Gain valuable insights into the importance of supplier data quality for efficient supplier management and compliance with regulatory requirements.
The quality of supplier data is crucial for efficient supplier management and the fulfillment of legal requirements such as the Supply Chain Act. High-quality supplier data enables companies to precisely calculate and control greenhouse gas emissions along their supply chain. A key aspect here is the correct assignment of NACE codes (Statistical Classification of Economic Activities in the European Community) to suppliers. NACE codes are a standardized classification system that assigns companies to certain economic classes based on their main activity. Precise coding is essential for an abstract supplier risk analysis and for calculating the Product Carbon Footprint (PCF). The PCF quantifies the greenhouse gas emissions of a product over its entire life cycle - from raw material extraction to disposal. NACE codes provide industry-specific emission factors that are included in the PCF calculations. The more precise the codes, the more accurately the emissions along the supply chain can be determined. Incorrect or outdated supplier data, on the other hand, leads to inaccurate NACE coding and falsified PCF values. This can have serious consequences, such as non-compliance with legal requirements or incorrect decisions when selecting suppliers and reducing emissions. Companies must therefore implement processes to ensure high data quality. This includes regular updates, the collection of all relevant information and the verification of the economic sectors specified by suppliers themselves. Central data management in a company-wide database is also advisable. Only with high-quality supplier data can companies fully exploit the advantages of the NACE codes for CO2 calculations and efficiently meet legal requirements. Maximized data quality is the key to transparent and sustainable supplier management.
The abstract risk analysis is an important part of the supplier risk analysis according to the Supply Chain Due Diligence Act (LkSG). It is used to identify and assess potential risks at suppliers at a higher level before a more detailed analysis is carried out. In the abstract risk analysis, suppliers are subjected to an initial risk assessment based on certain criteria such as industry, country of origin or product category. Publicly available indices, country reports or industry-specific risk assessments can be used for this purpose. For example, countries are assessed based on factors such as human rights, labor and environmental standards using country indices such as the Global Slavery Index or the Environmental Performance Index. Certain industries such as textiles, mining or agriculture are considered to be at risk for human rights violations due to the production conditions. Specific risks can also arise from the raw materials or production processes used, such as child labor in cocoa cultivation. The size of the company is also taken into account, as smaller suppliers may have fewer resources for compliance measures. By combining such criteria, suppliers can be divided into risk classes. Suppliers with a high risk potential must then be subjected to a concrete risk analysis. The abstract risk analysis is a screening tool that helps companies to efficiently prioritize risks in their supply chain. It enables an initial narrowing down of suppliers who require a more in-depth examination, thus creating the basis for targeted preventive and remedial measures in accordance with the LkSG.
The implementation of supplier risk analysis in accordance with the Supply Chain Due Diligence Act (LkSG) poses major challenges for many companies. In most cases, the information required for a comprehensive supplier assessment according to risk classes is not stored in the existing ERP or accounting systems. Although these systems contain basic supplier data such as company names, addresses and bank details of creditors, they often lack crucial information on the industry, product categories, countries of origin or the size of the suppliers. However, this information is essential in order to correctly assess the risks posed by suppliers with regard to human rights and environmental standards. In order to close this gap, companies have to invest a considerable amount of effort in manual data maintenance. Employees have to laboriously gather the missing information through research, surveys or data comparisons with external sources. This process is not only extremely time-consuming, but also prone to errors, as data from different sources has to be merged. What makes matters worse is that, according to the LkSG, the risk analysis must be carried out not only for direct suppliers, but also for indirect suppliers, provided there is substantiated knowledge of possible legal violations. This significantly increases the data collection effort for companies with complex supply chains. To meet this challenge, many companies rely on specialized software solutions that enable structured data collection, analysis and documentation. Interfaces to existing systems allow existing supplier data to be taken over and enriched with the additional information collected. In this way, risks can be assessed efficiently and the legal requirements of the LkSG can be met.
It is of key importance for companies to have complete and correct information about their suppliers. In particular, knowledge of economic classes and NACE codes is essential for efficient supplier risk analysis and compliance with legal requirements such as the Supply Chain Due Diligence Act (LkSG). In practice, however, the problem often arises that this crucial data is not stored in the ERP and accounting systems. Often only basic information such as company names, addresses and bank details of creditors are stored here. Information on industry, product categories, countries of origin or company size - which are required for NACE coding and risk assessment - is usually missing. To close this gap, companies often have no choice but to take the laborious route of manual data maintenance. Employees have to gather the missing information through research, surveys and data comparisons with external sources. This process is not only extremely time-consuming, but also prone to errors, as data from different sources has to be merged. To make matters worse, according to the LkSG, the risk analysis must be carried out not only for direct suppliers, but also for indirect suppliers, provided there is substantiated knowledge of possible legal violations. This significantly increases the data collection effort for companies with complex supply chains. Specialized software solutions offer an efficient solution for enriching supplier data with NACE codes. These enable structured and central data collection. Existing supplier data can be imported from existing systems via interfaces and enriched with the additional information required, such as industry, product categories, countries of origin and company size. With the help of databases and intelligent algorithms, the correct NACE codes can be efficiently assigned to suppliers. On this basis, risks can be assessed and prioritized in accordance with the requirements of the LkSG and the necessary preventive and remedial measures can be initiated. One provider of such a specialized solution is Scopewire Data GmbH. Their software supports companies in reducing the enormous manual effort required for data maintenance and in efficiently implementing legal requirements relating to supplier evaluation and due diligence obligations. By using such tools, companies can enrich their supplier data with high data quality and thus ensure transparent and sustainable supplier management. The correct assignment of NACE codes is the key to this.