Good inventory management is crucial for wholesale companies, especially in times of increasing competition and ongoing global uncertainty. This can be achieved with the help of artificial intelligence (AI). The use of AI technology gives wholesale companies a new role in the chain. By smartly utilising AI for demand forecasting, inventory management, and pricing strategy, their position shifts from a logistical link to an indispensable strategic partner. However, to fulfil that role, more collaboration and data sharing with other partners in the chain is needed than is often the case now. This is evident from an article published today by ING Research.
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'The ability to smartly integrate AI into inventory strategies increasingly determines the distinctive capabilities of wholesalers in today's dynamic and competitive market,' says Dirk Mulder, Sector Banker Trade & Retail at ING Business Banking. 'Wholesale companies that apply AI technology to improve demand forecasting and inventory optimisation not only create operational efficiency but also strategic value for their customers. This positions them as indispensable links in the chain, thereby significantly improving their competitive position.'
AI makes wholesale smarter, faster, and more profitable
Based on historical sales data, seasonal trends, and weather forecasts, AI can make accurate predictions about future demand. This enables wholesale companies to optimally align their inventory levels. AI technology also provides solutions in the logistics process for wholesalers. For example, AI can optimise route planning and indicate how stores and distribution centres can be most efficiently supplied. This leads to shorter delivery times and lower storage and transport costs. A third opportunity where AI technology can be deployed is in product pricing. AI tools analyse real-time market data to determine the right pricing, including based on market supply and demand, available inventories, and competition. Strategic pricing makes traders more flexible in their pricing strategy, thereby improving profit margins and remaining competitive.
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Inventory optimisation leads to higher profit margins
A good balance in inventories leads, among other things, to lower storage and transport costs, less waste, and more efficient working capital use. In the long run, inventory optimisation also results in better profit margins for the wholesaler. These had actually deteriorated in recent years, partly due to rising working capital costs as a result of large inventories combined with relatively high interest rates in 2023. Our calculations show that when final inventories decrease by 10%, profit margins in wholesale structurally improve by approximately 0.65%. This may seem relatively little, but in absolute numbers, it represents a significant profit improvement, especially for a sector with relatively thin profit margins.
Bottlenecks hindering rapid implementation
Conversations with various parties in the supply chain show that there are several bottlenecks that hinder the rapid implementation of AI in many wholesale companies. The biggest bottleneck experienced by companies concerns the quality and access to data, followed by an outdated digital infrastructure and a lack of the right expertise.
Data is still insufficiently shared within the chain
The availability of a large amount of high-quality data is crucial for the optimal functioning of AI technology. Without good data, AI cannot make accurate predictions. Additionally, AI technology is trained on data. Within companies, there is still not always uniformity in data between different departments because too often work is done in separate silos. Significant steps can also be made within the supply chain in terms of both data quality and accessibility. If it is possible to unlock data from the supplier to the customer, it leads to a more efficient chain. This is still insufficiently done because suppliers and consumers in the supply chain are not always willing to share their data with the wholesaler.
Creating value with data
By working more data-driven, wholesale companies can offer innovative services in the supply chain. For example, the wholesaler can provide retailers with insights into which products are doing well or not, what market trends are, and what optimal inventory the retailer should maintain based on expected demand. With data, the wholesaler can link customer demand to supplier demand. This allows the wholesaler to steer production instead of distribution based on what AI tools indicate is needed. This transforms the role of the wholesaler from intermediary to strategic partner.
'Since not all trading companies are yet applying AI technology in their daily work, there is a real chance that in the future, a greater divide will emerge between companies that join the AI transition and those that do not or cannot,' says Mulder. 'As technological developments progress rapidly, the lagging companies only fall further behind. It is not a question of whether wholesale companies should transform, but how quickly they can do so to remain relevant in the future.'
More information:
ING
www.ing.nl