In a globally functioning business world, companies operate in an area of conflict between margin pressure, customer satisfaction, speed, and quality standards.
Reliable information, a high level of process efficiency and security are among the important factors responsible for the success of a company.
Therefore, a high level of master data quality is one of the foundations of effective and efficient corporate action today.
Master data in the ERP system
Often companies are not aware of the importance and significance of high master data quality. This is something we often find out in practice when we support our customers in the implementation of ERP projects.
It is not uncommon for the collection, maintenance and cleansing of master data to be considered laborious and not value-adding. As a result, this task is often entrusted to people in the company who are only partially able to assess the consequences of a lack of master data quality. In addition, established and proven maintenance processes, i.e. actual master data management, are often missing. Master data duplicates, lack of consistency, insufficient up-to-dateness or completeness are the result.
In ERP systems, in particular, master data is an indispensable prerequisite for ensuring that business processes can be handled correctly and efficiently. They are virtually the core of the business process. The systemic approach now helps the user to carry out the processes assigned to him within the predefined structures and with the least possible time input. Ideally, the business process is also coordinated and harmonized with pre-and post-processing steps.
Let’s take a look at a classic sales process in an ERP system.
In a sales process, master data from three levels play together: Customer and article master data as well as the prices and conditions stored in the system. While the customer and article master data represent important objects for the later analysis of key figures, prices and conditions form the basis for the amount invoiced to the customer. Assuming that the price list conditions used are not up to date or insufficiently maintained, the customer will be charged an incorrect amount. In addition to the risk of annoying the customer, the correction leads to additional effort and loss of time. In the worst case, there is even a risk of loss of earnings, namely if the customer was not charged enough.
Incorrect article and customer master data can also lead to annoying and time-consuming credit notes and corrections, but much worse are incorrect coding and classifications in the master data. In addition to the thought that, for example, incorrect CRM data on the customer can also lead to incorrect marketing activities, inadequate customer or article characteristics in controlling can result in incorrectly calculated analyses such as contribution margin calculations. Even if the master data is subsequently adjusted or corrected, it will take at least another two years before the management can again have meaningful comparisons of key figures.
These evaluations and analyses provide an important basis for corporate decisions and actions. Actually, there should be no compromises. Only those who know their customers and value flows in detail can act successfully! A first indication of how important master data is for sustainable business success.
Preparation for digitalisation
Studies show that a number of preparatory tasks need to be completed, especially in the manufacturing industry and trade, in order to successfully master the digital transformation. This includes modernizing existing IT systems to integrate digital solutions, automating business processes and developing data-based business models. Master data also plays a central role here. While many resources in the form of time and money are invested in the expansion of IT infrastructures and in new business models, effective master data management still enjoys a wallflower existence.
Without sufficient master data quality (complete, up-to-date, consistent) digital business models do not even need to be developed. Thus, it is of no use to a company to have complete but outdated customer data records. For example, a young family would rather receive an offer for a sports car than information for a spacious estate car. The effectiveness of marketing activities thus fizzles out without benefit.
Master data becomes global
Collaborative B2B or B2C scenarios have been driven by companies for over 10 years. We assume that the exchange of data, especially master data, between business partners will continue to increase rapidly in the near future. Companies worldwide – whether as suppliers or customers – could have identical and redundancy-free master data along the entire value-added chain. Or imagine that from tomorrow on, your favorite wine retailer would provide you with the article master data of your favorite wines. You could manage your private wine cellar yourself in a completely different form. For the wine merchant, this opens up the opportunity to see customer loyalty in a completely new light. The prerequisite for this is once again an excellent quality of the master data.
Conclusion and approach
It seems that although the high investments in technology were necessary, many companies have failed to change their structures and processes to ensure that master data can be managed sensibly. Without excellent master data quality, the entire digital transformation, including Industry 4.0, Logistics 4.0, Internet of Things and other digital business models, stands on shaky ground.
It is important that companies recognize the need for optimization in the administration of master data and systematically integrate master data management into an organizational and operational structure. Centralization of master data management within the company, with clearly regulated tasks, competence and responsibility, also enables a solid, correct and up-to-date database.
An excellent master data quality represents – not only – with regard to the digital transformation a decisive competitive advantage and strategic success factor for a company.
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