Webinar recording: Optimizing master data quality in purchasing: How AI opens up new potential
published on
21.11.2024
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Master data quality is the key to efficiency and innovation in procurement. At a time when data forms the basis of every decision and AI is increasingly finding its way into procurement, the quality of master data in SMEs is becoming a key factor for strategic resilience and operational excellence.
In our exclusive live webinar "Optimizing master data quality in procurement: How AI unlocks new potential", we shed light on a topic that is becoming increasingly important for many SMEs: the role of consistent data and modern technologies in the digitalization of procurement. Robert Kaiser (procurement expert at Tacto) showed how inadequate master data is a burden on companies, what challenges are associated with it and how artificial intelligence can be used today and in the future to sustainably improve master data quality and tap into new efficiency potential.
The quality of master data plays a central role in the success and efficiency of purchasing in companies, especially in medium-sized industrial companies. In an increasingly data-driven economy, error-free, consistent and well-maintained master data is not only a cornerstone for operational processes, but also a decisive factor for strategic decisions and long-term competitiveness.
Industrial SMEs are facing a variety of challenges: The growing complexity of global supply chains, stricter legal requirements such as the Supply Chain Duty of Care Act (LkSG) or the EU Green Deal, as well as increasing pressure to operate more sustainably and efficiently. All of these factors require flawless master data quality in order to make informed decisions, optimize processes and minimize risks.
Many medium-sized companies struggle with inconsistent and fragmented data. Master data is often distributed across different systems - from ERP systems to Excel spreadsheets and manual records. This decentralized data management leads to problems such as duplicate entries, incomplete information or incorrect details. The manual effort required to maintain this data is enormous, and the lack of a uniform "single source of truth" makes it difficult to carry out standardized processes or transparent analyses.
These deficits have far-reaching consequences: From increased procurement costs due to incorrect orders and inefficient supplier evaluations to legal and regulatory risks. Without a clear overview of supplier qualifications, certifications and price developments, companies lack the necessary basis to effectively manage their purchasing strategies and exploit optimization potential.
Systematic and automated data maintenance opens up numerous possibilities. With well-maintained master data, companies can not only avoid operational errors, but also pursue more strategic approaches. Examples include the improved evaluation and selection of suppliers, the automated recording and evaluation of certificates and the implementation of detailed price and performance analyses. This not only creates transparency, but also forms the basis for the continuous improvement of supplier relationships and the optimization of cost structures.
Particular attention is paid to the integration of technologies such as artificial intelligence (AI). This makes it possible to automatically analyze data, detect and correct errors or add new information. For example, companies can update outdated address data by comparing it with external databases or automatically detect and correct inconsistencies in VAT IDs.
Innovative supplier relationship management (SRM) tools such as Tacto offer a comprehensive platform for centrally managing master data and automating processes. The ability of such solutions to seamlessly supplement existing ERP systems and create a central metadatabase that integrates and consolidates all relevant information is particularly noteworthy.
A key advantage of modern SRM systems is the ability to fully digitize supplier processes - from the onboarding phase and certificate management to the monitoring of key performance indicators. This not only saves time, but also improves data consistency and reduces manual effort.
With the increasing integration of AI-supported functions into purchasing processes, companies are able to work even more efficiently and agilely. Procurement 4.0 stands for the complete digitalization and automation of operational and strategic procurement processes. In the next stage of development - Purchasing 5.0 - artificial intelligence is not only used as a supporting tool, but also proactively takes decisions, makes optimization recommendations and continuously improves itself through self-learning algorithms.
Future scenarios include automated price benchmarks, the analysis of supplier risks based on global data streams and the real-time monitoring of compliance requirements. These developments will enable SMEs to align their purchasing strategies in an even more targeted manner while saving costs, minimizing risks and pursuing their sustainability goals.
The quality of master data is one of the decisive factors for the efficiency and future viability of procurement. Companies that invest in the digitalization of their data and processes today are laying the foundations for sustainable success. Tools such as Tacto not only offer the opportunity to overcome current challenges, but also enable the gradual introduction of future-oriented technologies such as AI. The journey towards data-driven and intelligent procurement is not only feasible for industrial SMEs, but also a decisive competitive advantage.
The importance of data and AI in procurement will continue to grow in the coming years. Particularly with regard to sustainability, resilience and compliance, the pressure on companies to digitalize their processes and optimize them based on data will increase. Companies that embrace this development at an early stage will not only secure a competitive edge, but also position themselves as pioneers in an increasingly digitalized world.
