Executive Summary: Key takeaways for decision-makers
- The status quo is inadequate: traditional order automation via machine learning and fuzzy matching often fails due to the variance of modern supply chains.
- The 80% hurdle: Anyone who accepts an automation rate of less than 80% today is carrying a massive technological burden.
- Neurosymbolic AI: The combination of Large Language Models (LLMs), OneTouchLearning, GNN and logic-based extraction enables adaptive, precise 2- and 3-way matching beyond orders and invoices.
- Strategic shift: Today, modern IDP solutions must be able to process all ERP-relevant documents, not just standard formats.
The efficiency paradox in input management
Companies invest millions in state-of-the-art ERP landscapes, only to find that the fuel for these systems – the data – is still filled in manually. Incoming order processing in particular is considered the problem child of digitization. While the invoice has been digitized – also by means of e-invoicing – the intelligence behind it has often remained at the level of the early 2010s.
The problem: When data does not correspond
In theory, it sounds simple: an order is received, the items are compared with the master data in the ERP and the process runs through. In practice, unstructured PDF data meets rigid database structures.
The resulting consequences:
- High error rates: Manual corrections in item allocation lead to incorrect orders and delivery delays.
- Resource commitment: Highly qualified employees spend hours “typing up” position data.
- Lack of scalability: Seasonal peaks immediately lead to backlogs, as the system is blind without human validation.
The technological impasse: Why classic fuzzy matching and machine learning are not enough
Many companies today use systems that are based on simple fuzzy matching. This technology searches for similarities in character strings. But here lies the flaw in the system: an “iPhone 15 Pro – black” on the order and an “AAPL-IP15P-BLK” in the ERP system have hardly any similarities in terms of characters.
Previous solutions are also often “one-trick ponies”. They were developed specifically for invoices and reach their limits when it comes to complex orders or delivery bills. Anyone relying on such isolated solutions today is building up a technological mortgage. If you are not able to process more than two or three document types highly efficiently, you are cementing the inefficiency of the rest of your business processes.
“Anyone who celebrates a processing rate of less than 80% as a success today has lost touch with technological reality. It’s time to raise our ambitions.” – Alain Veuve (CEO Parashift)
The paradigm shift: Neurosymbolic AI and the end of compromises
What has changed? The answer lies in the architecture of artificial intelligence. We are moving away from pure pattern recognition tools towards systems that understand context.
The new 2- and 3-way matching
In the first quarter, Parashift launches a feature set that takes ERP document automation to a new level. The centerpiece is our “Neurosymbolic-AI”. This approach combines the statistical power of deep learning (the “understanding” of text) with the hard logic of symbolic AI (the “adherence” to business rules).
The advantages of the new approach:
- Semantic comparison: The AI recognizes that “M8 screw” and “M8 fastener” are identical without a human having to define rules.
- Integrated logic: 3-way matching between order, delivery bill and invoice takes place in real time, with discrepancies being highlighted immediately.
- Universal applicability: The system is not limited to invoices. Every ERP document is captured with the same precision.
The interface as an enabler
Technology alone is not enough. The complexity must disappear for the user. A new type of user interface ensures that the few cases that still require human intervention (the remaining 10-20%) can be processed as intuitively as possible. It is no longer about data acquisition, but about data validation at the click of a mouse.
Conclusion: Don’t be afraid of the system change
The modernization of incoming order processing is not an isolated IT project – it is the basic prerequisite for far-reaching automation of all ERP documents. Companies that hesitate now risk their operational costs becoming prohibitive compared to the competition, which relies on Neurosymbolic AI.
The switch is worth it. Not only because of the time savings, but also because of the data quality, which has a direct impact on your company’s decision-making ability. Those who set the course today will not only process documents faster tomorrow, but also more intelligently.
