For many mid-sized manufacturing companies, catalog parts, standard parts, C-parts and semi-finished materials account for a surprisingly large share of all purchased part numbers. Individually, these parts often seem insignificant — a screw, washer, cable tie, cable lug or sheet metal blank rarely attracts the same attention as a complex welded assembly or a precision-machined component. But across hundreds or thousands of part numbers, these categories create substantial procurement complexity.
In one recent analysis, a mid-sized manufacturer had more than 1,800 different part numbers in scope. Almost half of them were catalog parts or standard parts. That is not unusual. For the German Mittelstand (SME), this is a typical situation: many technical products are built from a combination of custom-designed components, standard mechanical parts, electrical catalog goods and semi-finished materials such as sheets, tubes, profiles or bars.
The common assumption is that these categories are already optimized — standardized, sourced from professional catalog suppliers, integrated into ERP systems and supported by efficient ordering processes. But this assumption is often wrong. The central insight is simple:
Catalog integration does not replace price intelligence.
Why Catalog and Standard Parts Matter
Catalog parts and standard parts exist to reduce complexity. Instead of designing and sourcing every small component individually, companies use standardized components available in large quantities from specialized suppliers — mechanical standard parts such as screws, nuts and washers, as well as electrical catalog goods such as cable ties, cable channels, cable lugs, relays, switches and other installation components.
A mid-sized manufacturer producing in low or medium volumes cannot afford to create custom specifications for every standard component. A simple M6 screw, for example, is dramatically cheaper as a mass-produced standard part than as a custom-manufactured component. That is why catalog and standard parts are essential for industrial efficiency: they reduce engineering effort, simplify sourcing, improve availability and help companies avoid unnecessary customization.
Why Professional C-Parts Suppliers Create Real Value
Established C-parts suppliers such as Würth provide much more than individual parts.
They offer broad assortments, ERP catalog integration, automated ordering, reliable logistics, production-related supply concepts and in some cases consignment stock directly at the customer's site.
This creates real operational value.
For procurement teams, the value is not only the price of a single screw or cable tie. It is the efficiency of the entire process:
- ordering
- forecasting
- catalog management
- ERP integration
- invoice handling
- delivery reliability
- logistics
- inventory management
- replenishment
- production availability
For this reason, C-parts management has traditionally focused heavily on process cost reduction — and that focus is valid. A well-integrated catalog supplier can reduce administrative effort and make the supply of standard parts highly efficient. But there is a blind spot: a process can be efficient while the underlying price structure becomes increasingly inconsistent.
The Blind Spot: Price Logic
Many companies assume that catalog parts are already optimized because the ordering process works well. The supplier is integrated, the catalog available in the ERP system, deliveries reliable, invoices processed automatically. From an operational perspective, everything looks fine. But the price logic behind thousands of catalog positions is often much less transparent.
Over time, catalog prices can become inconsistent for several reasons:
- old price lists are carried forward
- new parts are added without systematic benchmarking
- discounts are applied inconsistently
- high-runner items are negotiated aggressively while long-tail items are accepted
- annual price negotiations use outdated reference volumes
- technical comparability between parts is not transparent
- historical supplier relationships reduce price pressure
- ERP catalog integration creates a perceived lock-in effect
The result is a catalog structure that works operationally, but is no longer commercially optimized.
This is where COVALYZE and PartIQ create value.
How COVALYZE and PartIQ Change the Analysis
Traditional procurement analysis usually starts with ERP data — supplier names, part numbers, descriptions, order quantities, prices and spend values. But for standard parts and catalog goods, this information is often not enough. A supplier description may say "screw M6," but that does not fully describe the part. For a meaningful comparison, procurement needs technical parameters such as diameter, length, material, coating, head type, thread type, strength class and standard reference. The same applies to electrical catalog goods, semi-finished materials and many other standard components.
PartIQ enriches procurement data with technical parameters. COVALYZE Analytics then uses these parameters to make parts comparable, identify outliers, analyze price structures and prepare supplier negotiations or new tenders. This changes the role of procurement analysis: instead of comparing only prices and volumes, companies can compare technically similar parts under controlled conditions. That is the difference between simple spend analysis and technical price intelligence.
Case example: screws
400+ screw positions — and an unexpected price pattern
In one anonymized analysis, more than 400 screw positions were examined. At first glance, this seemed like a typical standard parts category. The supplier relationship was established, and the assumption was that pricing would follow normal quantity logic.
In procurement, the expected logic is clear: the higher the quantity, the lower the unit price. This means quantity and unit price should normally show a negative correlation. But the analysis revealed the opposite — for technically comparable screws, higher quantities were associated with higher prices.
Without technical parameters controlled for screw type, size, length and coating, a supplier can always argue that two screws are not truly comparable. Regression-based analysis removes that ambiguity and makes price deviations visible.
Why These Price Structures Happen
In many companies, catalog negotiations are based on reference baskets or standard volumes. A procurement team selects a group of representative items, sends them to suppliers and receives price lists in return. Based on these responses, the buyer creates a price comparison and selects or renegotiates with a supplier. The problem is that these reference baskets often age.
Over several years, demand changes. New parts are added. Some former high-volume items become less relevant. Other parts become more important. But the negotiation logic is not always recalibrated with current ERP volumes or forecast data. During annual price negotiations, a few visible high-runner items may be pushed down in price while increases are accepted on less visible items. On paper, procurement may still show savings on selected positions — but across the full catalog, the commercial logic can deteriorate.
