At the same time, organizations have access to large amounts of procurement data. However, this data is often spread across ERP systems, Excel files, individual reports or different departments. As a result, many companies lack a central view of categories, suppliers, price developments, savings and relevant procurement KPIs.

What is procurement controlling?

Procurement controlling refers to the systematic planning, analysis, management and monitoring of all relevant procurement processes and procurement KPIs. The goal is not only to handle procurement operationally, but to manage it strategically based on reliable data.

Procurement controlling goes far beyond simple reports or regular Excel evaluations. It combines procurement data, supplier information, categories, price developments, savings potential and relevant KPIs into a single decision-making basis. This makes it visible where costs arise, which suppliers are strategically important, which categories require attention and where procurement can actively intervene.

Professional procurement controlling helps answer key questions such as:
How high is our procurement volume? Which categories generate the highest costs?
Which suppliers are strategically relevant? Where are price increases occurring? Which savings potential is realistic?
Are we buying at market level?
And which KPIs does management need for reliable decision-making?

This makes procurement controlling an important foundation for strategic procurement.

Why is procurement controlling important?

In many companies, procurement is responsible for a significant share of total costs. Even small price changes can have a major impact on margins, product costing and competitiveness. At the same time, markets are becoming less predictable. Raw material prices fluctuate, supply chains remain vulnerable and suppliers increasingly justify price increases with external cost developments.

Without professional procurement controlling, it becomes difficult for procurement departments to evaluate these developments in a structured and reliable way. When data is scattered across different systems or evaluated manually, information gaps quickly arise. Price increases are identified too late, savings are difficult to track and supplier evaluations are often based on individual pieces of information instead of a reliable overall view.

The risk is significant: decisions are made based on incomplete, outdated or inconsistent data. Procurement teams spend too much time on manual evaluations instead of actively steering procurement performance.

Procurement controlling creates transparency. It makes developments visible, standardizes KPIs and shows where action is required. This enables procurement teams to respond faster, negotiate on a stronger factual basis and strengthen their role as a strategic partner within the company.

1. Building a clean data foundation

The foundation of successful procurement controlling is reliable data. Every analysis is only as good as the data it is based on. In practice, however, this step is often underestimated.

Many companies start directly with reporting and analysis even though supplier master data, category structures, article information or invoice data are not consistently structured. Different spellings of supplier names, inconsistent category assignments, duplicate records or missing information can lead to inaccurate analysis results.

A clean data foundation means that relevant procurement data is complete, up to date and consistently structured. This includes purchase orders, invoices, supplier information, categories, article master data, prices and contract information.

2. Defining relevant procurement KPIs

KPIs are a central element of procurement controlling. They help make developments measurable and enable procurement to be managed more effectively. However, not every KPI is automatically relevant.

Many companies primarily measure what is easily available. This may include order volume, the number of purchase orders or the number of suppliers. These figures can be useful, but they do not automatically show whether procurement is performing successfully or whether existing potential is being used.

More important are KPIs that provide real steering information. These include savings, price developments, supplier performance, category development, maverick buying, deviations between purchase orders and invoices or the share of procurement volume managed strategically.

3. Using price developments and benchmarks

One of the most important topics in procurement controlling is the evaluation of price developments. Procurement departments are regularly faced with the question of whether supplier price increase requests are justified. Suppliers refer to rising raw material prices, energy costs, transport costs or labor costs. For procurement, however, such explanations alone are not sufficient.

Internal purchase prices show how a company’s own costs have developed. But they do not automatically answer the question of whether this development is in line with the market. This is why price benchmarking is becoming increasingly important in procurement.

In price benchmarking, internal price developments are compared with external market and price indices. This allows procurement teams to better assess whether a price increase is understandable or whether it exceeds actual market development. Especially in complex supplier structures and with recurring price increase requests, this creates a much stronger basis for negotiations.

Price benchmarking also shows which categories are particularly affected by price increases, where risks may arise and which price developments should be analyzed in more detail.

4. Using dashboards instead of manual reports

Many procurement departments still rely heavily on Excel. For individual analyses, Excel can be useful. However, in complex procurement structures, this approach quickly reaches its limits. Manual reports are time-consuming, error-prone and often not up to date.

Modern procurement controlling therefore requires central dashboards that present relevant procurement data clearly and consistently. A good procurement dashboard does not only show figures. It makes developments, anomalies and areas for action visible.

The key advantage is that all relevant information is brought together in one system. Procurement managers, strategic buyers and controlling teams can access the same data basis and generate their analyses directly from the system. This reduces manual effort, improves data quality and makes decisions more transparent and traceable.

