The foundation for the digital automation of modern business processes is Correct SAP Master Data. Therefore, companies that map their business processes based on SAP systems should pay close attention to master data management.
Incorrect or outdated data causes problems in the processing of SAP applications, and in the worst case, can lead to a complete stop of your business processes. In this area, one of the effective ways is to use Synopps MDM optimization. As the volume of data explodes, MDM has developed into one of the most exciting areas in the global IT market.
All confirm that master data management has reached the top of the IT agenda in many companies.
Data-driven business models in times of digitalization rely primarily on functioning master data management.
The structured maintenance of master data relating to entities such as customers, products, financial transactions, suppliers and business partners is becoming a major concern for companies.
On the one hand, this is a logical consequence of the digital transformation that has taken place in almost every industry. On the other hand, the optimization of SAP master data is a prerequisite for the digitalization of business processes.
The best management of master data in companies is to ensure that SAP business processes and transactions are consistent and accurate master data. The subsequent costs of incorrect master data are enormous.
This is because a lot of effort is required to restore an SAP system after it receives stale or redundant data. This extra work can be completely avoided with Synopps MDM optimization from the start.
Incorrect master data has disastrous consequences, especially in logistics and manufacturing processes. Duplication and unsupported master data in SAP can lead to incorrect deliveries and material bottlenecks, which in turn can lead to significant disruption to your material management business processes.
Ultimately, your employees should use manual workarounds to minimize the impact so that customer satisfaction is not compromised, and follow-up costs are kept to a minimum.
SAP’s Material Master is particularly complex and in need of focused training. If a setting such as Unit of Measure for the material is set wrong, there is not an easy fix. Understanding the settings and the downstream implications of those settings is essential.
Without that understanding, we see broken processes, custom code unnecessarily in place, and costly mistakes. Once you have a clear understanding of your master data, it is essential to put in place governance for each business object. A key business process owner is needed to be sure the data stays clean and free of duplication.
When implementing and running SAP software, a substantial amount of time and emphasis needs to be spent on understanding the implications of setting up clean and correct master data.
In addition, with SAP material master views, irrelevant fields are not even displayed, which helps to avoid errors when creating a material. If necessary, additional documents and specifications can be attached to the request.
let’s say the central department in your organization is responsible for validating and releasing newly created master data records to SAP. This main SAP data center receives new requests through an automated workflow – it validates them and, if necessary, returns them back to the submitter if the original data record contains errors.
One of the greatest challenges in master data maintenance is the cross-site MDM in distributed organizations. While some data fields are globally valid, others differ. Due to special information solutions, different plant views can be defined and the solution will automatically create the relevant views for the defined plants.
Organizations need to identify that a majority of active business processes have intersecting function boundaries. Several personnel are involved in the collaborative workflow processes for generating master data along with executing the business processes.
Cross-functional master data processes in enterprises usually generate the issue of process ownership, since organizations are conventionally built around function.
In addition, SAP MDG manages high volumes of data. It lays the foundation for big data management and enables data to be used to optimize business value. SAP MDG automates and accelerates maintenance and operations transactions.
It also serves as a repository for all information. Where the data circulates within the chain. The ERP system provides data that is adjusted and consolidated to achieve the MDGs. This is where data and changes are made, and data is still propagated through Process Integration (PI).
Even though data may only be stored and managed from one centralized location, organizations can still gain from the reuse of data utilizing data sharing managed from within a master data repository.
The quality and usability features of the master data must be multi-purpose, meaning organizations need to ensure cross-functional needs are recognized from the entire set of master data consumers. It also means that those needs will be able to be observed throughout all the data lifecycles associated with the cross-functional processes.
A horizontal view of the workflow processes within an organization is necessary to identify data producers and data consumers. This is a central requirement to properly measure data needs and expectations for quality, usability and availability.
The successful solutions can revolutionize the way a company works in terms of increased opportunities, decreased operational costs, and an improved level of trust in generated reports. Incorporation of the best practices ensures operational efficiency and organizational growth and needs to be kept in mind whenever instituting enterprise-wide changes.