Create and maintain data quality

The necessary processes are established in three standardized steps, and the results are synchronized with ERP. Companies thus benefit from efficient processes and with full data sovereignty of the ERP systems - for example, SAP.

Seek and you shall find - an old rule that should also apply to material data. But in many companies, far too much time is lost in the process. Design engineers, for example, spend a good part of their time unsuccessfully searching for components for their current project. Under time pressure, they simply redesign the part - inflating the warehouse or wasting manufacturing capacity. Each additional material master costs money and at the same time increases the problem: poor data quality.

The more up-to-date, accurate and structured the material master data is, the faster reliable search results are obtained. Parts that are not found are then actually not available. Likewise, there is no need to worry about which of two similar data sets is the valid one.

MDG - the way to high data quality in three steps

In order to establish master data governance across all locations in the company, simus systems has developed a standardized procedure in three steps. High data quality is anchored as a central goal in each process step. First, clear rules are developed for the structure and classification of data.

These can be applied automatically to the existing data stock using sophisticated tools. Based on this, material master application and maintenance processes are developed and responsibilities for them are clearly defined. Thanks to intelligent software modules, these processes are automated and established across departments.

This ensures that the data quality, once achieved, is further maintained. ERP systems such as those from SAP allow the definition of workflows, but they do not support the pursuit of high data quality.

First step: Automatic master data preparation

The best way for companies to take the first step is with a project for structuring and classifying material master data. Together with simus systems consultants, the customer's project teams define standards for data structuring as the basis for individual sets of rules that define the company's data conventions.

Customizable basic rule sets already exist for numerous use cases. The simus classmate software analyzes data from various internal sources such as CAD, ERP and PDM systems. Based on the analysis results as well as the finished set of rules, the existing data stocks are automatically prepared and structured in a meaningful way.

Second step: Set up material master application process

In order to maintain the quality of the material master data once it has been achieved, a material master request process for new parts is implemented in the second step. With the flexible search in simus classmate, the user receives a reliable result as to whether a required part is already in stock. If this is not the case, the search parameters can be used as a template and a new creation of a material master can be requested.

A master data team reviews the material requests. If no suitable solution is actually found in the inventory and the request is complete, the material is sent via
simus classmate is created in a structured manner in ERP systems such as SAP. Automatic processes and e-mail notifications are set up for this purpose. This has proven to be an important protection against duplicates in the inventory and an effective means of reducing part diversity.

Easy integration with SAP

The seamless integration of simus classmate with ERP systems from SAP has proven itself at many companies. They benefit from the high usability, flexibility and transparency of the processes set up with the modules without giving up the data sovereignty of the ERP system. For this purpose, all results of the simus modules are written to a database that is used for all functions.

The results are then synchronized with the ERP system at adjustable intervals. In this way, workflows can be defined independently of SAP - but the results are available centrally for all applications such as Product Lifecycle Management or Engineering Control Center (ECTR).

Third step: Error-free material master maintenance process

In this way, for example, many specialist departments are involved in the maintenance of material masters. From engineering to marketing, many employees must be able to access it. To ensure that this works smoothly and that all fields are filled out in a compliant manner, simus systems also offers a customizable, automated process.

In the process, each material passes through various processing steps until it is completely defined. For example, a drawing part is defined in engineering and passed on to work preparation with a status change. There, the procurement type is defined, and in the case of purchased parts, Purchasing, for example, adds further views.

By the time a material has been completely created, numerous departments have been involved in the process. Here, too, automatic routines ensure that the respective tasks are processed quickly and in a concentrated manner. An authorization concept ensures security, intelligent presettings reduce the effort and prevent incorrect entries.

The process can even span distributed locations and be adapted to different workflows, for example for different types of materials. The intelligent support for routine tasks accelerates the throughput time, the data stock remains up-to-date and of high quality.

Master data governance with simus classmate - focus on data quality

In these steps, Master Data Governance can be implemented with simus classmate in a user-friendly, secure and flexible way. Both for basic cleansing and for application and maintenance during ongoing operations, the software suite provides powerful tools and convenient functions that have been specifically developed for these tasks. The increased user-friendliness leads to fast and error-free processes in accordance with applicable standards and rules

This concept of master data governance with its clear, proven methodology is suitable for permanently eliminating quality deficiencies in master data at a manageable cost. Through permanent monitoring and automatic correction mechanisms, it brings a high level of security to diverse digital processes and is thus a reliable basis for more extensive digitization projects.