Introduction
Trading and wholesale companies no longer gain a competitive advantage from standalone systems. The real differentiator lies in their ability to connect data, processes, and customer experiences.
A lot of companies have already invested in e-commerce platforms, ERP systems, Product Information Management (PIM), and AI. The challenge is that the value rarely comes from any one solution alone. It’s created when these systems work together. When the systems work well together, the result is better customer experiences, fewer manual processes, and a stronger foundation for growth.
The data challenge
When data works against the business
Customer expectations are simple: find the right product, see the correct price, trust the inventory information, and receive their order as promised. They don’t think about where the information comes from. It should just be accurate.
The reality for many trading and wholesale companies is quite different. Product data is often scattered across spreadsheets, supplier files, e-commerce platforms, ERP systems, and online marketplaces. This creates duplicate work, uncertainty, and errors.
The consequences are familiar:
Incorrect or incomplete product information
Inconsistent pricing across channels
Inventory inaccuracies
Manual order processing
Increased customer service inquiries
Longer time-to-market for new products
The problem is the lack of integration between systems. Without streamlining, multiple versions of the truth emerge, affecting both operational efficiency and customer experience.
Competition is increasingly driven by data quality
Digital commerce continues to grow, and AI is playing an increasingly important role in the customer buying journey. Product discovery, recommendations, content creation, and analytics are becoming more reliant on intelligent technologies. This is changing the competitive landscape.
Trading and wholesale companies no longer compete solely on products, pricing, and delivery. They also compete on the quality of their data. When product information is missing, inconsistent, or difficult to access, it becomes harder for both customers and digital tools to understand, recommend, and purchase a company’s products.
In an AI-supported buying journey, the first evaluation of a product is often made not by a person, but by an algorithm. As a result, structured, reliable, and accessible product data is becoming an increasingly important part of the sales process.
At the same time, requirements for documentation and traceability continue to grow. New initiatives such as the Digital Product Passport are increasing the need for data that supports not only sales and marketing, but also compliance and reporting.
Product data has therefore evolved from an administrative back-office function into a strategic business asset.
The foundation
The strong foundation consists of four building blocks
When trading and wholesale companies succeed in creating digital connectivity, it is often because four key areas work closely together:
ERP provides visibility into products, pricing, inventory, finances, and orders.
PIM centralizes, enriches, and distributes product data across channels.
E-commerce makes it easy for customers to buy, reorder, and self-serve.
AI supports analysis, automation, and decision-making.
It is tempting to view these areas as separate projects. However, the greatest impact is achieved when they are treated as a single, connected commerce platform.
When ERP, PIM, and e-commerce systems are integrated, many of the errors and bottlenecks that would otherwise arise between systems are reduced. Product information becomes consistent, pricing is updated automatically, and order processes operate more efficiently.
Only then does AI have the best conditions to create value.
AI makes the need for high-quality data even clearer
There is significant interest in AI across the wholesale and distribution industry. For good reason. AI can help automate repetitive tasks, optimize product assortments, improve forecasting, identify patterns in customer behavior, and create product content more quickly than ever before.
However, AI does not solve problems caused by poor-quality data. If product information is incomplete or inconsistent, the insights generated will be unreliable. If pricing and inventory data are not up to date, automated recommendations will create frustration rather than value.
The more companies want to leverage AI, the more important it becomes to establish a strong data foundation. For this reason, AI should not be treated as a separate initiative layered on top of the business. Instead, it should be integrated into the processes where data already creates value and where decisions are made every day.
Customer Experience
The customer experience is shaped by the entire value chain
Many companies naturally focus on their e-commerce platform when discussing customer experience. However, the customer’s experience is shaped long before and after the actual purchase.
It is influenced by:
The quality of product information
Pricing accuracy
Inventory management
Order processing
Delivery
Returns handling
Customer service
If one link in the chain fails, the entire experience can suffer. Conversely, connected processes create a sense of reliability and professionalism. Customers encounter the same information whether they interact through the e-commerce platform, a sales representative, an online marketplace, or customer service. This strengthens trust while also reducing internal resource consumption.
Where do you start?
Start where the friction is greatest
Creating digital connectivity does not mean implementing everything at once. It means identifying the area where the challenges are greatest and where the impact can be measured.
For some companies, the challenge is product data. For others, it is customer-specific pricing, real-time inventory visibility, returns management, or reporting.
A good place to start is with three questions:
Where does our most important data reside today?
How many manual steps are required before customers can access it?
How often do errors, delays, or uncertainty occur in the process?
The answers often point directly to the area where the first improvement should be made.
Digital connectivity is not just an IT initiative. It is a business strategy that makes trading and wholesale companies more efficient, scalable, and easier to do business with. When ERP, PIM, e-commerce, and AI work together, they create a stronger foundation for better customer experiences and better business decisions.
Need an outside perspective on where your greatest opportunities lie, or how ERP, PIM, e-commerce, and AI can work together more effectively?
Michael Rosenørn, Product Manager
With nearly 30 years of experience and roots in the original Navision Software, Michael has extensive expertise in ERP and Business Central. He stays up-to-date with the latest developments and turns his knowledge into value through webinars, training, and consulting. Additionally, he develops solution packages and works closely with consultants and developers to deliver the best solutions.
