Artificial Intelligence in Wholesale

Künstliche Intelligenz im Großhandel | AI in Wholesale
AI in Wholesale Distribution is a great opportunity and a challenge at the same time. In this article, learn about concrete use cases of AI in wholesale and their benefits.

Wholesale companies are an indispensable part of the economy. They represent an essential link between the economic levels of industry, trade, and retail. A quote from the Frankfurter Allgemeine Zeitung describes the situation of wholesale companies very well:

“The former pure delivery wholesale, which brought the goods of the industry to the retail trade, has become a modern service provider facing additional challenges. The modern wholesaler takes over warehousing, does shelf maintenance, acts as a lender and advises its retail customers on assortment issues.”

As if this increasing number of tasks needed to be more challenging, wholesalers face rising supplier prices, shrinking margins and increased competitive pressure from e-commerce. A burden that has led to insolvency for some wholesalers in the past.

No wonder there is a growing interest in artificial intelligence systems and tools. Let’s look at what advantage AI systems offer and what concrete fields of application AI has in wholesale.

Advantages of AI systems in B2B companies

Roughly speaking, artificial intelligence tries to emulate human-like perception and decision-making structures. That sounds a lot like the Terminator or I-Robot. However, this type of AI is nothing more than science fiction. In practice, systems are used to solve a specific application problem. AI systems are, therefore, highly specialised and not “all-rounders”. Depending on the model, structured (tables) or unstructured data (images, videos, written texts) are used so that AI systems learn from them and fulfil a specific purpose.

In B2B companies, AI systems thus help automate processes and repetitive tasks. That can uncover hidden potential and reduce costs at the same time. B2B companies that successfully use AI systems save time and resources and gain a substantial competitive advantage as pioneers.

In general, these are advantages that apply to AI systems. Let’s get more specific and look at concrete application areas and AI topics in wholesale.

Four Thematic Fields for Artificial Intelligence in Wholesale

Together with Safaric Consulting, the IHK-Ruhr has identified four areas and use cases for artificial intelligence in wholesale:

1) AI in assortment and condition management

Assortment analysis and planning is an essential topic in wholesale. In most cases, wholesale companies use classic manual assortment analyses, which are rather rudimentary and take up a lot of time.

AI systems can automate data preparation and evaluation to eliminate manual effort. In addition, such systems also provide assortment recommendations and indicate the need for adjustments.

2) AI forecasting models for promotion and price management

To put it bluntly, wholesale companies are characterised by many thousands of products and customers. That creates an enormous amount of transaction data tailor-made for AI systems.

You can use AI-based predictive analytics to create precise sales and turnover forecasts. These forecasts show, for example, which customer will soon churn, which prices are most likely to be accepted and where there are additional sales opportunities.

Here, too, the AI provides concrete recommendations for action, which you can either play out to the sales team via the CRM or directly to an online shop.

Through these individual sales forecasts, wholesale companies can also target their customers more precisely and increase customer satisfaction.

Similar to the assortment analysis, some wholesale companies are already trying to carry out manual sales analyses with, e.g. Excel. Here the advantages of AI are repeated because manual analyses are far more error-prone, time-consuming and less precise than AI-based forecasts. Sales forecasts also impact warehouse planning and logistics.

3) AI in logistics management

The process steps of logistics – i.e. getting the suitable goods to the right place at the right time – are simple in theory and often even standardised in practice. Nevertheless, their optimisation, networking and interlinking are among the most complex challenges in wholesale companies. That creates great potential for artificial intelligence.

Artificial intelligence can, for example, put a logistics system in a position to predict the ordering behaviour of customers and thus better assess whether customers may place several orders in succession.
Charges in a row. This way, you can optimise deliveries at high speed and simultaneously realise savings in packaging material, volume and transport costs.

The AI field of robotics can also help with logistics. Automating logistics processes in warehouses is on the agenda of many wholesale companies. AI-based robots offer high productivity gains without having to rebuild facilities.

4) AI in supplier data management

Wholesale companies have various data pools for supplier data maintenance. In some cases, the existing validation rules need to be updated and no longer meet the requirements of the retail company, resulting in errors in the target system, for example. Here, AI systems can help to detect such errors and make correction suggestions. Wholesale companies thus save manually created Excel tables and discover errors or inconsistencies at an early stage.


Artificial Intelligence in Wholesale – Conclusion

Artificial intelligence offers a wide range of possible applications and opportunities for wholesalers. But wholesale companies cannot realise all projects at once and implement AI overnight. The use of AI requires a precise analysis of the existing processes with the aim of prioritising. Where is the greatest need for optimisation, and how quickly can a solution be implemented? Check the solution for its ROI. How long will it take until it is ready for use, and when will you start making profits with the solution?

We have created an eBook on “Predictive Analytics in Wholesale”, in which you will find a concrete procedure for using AI-based predictive analytics in wholesale.


Further Read (in german language):

IHK Dortmund: Wissenswertes zum Thema Großhandel.

IHK Ruhr & Safaric Consulting (2022): Künstliche Intelligenz im Großhandel – Einsatzmöglichkeiten und Anwendungsbeispiele.

Rolf Müller-Wondorf (2020): Künstliche Intelligenz treibt die Logistik an. Hg.:

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Predictive Sales Analytics im B2B Großhandel