As you are surely aware, if you have come across this article, master data in SAP is a fundamental pillar for the efficient operation of any company. Since master for multiple modules or business areas, its creation and maintenance involve multiple participants, such as the purchasing team, finance team, compliance team, and master data team itself.
And then, there is an unfortunate truth: in the standard process for master data creation, SAP lacks robust governance functionality.That is why companies often implement artificial governance using complex Excel templates, shared via email to involve all responsible parties. Others develop custom external systems that ultimately generate Excel files, which, due to a lack of SAP integration, result in batch input processes filled with errors—requiring hours of analysis and correction by the master data team.
The keys to successful data governance in SAP
When implementing successful master data governance in SAP, it is possible to avoid inconsistencies and duplicates, ensure data accuracy, and, of course, comply with company and external regulations.
To achieve this, it is essential to:
- Accurately define policies and standards
- Establish a clear process for data creation, validation, and maintenance
- Effectively assign roles
Design and implement a tool to execute the process.However, this task often presents various challenges, which we will address in this article. Additionally, we will introduce you to the best available solution on the market for achieving successful data governance, since the standard solution does not always provide all the necessary tools to manage data optimally.
Challenges in master data governance in SAP
Next, we will analyze the most common challenges that SAP users face regarding master data governance.
Define the workflow
Master data creation, particularly for materials, involves multiple participants across various departments, including purchasing, finance, logistics, compliance, and the master data team. Each of these teams plays a distinct role, contributing specific pieces of information to ensure the data is accurate and aligned with business requirements. Without a clearly defined workflow, the process can become disorganized, leading to errors, inefficiencies, and compliance risks.
In this workflow, different participants have varying levels of responsibility. Some are tasked with entering data in specific views, such as purchasing or finance, while others are responsible for reviewing attachments and granting approvals. Additionally, certain roles involve creating related data, such as Bills of Materials (BOMs) or routing information. A critical part of the process is ensuring data integrity, which includes verifying duplicate materials or vendors, checking compliance with restrictive lists, and ensuring that all necessary validations are completed before proceeding. To prevent confusion and redundancy, each participant must understand their role and when their input is required.
Since the master data creation process follows a strict sequence, defining the workflow is critical. Establishing clear steps ensures that each task is completed in the right order, preventing delays and rework. A well-structured workflow not only improves efficiency but also enhances data accuracy, governance, and compliance, ultimately supporting better decision-making across the organization.
Notifications Save Time
Defining roles is not enough. All participants need to know when it is their turn to contribute, and receiving a notification at the right time is essential. Without proper coordination, delays can occur, leading to inefficiencies and missed deadlines.
When each participant is aware of their responsibility but lacks visibility into when they should act, tasks may remain pending for extended periods, creating bottlenecks in the process.
Traceability: The First Step to Optimization is Measurement
When multiple people are involved, the process can take longer. Master data typically has an SLA to meet, making it essential to include a way to track each step. This includes identifying back-and-forth processes, understanding the reasons behind them, measuring the time each step takes, and pinpointing where the process currently stands. Without proper monitoring, inefficiencies can go unnoticed, leading to delays.
A robust tracking system provides visibility into the entire process, making it easier to detect bottlenecks and inefficiencies. By analyzing where and why delays occur, companies can take corrective actions, such as redistributing workloads, adjusting workflows, or implementing automation. Additionally, tracking helps prevent redundant work, as participants can see exactly what has been completed and what still requires attention, reducing errors and unnecessary rework.
Beyond efficiency, traceability plays a critical role in compliance and governance. Many industries have strict data management policies requiring companies to maintain clear audit trails of all changes made to master data. By tracking each step, organizations can demonstrate accountability, ensuring that all actions are documented, authorized, and performed within the required timeframes.
Third-Party Engagement
When it comes to vendor records, the challenges of multiple participants, Excel templates, and email exchanges become even more complex. The process often requires vendors to provide critical information and submit documents, typically through a form. However, instead of seamless integration, a company user must manually transcribe this data into the system, increasing the risk of errors, inconsistencies, and missing information. This lack of automation not only slows down the process but also adds unnecessary administrative overhead.
Manual processes and lack of automation
The problem of manual data entry is not the only challenge in master data governance in SAP. In many companies, general data handling processes in SAP are also manual and, which causes inconsistencies and affects the quality and reliability of information.
With no automated workflows, each department can manage information differently, leading to contradictory or outdated data. This causes data to become unreliable and processes to be inefficient.
A solution to optimize data governance in SAP
To address these issues in master data management of materials and vendors in SAP, at Innova we have developed two solutions specifically designed to improve processes within the SAP system. Below, we explain how they work and how they address the mentioned challenges.
Solutions for master data governance in SAP: SiDM Materials and SiDM Vendors
To improve data quality, reduce processing times, minimize errors, automate workflows and approvals, and update information efficiently—in short, to ensure effective master data governance in SAP—at Innova we have developed two solutions:
- SiDM Materials, for managing materials master data
- SiDM Vendors, for managing suppliers master data
Both solutions are designed following best practices in master data governance within the SAP ecosystem. Moreover, by working directly with the SAP system, without the need for costly or complex integrations, we ensure a faster return on investment, avoiding slowdowns during adoption and implementation. Let’s take a closer look at what each solution offers:
SiDM Materials. Managing materials master data
- Avoids duplicates: Identifies and corrects duplicate materials through automatic comparison of fields like EAN, OEM, and descriptions.
- Data validation: Applies customized rules to ensure materials are created with accurate and consistent information.
- Custom workflows: Allows the creation of tailored workflows and notifications with specific roles to validate and approve data before use.
- Automation and standardization: Synchronizes data across multiple plants and manages large-scale migrations and changes, ensuring data remains up-to-date and accurate.
SiDM Vendors. Managing suppliers master data
- Vendor Web Portal: Facilitates the direct upload of data by suppliers without the need for SAP access (and in compliance with SAP), eliminating manual processes and errors.
- Automation and Validation: Custom workflows to review and approve data, with automatic notifications and direct approval options within SAP.
- Centralized Document Management: Stores documents in external DMS systems (SharePoint, Azure, AWS S3), ensuring traceability and regulatory compliance without affect SAP database.
In short, these solutions transform master data management in SAP, offering key benefits such as improved data quality and consistency, reduced operational costs and errors, accelerated processes, guaranteed regulatory compliance, and offering something that SAP standard don’t Data governance—all with quick and easy adoption.