If ad-hoc analyses are also possible, the added value increases significantly. Procurement teams can analyze specific questions at short notice without having to create new Excel files every time. For example, price increases, supplier developments, categories or savings potential can be examined directly within the system.

Procurement controlling with WebCIS

With WebCIS, SoftconCIS supports procurement departments in making ERP and procurement data centrally usable. Relevant data is transferred within a short period of time into a secure, web-based and ISO-certified system. From there, procurement KPIs, supplier and category analyses, price developments, price benchmarks, savings potential and AI-supported evaluations can be centrally analyzed and managed.

WebCIS was developed by procurement professionals for procurement professionals and is designed to reflect the actual requirements of strategic procurement departments. The solution helps companies not only make data visible, but translate it into actionable information.

The main added value lies in giving procurement teams a central, up-to-date and reliable data foundation. This makes it easier to assess price developments, identify savings potential faster, evaluate suppliers more transparently and make better-informed decisions.

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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.

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On May 19 and 20, 2026, SoftconCIS presented WebCIS 4.0 at the BME eSolution Days at Areal Böhler in Düsseldorf. The event once again brought together numerous solution providers, procurement professionals and experts to discuss current developments in digital procurement.

One topic was particularly present throughout the event: artificial intelligence in procurement. At many booths, in presentations and in conversations, it became clear that AI is becoming increasingly important for procurement organizations. At the same time, it also became apparent that while many companies are actively exploring the topic, practical implementation is still at an early stage.

A particular highlight was our expert presentation by Bastian Wagner on the topic “AI in Procurement: Doing Instead of Talking!”. The high number of participants confirmed that procurement departments are currently looking above all for practical answers:

• Where can AI provide concrete support in procurement?
• What data foundation is required?
• How can price developments, benchmarks and KPIs be evaluated more effectively?
• What role does procurement controlling play in data-based decision-making?
• How can real value be created from existing ERP data?

In the discussions at our booth, it became clear that many procurement departments already have access to large amounts of relevant data – for example from SAP and non-SAP systems, purchase orders, invoices, supplier master data or category structures. However, the challenge often lies in making this data quickly, structurally and decision-oriented usable.

This is exactly where WebCIS 4.0 comes in. As a specialized platform for strategic procurement controlling, WebCIS supports companies in transparently analyzing procurement data, preparing key performance indicators and making potential savings visible.

The event also showed how dynamic the market around AI in procurement has become. Many providers are now positioning themselves with AI functionalities, AI agents or automated workflows. For procurement decision-makers, this creates a new challenge: it is no longer just a question of whether AI is relevant in procurement, but which applications actually deliver measurable value.

Because AI alone does not solve procurement problems. What matters is whether it works on a clean data foundation, can be embedded into existing system landscapes and answers concrete procurement-related questions. For example: Where do price deviations occur? Which suppliers are developing critically? Which categories are affected by market changes? Where are potential savings hidden? And which developments will become relevant to future business results?

From our perspective, this connection will be decisive: AI must not be viewed separately from procurement, but as an intelligent extension of reliable procurement controlling. WebCIS 4.0 provides the foundation for this by bringing together procurement data from SAP and non-SAP systems, analyzing it and translating it into decision-relevant information. AI can build on this foundation, identify patterns faster, detect anomalies and support procurement teams in making more fact-based decisions.

The BME eSolution Days therefore confirmed an important impression: the future of procurement will not be determined by new technologies alone, but by the ability to integrate technology meaningfully into existing processes, data structures and decision-making paths. Companies that want to use AI successfully in procurement should therefore first strengthen their data foundation, KPI logic and transparency in procurement controlling.

We would like to thank all visitors for the insightful conversations, the open exchange and the great interest in WebCIS 4.0.

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Between Euphoria and Skepticism

Hardly any other topic polarizes strategic procurement as much as artificial intelligence. On one side are the enthusiasts who see AI as the solution to every challenge, from spend analysis to supplier development. On the other side are the skeptics who distrust AI results and rely on the tried-and-true combination of experience, market knowledge, and their own judgment.

Both camps are right, and both are wrong when they ignore the other side.

Because AI in strategic procurement is neither a panacea nor just hype. It is a powerful tool, but only in the right hands.

What AI can really do in procurement

AI’s strengths lie where humans reach their natural limits: in processing large amounts of data, recognizing patterns, and the speed of analysis.

