimization

Binnen modern retail- en supply chain management leidt het sturen op eenvoudige gemiddelden of historische verkoopcijfers steevast tot onbenut financieel potentieel. Voor een retailer met meerdere winkels heeft RAW Analytics een traditionele voorspellingsmethode vervangen door een state-of-the-art Machine Learning en probabilistische simulatie-engine. Door de focus te verleggen van "het voorspellen van één enkel getal" naar "het managen van onzekerheid", hebben we met succes een systeem gebouwd dat de gewenste klantenserviceniveaus (Fill Rates) garandeert en tegelijkertijd het vastgelegde werkkapitaal actief minimaliseert.

The Challenge: The Cost of Getting it Wrong

At its core, demand forecasting is the attempt to predict what customers will buy, while inventory optimization is the decision of exactly how much to stock to meet that demand.

Every supply chain leader faces the same balancing act:

Too much stock: Capital is trapped in the warehouse, leading to high holding costs, obsolescence, and forced markdowns.
Too little stock: You experience stockouts, resulting in lost immediate revenue and damaged long-term customer loyalty.

Our client, a retailer with multiple stores, has relied on the so-called Seasonal Naive approach (e.g., "order exactly what we sold this week last year"). While simple, these type of models are dangerously brittle. They cannot adapt to new trends, they ignore the impact of complex factors like pricing and promotions, and critically, they fail entirely when demand is "clumpy" or erratic.

Our Approach: From Guesswork to Precision

RAW Analytics has developed an end-to-end intelligence platform that takes a fundamentally different approach to demand forecasting and inventory management. The system operates in three interconnected steps:

1. Intelligent Demand Forecasting with AI. Instead of simply repeating the past, our Machine Learning models analyze complex historical patterns, recent trends, seasonality, and external factors such as promotions and price changes. The result: forecasts that are significantly more accurate than traditional methods.

2. Insight into risk and uncertainty. A forecast is never certain. That is why we go beyond a single number: our system calculates a complete risk profile for every product. This allows us to know exactly which products are stable (and require less safety buffer) and which are unpredictable (and require extra protection). This way, every decision is backed by probability calculations, not rules of thumb.

3. Optimal ordering advice through simulation. Using these risk profiles, the system runs thousands of simulated future scenarios per product. It takes into account current inventory, expected deliveries, and future demand uncertainty to calculate exactly the minimum order quantity needed to achieve your service target — without tying up unnecessary capital.

The Impact: Improvement Versus the Baseline

The impact of this approach goes beyond better numbers. It changes the way your organization handles demand and inventory:

Higher revenue: By consistently having the right products in stock, lost sales are prevented and revenue is secured.
Reduced tied-up working capital: Excess safety stock for stable products is surgically removed, freeing up capital for other purposes.
Guaranteed service levels: You simply set your desired service target — the system automatically calculates the minimum investment required to achieve that goal.
Operational efficiency: The platform optimizes thousands of products in minutes, fully automated. Your planners have more time left for strategy.

Our advanced Machine Learning forecasting system has achieved a 30% improvement in out-of-sample forecast accuracy compared to the client's legacy model. McKinsey Global Institute states that “improving forecasting accuracy by 10 to 20 percent translates into a potential 5 percent reduction in inventory costs and revenue increases of 2 to 3 percent”. A 30% improvement in forecast accuracy can therefore increase expected revenue with 4 to 5 percent.

Why RAW Analytics

Decades of experience. We combine deep practical experience at large organizations with scientific rigor. Our approach is tested and proven in the real world.
Cutting-edge technology. We actively remain at the forefront of AI and Machine Learning. From classical statistical models to the latest Foundation Models — we integrate what works.
Flexible & future-proof. Our platform is model-agnostic: as soon as better models become available, we integrate them automatically — at no extra cost to you.

Ready for the next step?

Whether you are struggling with excessive inventory levels, inconsistent availability, or time-consuming planning — RAW Analytics has the expertise and technology to change that. We would be happy to explore with you what our solution can mean for your organization in concrete terms.