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Detect errors and causes faster

Master data plays an increasingly important role in times of digitalization, S/4 and Industry 4.0. The Swiss manufacturer Franke Kitchen Systems is taking a new approach to continuously improve its data quality in a process-oriented manner.
Tanja Ott, cbs
October 22, 2018
Detect errors and causes faster
This text has been automatically translated from German to English.

Master data as a digital copy of real business objects plays an increasingly important role in times of digitization, S/4, Industry 4.0 and the Internet of Things (IoT). Consistently high master data quality is the basis for efficient business processes.

The Swiss manufacturer Franke Kitchen Systems therefore wanted to replace the manual evaluation of its master data with a more efficient solution and thus continuously improve data quality in a process-oriented manner.

Meanwhile, Franke uses cbs Master Data Validation (cbs MDV), a comprehensive standard software for evaluating, monitoring and optimizing master data.

The software offers an intuitive cockpit for defining company-specific business rules for data quality management. With the solution, problems and opportunities can be identified more quickly and master data can even be valued monetarily.

Access to current technical data

Every cook knows that good ingredients alone are not enough if you want to prepare first-class dishes. In addition to experience, creativity and skill, meticulous preparation is an indispensable prerequisite for success.

For Franke Kitchen Systems, this preparation begins when planning a kitchen for a private household. In order to perfectly match the Swiss company's kitchen systems to individual customer needs, planners require access to up-to-date technical data, specifications, illustrations and model variants of the individual components at all times.

Technical specifications, dimensions, photos, prices and installation instructions - all this information must be correct at all times so that customers can select products in a targeted manner.

However, if this master data is not optimally maintained, planning errors can quickly occur. Incorrect information on dimensions or raw material allocations, for example, will inevitably produce unnecessary scrap during production, and the necessary corrections will, in the worst case, also cause delivery deadlines to be exceeded. Loss of customer confidence and inefficient internal workflows that generate unnecessary costs are unavoidable consequences.

Experience shows that efficient business processes are not possible without correct master data. For this reason, monthly measurement of master data quality has been routine at Franke for a year now.

Patricia Venzlaff, Master Data Manager in the Kitchen Systems Division, previously had to read out the information stored in the SAP databases to determine the DQ (Data Quality) index and then laboriously analyze it in Excel according to defined data quality rules.

This was a time-consuming, error-prone procedure that also offered no possibility of specifically changing the criteria for the analysis. The result did provide information on whether the content was better, the same or worse maintained than in the previous month; however, it did not provide any clues as to the cause of the existing errors.

"To find the sources of error, I would have had to roll up the entire process step by step at great expense"

criticizes Patricia Venzlaff.

In search of a solution for the efficient measurement and process-oriented optimization of data quality, the cbs Master Data Validation (cbs MDV) software was recommended to the management.

Tanja Ott

The Heidelberg-based SAP consultancy cbs Corporate Business Solutions proved to be the ideal partner for Franke. The cbs project team analyzed the current approach, defined the requirements together with the users and implemented them prototypically with the new release cbs Master Data Validation for SAP ERP & S/4 Hana 1.5.

"The software is easy to introduce"

praises Venzlaff:

"Everyone on the cbs project team understood the issues from both a management and technical perspective. In this way, ideas and solutions emerged that we would never have thought of ourselves."

Since customer and supplier data were initially not to be included in the analysis, the project was limited to Franke's material master data - and thus to 350,000 articles with data on around 2.5 million production orders, 1.2 million purchasing document items and almost 20 million sales document items.

In addition to optimizing the data quality, the where-used list and determining the reproduction costs for the material master data were on the agenda. Just under three months later, planning and implementation were successfully completed.

Since then, Venzlaff no longer needs to perform master data maintenance and data analysis in time-consuming manual work. Instead, she extracts the data on a monthly basis according to defined rules that she creates in cbs MDV's intuitive cockpit.

This SAP-based control center does not require a separate interface to the database and works easily with the fields that have already been defined. The master data manager can, for example, store routines to find out whether a stored value is valid - and track down errors more quickly in this way.

Demand-oriented evaluations can now also be carried out with little effort and make even complex correlations visible. With just a few mouse clicks, for example, you can determine the total weight of a product by adding up the weights of its components.

"What makes the work especially easier: that with the new where-used list I can check which master records were used at all."

Patricia Venzlaff emphasizes.

"So I can exclude very new items or very old items where that usage is particularly low from the analysis - and I can easily specify that in the cockpit, too."

When Venzlaff is asked when she will be finished with the master data cleanup, she smiles. Master data maintenance is an ongoing process that is never finished.

Firstly, because data is constantly changing: Addresses or account numbers change, the product range and customer base grow, or a change of supplier takes place. Secondly, the demands on master data analyses are increasing.

Therefore, Franke has recently introduced the release cbs MDV 2.0 SP005 and thus completed the last stage on the way to optimization for the time being. With the cbs MDV Reproduction Costs module, it is now finally possible to determine the costs for the creation and maintenance of its master data and to include them in the company value.

Solid foundation for optimized data quality

"The software is easy to implement. With cbs MDV, we create a solid foundation to continuously improve our master data quality in a process-oriented manner. This solution helps us to identify errors and their causes more quickly. This has enabled us to significantly improve the transparency of our master data."

sums up Venzlaff.

With the new analyses of the data, it has already been possible to optimize some processes.

"For example, we found that the data quality in one area of the business was below average"

explains the master data expert.

"As a result, we had the information in question maintained, first, by another department and, second, earlier in the process. This simple measure noticeably improved the quality of our master data within a month."

Project Franke

  • The monthly measurement of master data quality was largely done manually in Excel. This was extremely time-consuming, ineffective and not meaningful.
  • The company wanted to improve the quality measurement of master data and therefore uses cbs Master Data Validation for SAP ERP & S/4 1.5, a comprehensive standard software for the evaluation, monitoring and optimization of master data.
  • In cooperation with cbs, a customized solution was developed that allows master data to be analyzed in a process-oriented manner, according to freely definable rules.
  • In further steps, additional modules of cbs MDV were introduced, with which the where-used list for material master data and the reproduction costs can be determined.
  • The solution has reduced the effort required to measure the data quality index and provided the basis for improving material master data quality.
Tanja Ott, cbs

Tanja Ott is Consulting Director in the area of Business Application Technology at cbs Corporate Business Solutions. She supports companies worldwide in the area of SAP Custom Development.

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