This is not necessarily the result of bad intent — it is often the result of complexity. When hundreds or thousands of catalog positions, technical variants, price tiers and changing volumes are involved, manual analysis becomes difficult and Excel-based comparisons quickly reach their limits. AI-supported procurement analytics changes this: COVALYZE Analytics can process the full dataset, enrich missing technical parameters, analyze price-volume relationships and identify where the price logic no longer makes sense.
Why Semi-Finished Materials Belong in the Same Discussion
Semi-finished materials should not be excluded from this analysis. For many manufacturers, sheets, tubes, profiles, plates, bars and similar materials represent significant purchasing volumes, especially in metalworking processes such as turning, milling, bending, welding and laser cutting.
The value of technical data is particularly strong here. If a company knows that 50 different parts use the same 2 mm sheet metal quality, procurement gains a completely new level of transparency.
Semi-finished materials
Standardization potential and supply chain risk in one view
First, standardization. If five similar sheet metal specifications can be reduced to three, the company can bundle demand, reduce complexity and negotiate better purchasing conditions.
Second, risk transparency. If a supplier for a specific semi-finished material fails, the company can immediately identify which parts are affected. If the affected parts are known, the company can identify which products are affected. If the affected products are known, the company can understand which customer orders may be at risk.
This turns technical part data into supply chain risk intelligence. For mid-sized companies, this is highly valuable. Many supply chain disruptions do not start with complex finished parts — they start with missing material, unavailable sheets or supplier-specific dependencies that were not visible early enough.
From Supplier Lock-In to Negotiation Power
One reason companies hesitate to challenge catalog suppliers is the perceived lock-in effect. The catalog is already integrated into the ERP system, employees are used to the ordering process, and production depends on reliable delivery. A supplier change appears risky and operationally complex. This concern is understandable — but it should not prevent companies from analyzing the commercial structure behind the catalog.
With COVALYZE and PartIQ, procurement teams can create a supplier-independent catalog data basis. Technical parameters are structured, comparable parts are clustered, price tiers are analyzed and current market or supplier information can be added. This makes a new tender much easier to prepare and changes the negotiation dynamic with the existing supplier.
The goal does not always have to be a supplier change. In many cases, the strongest result is a better negotiation position. If procurement can show that technically comparable parts have inconsistent prices, that quantity discounts are not reflected properly, or that current market alternatives are more competitive, the discussion becomes fact-based. The supplier relationship may remain in place — but the pricing logic has to become transparent.
Typical Savings Levers in Catalog and Standard Parts
COVALYZE Analytics can support several concrete levers in catalog and standard parts procurement:
1. Price Outlier Detection
Technically comparable parts are analyzed to identify unusually high prices.
2. Quantity-Price Correlation
The system checks whether higher volumes actually lead to lower unit prices — or whether the opposite is happening.
3. Technical Standardization
Parts with similar or identical technical parameters can be grouped, consolidated or standardized.
4. Alternative Part Identification
Where technical requirements allow it, alternative catalog parts can be identified and included in sourcing decisions.
5. Price Tier Analysis
Quantity discount structures can be extracted, compared and applied to actual ERP volumes or forecast volumes.
6. Supplier-Independent Tender Preparation
Instead of sending incomplete ERP descriptions to suppliers, procurement can issue technically enriched tender data.
7. Semi-Finished Material Bundling
Sheets, tubes, profiles and other materials can be grouped by material, thickness, dimensions or quality.
8. Risk Analysis
The system can identify which parts, products and orders depend on specific materials or suppliers.
Why This Matters for the SME
Mid-sized manufacturers often have lean procurement teams. They do not have unlimited resources for category analysis, technical data enrichment or manual price benchmarking. At the same time, they manage complex product portfolios, many low-volume parts and long-standing supplier relationships.
This is exactly where AI-supported procurement analysis creates value. Tasks that previously required manual Excel work, supplier-by-supplier comparison and time-consuming data cleanup can now be automated to a much higher degree.
That does not replace procurement expertise. It gives procurement teams a better basis for decisions. The buyer still decides how to negotiate, which supplier relationship matters strategically and where a change is realistic. But the analysis no longer depends on incomplete descriptions, outdated reference baskets or manual comparisons.
The Core Insight
Catalog parts, standard parts and semi-finished materials are often considered mature procurement categories. But maturity in process integration does not mean maturity in price intelligence.
A catalog can be deeply integrated into the ERP system and still contain hidden savings potential. A supplier can deliver reliably and still have inconsistent price logic. A standard part can be inexpensive individually and still create substantial savings potential across hundreds of positions.
The companies that win in this area are not the ones that simply switch suppliers. They are the ones that understand the data.
Conclusion
C-parts and standard parts are not automatically optimized just because they are standardized. They are not automatically optimized because they come from a professional catalog supplier. And they are not automatically optimized because they are integrated into the ERP system. To uncover savings potential, companies need technical price intelligence.
COVALYZE and PartIQ make catalog and standard parts comparable by enriching ERP data with technical parameters, analyzing price-volume relationships, identifying outliers, evaluating quantity tiers, supporting tenders and revealing standardization potential. For semi-finished materials, the same logic creates additional value: bundling, standardization and supply chain risk transparency.
Catalog integration does not replace price intelligence.
For the German SME, this is an opportunity to reduce costs, improve negotiation power and make standard parts procurement more transparent — without sacrificing the operational benefits of professional C-parts integration.
