What is Master Data Governance?
Master data governance includes all strategic, organizational, methodical and technological activities concerning corporate master data.
The goal is ensuring high data quality as well as consistency.
Master Data Governance gets smooth processes going
The digitalization of processes requires data quality to be up to par, starting with up-to-date, accurate and complete data. Only data that conforms to system-specific guidelines can be processed automatically.
Data has to be consistent and free of redundancies. Duplicates inflate data volume unnecessarily and increase the risk of errors as well as processing costs. Complying with guidelines for master data quality is hard enough, even without the additional effort of eliminating duplicates.
Master data governance also means integrating a suitable IT solution, new processes and organizational structures with clear guidelines and rules. Companies can – and should – model the creation of master datasets and define individual approval and authorization processes. Only then will they be able to keep their master data quality on a high level in the long term.
Master data governance accelerates automation
With the same measures and methods, companies can also support and automate other business processes. Precise texts can be automatically transformed into data and processed as orders, online shop information or descriptions of spare parts.
Industry 4.0 creates a range of new requirements, such as creating serial numbers for industrial parts and products, ensuring complete traceability of parts, and providing information on quality including documentation. Defined processes with integrated evaluation options provide fast and seamless workflows in line with industry standards.
The concept of master data governance seems to be capable of eliminating the lack of quality in master data effortlessly. Through consistent monitoring and automated corrections, master data governance ensures a high level of security in a variety of digital processes.
How do Master Data Governance solutions by simus systems work?
Phase 1: Cleaning and restructuring master data
To implement a master data governance project, it is recommended to clean and restructure master data with specialized tools as, in this case, they are more efficient than an ERP system. In order to use the cleaned data in an efficient way, the recommendation is to employ a suitable “search engine”. This is how companies benefit the most from the structured data pools.
Phase 2: Workflows to organise creation of new material data
The professional creation of a material master has an extensive impact on all business departments. Companies securing their data regularly achieve noticable cost and time savings. Through an elaborate process, duplicates and errors in the material master can be prevented.
Phase 3: Maintaining the material master for long term success
Creating alongside maintaing the quality of material master data should be organized in an orderly and sustainable way. simus classmate provides you with a mature software solution to manage all required changes during the product life cycle.
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Why should companies implement an additional system on top of the ERP software?
Because it is flexible, quick and easy to comprehend.
By using rule-based algorithms, simus systems is in the position to adapt the product to suit your company’s needs. It is not limited to the abilities of a certain programming language. Process dependencies are easily mappable and controllable at any time.
The expenditure of implementing an additional system armortizes in no time by the huge savings on work routines. During the implementation process of simus classmate, our experts are available to answer questions and provide support.