SAP Master Data Governance (SAP MDG), is SAP’s solution for data management, designed to fit naturally into your SAP Landscape Solution. It can help you consolidate the entire master data lifecycle from a central location. SAP MDG works effectively with ERP and S/4HANA to address all aspects of data governance needs, creating a seamless MDG experience.

For SAP models that are currently in place, the SAP MDG Program can be easily implemented as a new Hub, created on a separate, internal server, or it can be embedded in an existing SAP Box or Hub.

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The SAP MDG program can also be used to optimize non-SAP systems. Because it’s offered as free software with licenses based on number of records to be managed, SAP MDG can be utilized with non-SAP systems as an add-on system tool and can be deployed On-Premise. Being deployed On-Premise means the solution remains installed on a company’s own servers and behind its firewall, or Cloud, which offers increased flexibility, agility, and scalability for enterprises.

Whether your company is already part of an SAP system or is looking to implement SAP data management, the SAP MDG Program is ready to use out of the box for most common master data objects such as Customers, Materials, Suppliers, Financial Objects in General, and Asset Objects as a 3rd party solution which includes components such as Equipment Master and Bill of Material, for example. Other master data objects can be built on this platform as well to provide further customization and personalization for your company.

The SAP MDG program combines various components that improve data quality, integrity, workflow, and flexibility for your company. Whether your company wants to implement a Central or a Federated data governance model, the SAP MDG program is highly flexible and can work with however the data governance program will be operationalized across the organization.

Standard and custom workflow models for data maintenance can be integrated into the MDG program to allow the organization to precisely control the maintenance process. It also allows for the tracking of various workflow models as well as where in the process the data maintenance is.

Data quality is another key component of MDG. Data quality ensures that master data is fit for the intended purpose and correctly represents the real-world construct that the data describes. Data Quality management is a set of practices that focuses on maintaining high quality information and is involved in every part of data, from acquisition, to implementation of data processes, through to an effective distribution of data.

Data quality involves rule management and mining, DQ evaluation, analysis, and remediation. These processes are utilized in SAP’s MDG program to ensure the highest quality data so that the output is accurate, reliable, secure, and usable. One example of this is address validation using guidelines from USPS which ensures correct address for customers and vendors.

Extended data validation, data consolidation, mass data processing, extended audit reports and analytics, round out the components of successful MDG programs. These measures help to increase transparency, detail, and disclosure so that data is governed and integrity maintained.

Data quality involves rule management and mining, DQ evaluation, analysis, and remediation. These processes are utilized in SAP’s MDG program to ensure the highest quality data so that the output is accurate, reliable, secure, and usable. One example of this is address validation using guidelines from USPS which ensures correct address for customers and vendors.

Extended data validation, data consolidation, mass data processing, extended audit reports and analytics, round out the components of successful MDG programs. These measures help to increase transparency, detail, and disclosure so that data is governed and integrity maintained.

SAP MDG: Addressing the Current ERP and Pain Points

One consideration that SAP data governance management makes is management of pain points within the company when it comes to the ERP implementation. ERP is the designation given to a class of business software intended to facilitate the processes of a company end to end.

Enterprise Resource Planning can help address a business’s pain points, or an issue that is causing problems within a company that requires a solution. These issues are often systematic and affect the bottom line and therefore, require a successful, immediate solution to limit inhibitions to the growth of a company.

Pain points related to lack of Master Data Controls occur in all areas of a company, including but not limited to, order to cash, procure to pay, finance to report, manufacturing, e-Commerce, and architecture and systems integration.

Pain points can then be organized into categories including positioning pain points, productivity, financial, people, process, and productivity.

By implementing the SAP MDG, your business can evaluate the current ERP practices and pain points causing issues both internally and with customers. SAP’s ERP program offers an integrated system that works in combination with other systems to create a reliable and centralized management system for all business needs.

Current Data Market Landscape

Data governance remains a crucial part of industry. It provides a framework for making data available, applicable, whole, and secure. Therefore, data governance remains an industry trend for constant improvement. However, the process of data governance and management has been increasingly viewed as a bridge between IT and business associates, and this shows the inter-departmental importance of data. Not only is the IT department working with and optimizing data, but anyone who is responsible for creating data or managing data must understand the rules, regulations, and importance of clean, useable data.