Specifically, this means the following in strategic procurement:

Price index comparisons at the click of a button. Instead of manual research and time-consuming Excel models, AI can automatically compare market indices such as those from Eurostat or the Federal Statistical Office with your own product groups and immediately highlight discrepancies. What used to take days can now be done in minutes.

Pattern recognition in supplier and pricing structures. AI detects inconsistencies in price trends, illogical tiered pricing structures, or conspicuous volume fluctuations, across all material numbers and suppliers simultaneously. No human eye could sift through this volume of data in a reasonable amount of time.

Predictive analytics for better negotiations. Based on historical price and market data, AI can model price trends and provide the buyer with a fact-based framework for supplier negotiations.

Homogeneity indices for clean product groups. One of the biggest weaknesses of many procurement organizations is an inadequate product group classification system. AI-based homogeneity indices objectively show how consistent the classifications are and make suggestions for optimization.

Where AI Reaches Its Limits

As impressive as these possibilities are, AI cannot replace the strategic thinking of an experienced buyer. And for good reason.

AI works with patterns from the past. It cannot assess whether a supplier is a strategically indispensable partner despite poor metrics. It does not understand political market dynamics, personal negotiation relationships, or company-specific priorities.

AI provides suggestions, not decisions. It highlights potential that would otherwise remain invisible. But whether and how this potential is realized remains the task of humans.

This is not a weakness of AI. It is the natural division of labor between humans and machines, and that is precisely where the real added value lies.

The crucial prerequisite: the data foundation

AI is only as good as the data it works with. This is where many procurement organizations fall short not because of the technology, but because of data quality.

Missing master data, inconsistent product category systems, and data from various sources that isn’t harmonized, all of this makes AI analyses unreliable or simply impossible. Anyone who wants to use AI effectively first needs a clean, complete, and consistent data foundation.

A powerful procurement information system like WebCIS 4.0 creates exactly this prerequisite: consolidated data from various sources, uniform product group classifications, and interactive dashboards as a solid foundation for integrable AI models that deliver real added value.

Conclusion: AI as an Enhancer of Human Expertise

AI in strategic procurement is not just hype, but it’s also not a surefire success. Its true value unfolds where it does what it does best: analyzing data, recognizing patterns, and identifying potential faster and more comprehensively than any human could.

Strategic assessment, decision-making, and negotiation remain the responsibility of the experienced buyer. Not because AI is incapable of doing so, but because procurement remains, at its core, a human endeavor.

The question, then, is not whether AI creates value in strategic procurement. The question is whether your organization has what it takes to leverage that value.

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Automation and AI open up tremendous opportunities to make processes more efficient and cost-effective. The real question is how we use them. Without human judgment, market knowledge, and creativity, procurement will only get halfway there.

Pattern-based analyses – from price developments to benchmarks, exchange rates, or commodity index tracking – have been standard for years. AI can now deliver these faster and at scale. But whether it will independently create complex, innovative analyses in the future is still an open question.

Intelligence is human

Procurement controlling is more than just a savings machine. It is a strategic steering instrument that shapes decisions. To do that, procurement needs powerful platforms that do not just collect data but also connect and interpret it intelligently. AI plays a key role here, but it is not the only one.

Data is today’s most valuable raw material. But it only creates value when it is analyzed purposefully and translated into clear actions. Systems like WebCIS support this process with modern self-service BI, automated forecasting, and flexible analytics. Still, one fact remains: at the end of the day, people make the decisions, not machines.

Procurement as a driver

A successful procurement function does not just look back; it looks ahead. Data-driven planning, forecasting, and structured bill-of-materials controlling turn procurement into a proactive driver within the organization, directly influencing sales, production, and overall strategy.

WebCIS enables this by speeding up analyses, creating transparency, and opening doors to new questions. In this way, procurement guides AI, rather than being guided by it.

More than just savings

Cost optimization remains a core objective. But modern procurement organizations demand more: flexibility, transparency, and the ability to shape analytics on their own terms. WebCIS delivers this with a broad set of KPIs, adaptable reporting, and more than 20 years of industry expertise.

A key differentiator is the combination of algorithms with customer feedback. Systems do not just learn from data, they also learn from real-world challenges faced by their users. This is how practical, innovative insights are generated, such as variance analyses, global price benchmarks, or best-in-class comparisons.

People and machines together

AI is a powerful tool for detecting patterns, uncovering anomalies, and accelerating processes. But for strategic decisions, creative thinking, and sustainable solutions, human expertise remains irreplaceable.

Success lies in the combination: AI provides the data foundation, people create the value. Today and in the future.

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