Many procurement departments are familiar with the situation: suppliers request price increases, material costs are changing dynamically, and internally the question arises whether current purchasing prices are still in line with the market.
But this question is often difficult to answer. Looking only at historical purchasing prices is not enough. Procurement needs external reference points: How has the market developed? Which cost components are driving the price change? And is the supplier’s price increase actually justified?
This is where WebCIS AI comes in. The solution helps connect internal procurement data with external market and price information. This creates a reliable basis for evaluating price developments more accurately and preparing negotiations on a stronger, data-based foundation.
Why Internal Data Alone Is Not Enough
Many companies have large amounts of procurement data: purchase orders, invoices, material numbers, supplier information and commodity groups. This data shows what has happened within the company.
What it often does not show is whether these developments are appropriate compared to the market.
For example, if a supplier requests a price increase of eight percent, procurement immediately needs to assess whether this request is plausible. Have raw material, energy, transport or labour costs actually increased accordingly? Or is the supplier’s request above market development?
Without external comparison data, this assessment remains difficult. With suitable benchmarks, procurement can evaluate much more effectively whether a price development is understandable and market-oriented.
The Role of NACE and Destatis
To compare procurement data meaningfully with external market information, materials, suppliers and commodity groups need to be classified correctly. Classifications such as NACE and product-related data from the German Federal Statistical Office, Destatis, can support this process.
The NACE code classifies companies and industries according to their economic activities. For procurement, this can be useful for assigning suppliers to industries, structuring market information more clearly and enabling international comparisons.
Destatis data is more focused on products and commodity groups. It can help link materials or product groups with suitable price indices and cost developments.
In short: NACE supports the classification of industries and suppliers. Destatis is particularly useful when evaluating product groups, materials and price developments.
How WebCIS AI Turns This Into Concrete Procurement Analyses
WebCIS AI connects these external reference points with existing procurement data from ERP systems. The assignment can take place on different levels, for example by supplier, commodity group or material number.
The advantage is clear: procurement no longer has to look only at internal price histories, but can compare them with suitable market and price indices. This makes key questions much easier to answer:
Is a price increase understandable?
Are our purchasing prices developing faster than the market?
Which materials or suppliers show anomalies?
Where is there a concrete need for negotiation?
This turns a simple data overview into a solid decision-making basis for procurement.
More Confidence in Price Negotiations
One major benefit arises in the preparation of price negotiations. When suppliers request price adjustments, procurement can better assess whether these requests are in line with market developments. By linking purchasing data with market indices and cost components, price developments become more transparent and easier to evaluate. Energy, transport, labour or material costs can play an important role here.
For procurement, this means that negotiations are based less on gut feeling and more on reliable data. This strengthens the internal argumentation basis and creates greater transparency towards suppliers and internal decision-makers.
Transparency for Indirect Procurement and Maverick Buying
Intelligent classification is particularly helpful where procurement data is not perfectly structured. This applies, for example, to indirect materials or maverick buying processes. In these areas, clear material numbers or well-maintained commodity group structures are often missing.
WebCIS AI can help generate suitable classification suggestions and validate them together with procurement. This also makes areas analysable that were previously difficult to capture.
In configurable dashboards, price developments, benchmarks, suppliers, commodity groups and materials can then be analysed in a targeted way. Procurement can identify more quickly where anomalies exist, which price developments are explainable and where action is required.
Conclusion: Bringing More Market Context Into Procurement Controlling
WebCIS AI helps procurement departments connect existing procurement data with external market information. This makes it possible to see whether price developments are understandable, how internal purchasing prices compare to the market and where concrete action is needed.
Especially in volatile markets, this is becoming increasingly important. Companies that do not only look at purchasing prices internally, but also connect them with market and price developments, can make more informed decisions and buy more in line with the market.