By taking advantage of new technology, data analysis has become increasingly insightful. Implementing a data management system that provides one space to manage various kinds of data throughout the data cycle can streamline and simplify the process needed to maintain and monitor data.

Data acquisition is an important process for companies looking to utilize and leverage data about real-world experiences. This process provides further data for analysis and is a part of master data that can be created, stored, and used to gather more information about a given real world experience. Using quality data for acquisition, for example, can help a company identify potential internal problems and to gain a full picture and understanding of all the operations within any business.

While data governance rules and regulations are constantly being updated, the key factor to keep in mind for any data is security and accuracy. Making sure that the company complies to all data regulations is important for avoiding issues both within data management programs and with outside parties. Maintaining the integrity of data is the main consideration for any company and creating reliable data means building trust with data stewards and other parties.

Benefits of MDG for Your Business

When implementing reliable MDG models and programs, is a multi-department and multi-workstream task that requires business and technology efforts with focus on data management. It is best to handle as an independent project bringing all business areas together and having business sponsors and an assigned budget. If planned correctlyan MDG project may result in proven ROI in many areas of the company and be justified with sponsors.

The benefits far outweigh the costs, and having a compact and centralized system can boost employee usage confidence, company growth, and confirm data integrity and security.

For most companies there are high costs that come with maintaining data for a multitude of reasons: unclean or flawed data can lead to significant unexpected costs due to the need for the data to be recleaned and fed back into the system. Also ensuring data quality at the highest level and maintaining that data can lead to higher costs. SAP’s MDG program helps to limit or eliminate these kinds of errors by creating one management center that monitors your data at every step.

MDG can also help to solve those pain points that are bound to cause issues in any company. By helping your company evaluate and identify which pain points are being sustained by your data and data management, you can quickly develop solutions that solve these issues.

With new, more advanced ERP systems such as S/4HANA, it is crucial that the data being used is consistent and reliable for these systems to properly function.  Data security and governance relies on and assumes that the integrity of data is intact and that making an investment in new technologies will only work if you feed them clean, reliable data. These systems can then help manage and organize that data to ensure that the analytics received are accurate and lead to growth.

Pitching SAP MDG to Executives

Learning how to leverage data and data governance ensures that you improve business outcomes such as gained trust and compliance, identifying new opportunities through data analysis, addressing regulatory requirements and, the most important aspect of data management, ensuring security and integrity. The Return on Investment while using the SAP MDG program has proven that both time related and non-time related savings can occur from the use of MDG.

Master data governance encourages collaboration between the business, who owns the master data, and IT sponsors, who provide the tools. By establishing rules, responsibilities, processes, and KPIs, you can plan a phased approach to help you successfully maintain, utilize, and understand the master data that you are working with to help build a business case, while prioritizing goals that are significant, achievable, and successful (fostering organizational confidence and continued support).

Additional Technology Aspects

There are other technologies that lend themselves useful to management of master data. Various modern open interface technologies are useful because of their ability to support data governance throughout various aspects of a company’s technology process and applications. SAP’s MDG solution can work efficiently along with non-SAP systems thanks to its open architecture.

SOA stands for a “Service Operated Architecture.” Essentially, SOAs help define ways that software can be reused within service interfaces, and instead of using unique communication systems that make them hard to transfer and reuse, they communicate using common standards that avoid deep integration each time on a new project or application. The benefit of being able to reuse service interfaces, rather than rebuilding them every time means greater business agility and a faster time to market, increased legacy functionality, and improved collaboration between business analysts and developers, to help gain more effective and accurate insights.

API stands for “Application Programming Interface,” and it is a software that acts as an intermediary between two applications, allowing them to communicate with one another. APIs offer an extra layer of security, because the two applications are never fully in touch with one another; instead, each application requests and receives only the essential information that it needs to fulfill a request. Because APIs have advanced in recent years, they have become more developer friendly and standardized, resulting in a greater discipline for security and data governance. Increased standardization has also led to greater documentation of the product lifecycle and its expectations.

By using various technologies to help further the accuracy and legitimacy of your data, your company can maintain cutting-edge analysis to help inform business decisions. Not only this, but in using various technologies to improve the quality of your data, you build trusting client relationships and build brand reputation. Data governance is key to staying ahead of the pack and maintaining the best data.

Contributions by Arturo Blasi and Ashley Stufano.