Data | Domains
Silver Sponsorship Data Driven Commerce 
Walter van der Scheer 27 Jan, 2016
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In today’s highly competitive retail landscape, demand forecasting is more critical than ever. Retailers need to predict product demand accurately to avoid stockouts, reduce overstock, and optimize their supply chains. While standard demand forecasting solutions may seem like a quick fix for small retailers, large-scale retailers need custom solutions tailored specifically to the unique complexities of their business, and data offers far greater long-term value. Whether you’re managing inventory for thousands of products across multiple stores or dealing with the complexity of seasonality, promotions, and external variables like weather, a custom demand forecasting solution is essential for capturing the true drivers of demand.
What is demand forecasting?
Demand forecasting is the process of predicting future customer demand for a product or service based on historical data, market trends, and external factors. For retailers, this means estimating how much of each product will be needed in stores over a specific period, optimizing inventory levels, and reducing stockouts (empty shelves) and overstock (excess inventory). Accurate demand forecasting enables retailers to meet customer needs while minimizing waste and operational costs. Learn more about our approach in designing custom demand forecasting.
1. Solutions Tailored to Your Business Needs
Retailers often face highly specific challenges based on scale, product range, and operational peculiarities. A standard forecasting tool is built to serve generic use cases and often fails to capture the nuances that can significantly impact a business. On the other hand, a custom demand forecasting solution can meet your business’s specific requirements and accommodate its unique data sources and patterns.
For instance, custom solutions can better handle factors like promotions, weather, regional demand fluctuations, and inventory complexity across different store locations. These models are adaptable to your business’s evolving needs, ensuring that the forecasts reflect reality. In contrast, standard models may overlook critical factors or apply generic assumptions, leading to less accurate predictions and costly miscalculations.
Xebia’s recent webinar with Albert Heijn (AH) highlighted the importance of a custom solution for managing large-scale retail operations. We emphasized that by building a model tailored to the business’s specific needs, the retailer could significantly improve forecasting accuracy. For example, AH was able to improve forecasting accuracy for weather-sensitive products by 12.5%, ensuring better stock availability during peak demand. This improvement translated to a reduction of food waste by many kilograms over a year. Standard models often fail to capture such complex and varied demand drivers. A custom solution, however, can be designed to address these nuances directly, ensuring more accurate and actionable forecasts. Please check out the on-demand webinar Demand Forecasting at Scale for the full story.
2. Handling Complex, Large-Scale Data
The sheer volume of data in large retail operations presents challenges. A retailer might be handling millions of transactions, thousands of products, and various locations every day. Additionally, other factors like promotional calendars, product launches, or special events can profoundly impact demand. Standard forecasting tools often lack the capability to process and integrate these data sources effectively.
A custom demand forecasting solution allows ingesting and integrating multiple, sometimes unconventional, data sources. These can include historical sales data, weather forecasts, promotional schedules, and even regional purchasing patterns. With the right setup, your custom solution can not only analyze these data points but also learn from them, improving its accuracy over time. Retailers that require forecasts for tens of thousands of products across different stores for multiple time frames will benefit from a custom model that can adapt to the complexity and scale of the business.
3. Better Accuracy Through Advanced Machine Learning
One key limitation of standard demand forecasting tools is that they generally use predefined algorithms or models that are not optimized for every business. On the other hand, custom solutions can leverage cutting-edge machine learning techniques to create more sophisticated models that better reflect your business’s unique characteristics.
In retail, product demand is influenced by multiple dynamic factors such as seasonality, holidays, promotions, and consumer behavior trends. A custom solution provides the flexibility to tweak algorithms, add or modify features, and retrain models to adapt to changing conditions. This level of control enables retailers to optimize their forecasts continually, improving the precision of their predictions and ensuring better inventory management.
4. Adapting to Real-Time Changes
Retail is fast-paced, and demand forecasting needs to keep up. External factors such as sudden weather changes, product recalls, or supply chain disruptions can significantly affect demand. Standard solutions often fall short when incorporating real-time data and adjusting forecasts dynamically.
A custom demand forecasting solution is built to be more responsive. By processing real-time data, your custom model can adapt to these shifts and generate updated predictions. For example, if a sudden heatwave is forecasted, your custom solution can predict a spike in demand for seasonal products like ice cream or cold beverages. These real-time adjustments can drastically reduce stockouts and improve customer satisfaction by ensuring products are always available when needed.
5. Reduction in Overstock and Waste
Overstocking can be as costly as stockouts, especially for retailers dealing with perishable goods. By adopting a custom demand forecasting solution, retailers can significantly reduce waste, particularly for fresh products with short shelf lives. Standard forecasting models may not be as fine-tuned to recognize and mitigate the risk of overstocking certain high-turnover items.
With a custom solution, you can build specific rules and models around your unique product categories, optimizing for waste reduction and efficient inventory management. You can create differentiated strategies for handling perishable vs. non-perishable items or bulky products that occupy significant storage space. The financial and environmental savings from waste reduction alone can justify the investment in a custom solution.
6. Long-Term Scalability
One significant advantage of a custom-built solution is that it scales with your business. As your retail operation grows, either through the expansion of product lines, stores, or geographic locations, the demand forecasting solution can be adapted accordingly. Standard solutions are often rigid, requiring significant reconfiguration (or expensive upgrades) to handle increased scale.
With a custom demand forecasting model, you can fine-tune and add capacity as your business evolves. Whether you’re forecasting new store locations, incorporating new product lines, or adjusting to shifts in consumer behavior, a custom solution offers the flexibility you need to keep up with market demands.
7. Full Control and Flexibility
Using a third-party standard solution often comes with limitations—you may not have full control over updates or access to all features. With a custom solution, your retail team has complete control, from the initial design to ongoing optimization. If new factors come into play, such as a change in your supply chain strategy or new marketing campaigns, you can update and modify your forecasting model accordingly.
Demand forecasting is always a collaboration between the forecasting model (regardless of its sophistication) and a human in the loop. Retail professionals often need to make last-minute corrections or adjustments for factors that cannot be captured in the data—such as local events, unexpected disruptions, or sudden changes in customer behavior. A custom solution makes this process much smoother by enabling seamless human intervention, allowing your team to quickly override or fine-tune the forecasts when necessary.
This flexibility ensures that the forecasting solution grows with your business and continues to deliver value without being constrained by vendor updates or a lack of customization options.
Conclusion: Why Custom is the Future for Retail Demand Forecasting
Standard demand forecasting tools may suffice for smaller operations or businesses with straightforward needs. However, for retailers managing vast inventories, multiple locations, and complex data sets, a custom demand forecasting solution is not just an option—it’s a necessity. A tailored solution’s flexibility, scalability, and precision allow large-scale retailers to respond quickly to market changes, reduce waste, and ensure that the right products are always available when customers need them.
Investing in a custom solution may seem like a significant step, but for large-scale retail operations, the long-term financial and operational benefits far outweigh the costs. If you’re a retailer looking to optimize your demand forecasting strategy, now is the time to explore the advantages that a custom solution can bring.
To learn more about how custom demand forecasting solutions can work at scale, check out our webinar on Demand Forecasting at Scale, featuring a deep dive into real-world retail applications and success stories.
