Data Harmonization: Definition & Meaning for Companies

Key Takeaways: What is Data Harmonization?

• Data standardization creates a consistent database that increases efficiency and transparency in business processes.
• Uniform and standardized data facilitates collaboration between departments and locations.
• International companies benefit from a global data structure that efficiently controls cross-border processes.
• Increased efficiency and resource optimization are key benefits of a standardized data structure.
• Similar data is the key to better collaboration and reliable information management.

Introduction

The standardization of data plays a central role in today’s corporate world. But what exactly does this mean? In short, the harmonization of information to be transferred describes the process of bringing data from different sources into a consistent form.

Companies have to adapt numerous data records from several systems so that they can be used uniformly and unambiguously. This is particularly important if a company operates at several international locations.

Employees in all locations and departments should be able to access the same, correctly interpreted and used information in order to avoid misunderstandings and errors. Why is this step so important?

Efficient data structures, where existing data is consistent across all systems, lead to optimized data management. It ensures smooth collaboration, reduces the workload and saves time and costs.

In this article, you will find out why standardization is a success factor in companies and how it contributes to the optimization of business processes.

Definition: What ist Data Harmonization?

Data standardization means bringing different information from different sources into a consistent and clear structure. This includes the analysis, in which data is first analyzed and its data fields defined.

Different systems use different data types for the same information, and a uniform understanding of these data types is required. The central challenge is to define data sets in such a way that all participants receive the same information content.

A company often works with many data sources that are created by different departments, locations and systems. For example, some systems only store one object for business partners such as customers and suppliers, while other systems use their own business objects for customers, prospects and suppliers.

These differences often lead to inconsistencies and make data standardization difficult. A global structure for business processes across application boundaries without media disruptions is necessary so that the data can be used and interpreted in all departments. Data management not only includes harmonization, but also clear mapping between the systems.

Uniform and consistent: the importance of data harmonization

Uniform and standardized data such as payment terms are crucial when it comes to data quality and consistency. A consistent data model is the basis for clear and efficient communication within a company.

A company-wide understanding of the data makes it possible to use the information correctly and sensibly. Employees from different departments and locations can access the same information and interpret it correctly.

One example of similar data formats is the use of a central model for customer data. Here, standardized fields such as name and address are stored uniformly in all systems used. This standardization allows information to be used in a harmonized manner and processed seamlessly.

The prerequisite for error-free use is that data is created once (“Create Once”) and used in all applications (“Use Everywhere”).

Data harmonization as a success factor for companies

The standardization of information is a key success factor. It creates a basis for reliable and transparent business processes. The harmonization of transferring information in business processes is often underestimated, although it can contribute significantly to increasing efficiency and avoiding errors. Harmonization ensures that all departments work with the same data records. Well-coordinated data management is therefore a competitive advantage.

Efficient data processes and resource optimization

Standardized data processes help to make workflows more efficient and make optimal use of resources. If data records are uniformly structured, they are easier to process automatically, which reduces the need for manual intervention.

Another advantage is the reduction of redundant information, as departments can access the same data and do not have to enter the same information multiple times.

The “Best of Breed” Approach: Optimal software solutions for specific tasks

A “Best of Breed” approach means that companies select the best software solutions for different business areas instead of relying on a comprehensive all-in-one platform. This approach offers the opportunity to rely on specialized systems for specific tasks such as CRM, ERP or data analysis, which are particularly powerful in their respective functionality.

However, this approach also brings challenges. When using several specialized systems, data must be harmonized and coordinated to ensure smooth processes. Strong data management is required to ensure error-free use across system boundaries.

It must be ensured that information from the various applications is consistent and can be used across application boundaries without media discontinuity. The standardization of data structures and efficient mapping of information is crucial here.

The “Best of Breed” approach can thus give companies a clear competitive advantage, as it makes optimum use of the strengths of specialized systems and at the same time creates the conditions for an efficient, harmonized data structure.

Challenges and opportunities for international locations

The standardization of data poses a particular challenge for internationally active companies. International locations often use identical applications, but these are configured completely differently and adapted to local requirements.

This means that the same data may be available in different systems in individualized and varying form. The situation is further complicated by several inconsistencies in the data records.

A global data structure makes it possible to use information coherently worldwide and implement adjustments more quickly.

This enables companies to ensure that all locations access the same quality-assured data and use it without media disruptions. The workflow between locations is also improved as the requirements for application integration are met.

Opportunities and potential of international data harmonization

The standardization of international data offers great potential, as it enables processes to be managed coherently worldwide.

The greatest common multiple and the least common multiple must be defined in the global context so that the respective systems can exchange the data correctly.

A standardized understanding of company information allows the data model to be designed in such a way that it is accepted company-wide.

Data harmonization as the key to better collaboration

Similar data promotes collaboration between departments and locations. Employees from different departments can interpret and understand the data without any misunderstandings.

To ensure that processes are understood identically, it is sufficient to create a common data structure from A to Z and to clean it up regularly. A successful data structure also enables better integration of the various systems.

The aim should be to capture data once and then use it in all relevant applications (“Create Once, Use Everywhere”). This minimizes the effort required for data maintenance and improves data quality.

The importance of Master Data for SAP, ERP, DAM and PIM systems

Master Data is the foundation of numerous business processes and comprises essential information about products, customers, suppliers and other central business units. In companies, this data is often used in different systems:

SAP and ERP systems manage financial and logistical processes, while DAM (Digital Asset Management) systems store digital content such as images and videos and PIM (Product Information Management) systems provide comprehensive Product Information for marketing and sales.

The use of all these systems makes a central source of master data necessary to ensure consistent and comprehensive data access.

Harmonization of master data for a uniform database

To ensure that master data remains consistent and up-to-date across systems, comprehensive harmonization of this data is required. The aim is to synchronize information such as product descriptions, customer profiles and supplier details so that they can be used in all systems without deviations and inconsistencies.

This reduces the workload for manual adjustments and significantly increases efficiency. A harmonized master data structure creates a Golden Record in the “Single Source of Truth”, which enables companies to access a uniform and reliable database.

This optimizes business processes and enables companies to deploy their resources in a targeted and successful manner.

The Role of Data Governance in Data Harmonization

Data governance plays a central role in the harmonization and management of master data across different systems, such as SAP, ERP, DAM and PIM. It encompasses the processes, responsibilities and policies that ensure data remains consistent, accurate and secure across the organization.

Without clear data governance guidelines, it is difficult to create a uniform database, as different departments and systems could apply their own data standards and practices.

Conclusion

A standardized data structure is a key success factor for modern companies. By consolidating and harmonizing information, work processes can be optimized and efficiency increased.

Companies that align their information processes are better prepared for the challenges of digitalization. A consistent database forms the basis for smooth and efficient information management and helps to ensure that information can be used reliably in all departments and systems.

Investing in a shared data structure pays off in the long term – in the form of greater efficiency, better collaboration and a higher quality standard for company data.