Single Source of Truth (SSOT)

1. What is Single Source of Truth (SSOT)?

Single Source of Truth (SSOT) is a concept in data management, in which information models and associated data schemas are structured in such a way that each data element is managed (or edited) only in a single location, which ensures data normalization in canonical form. It is not a specific technology, tool, or strategy, but rather a state of corporate data in which all data can be found via a single reference point.

The primary purpose of SSOT is to ensure that all stakeholders in an organization make their business decisions based on the same data. This removes discrepancies, reduces errors, and ensures everyone in the organization has access to the most accurate and up-to-date information, which supports better decision making.

The data typically collected in an SSOT system includes:

• Customer data and interactions
• Product information
• Company policies and documentation
• Process definitions and workflows
• Financial information and key figures
• Internal knowledge databases

2. Distinction from similar concepts

It is important to differentiate SSOT from similar data management concepts:

Master Data Management (MDM): MDM is a process that helps create an SSOT by managing master data. While SSOT is the concept or goal, MDM is an approach to achieving that goal.

Data warehouse: A data warehouse is a central repository for integrated data from various sources. It can serve as a technical implementation of an SSOT, but it is not synonymous with the SSOT concept itself.

Content Management System (CMS): A CMS manages digital content, but unlike SSOT, it can have multiple versions of the same content and focuses primarily on published content rather than all company data.

Enterprise Resource Planning (ERP): ERP systems integrate various business processes and can serve as part of an SSOT approach, but do not necessarily cover all data domains.

3. How is SSOT implemented? (methods and examples)

Implementing an SSOT system requires careful planning and can be done in various ways:

Method 1: Data warehouse or Data Lake Centralized data stores can serve as the basis for an SSOT.

instance:A financial services provider collects data from all customer transactions, web interactions, and support requests in a data lake, which serves as a central source for analysis and reporting.

Method 2: Master Data Management (MDM) An MDM tool serves as a hub for an organization's master data.

instance: A retailer implements an MDM system in which all product data is managed centrally. Changes to product descriptions, prices, or availability are first made in MDM and then synchronized to the online shop, POS systems and mobile apps.

Method 3: Enterprise Service Bus (ESB) An ESB allows many systems to receive data updates from other systems.

instance: A company implements an ESB, which automatically transfers changes to customer data (e.g. new addresses) in the CRM system to the ERP, support ticket system and email marketing tool.

‍Method 4: Cloud-based collaboration platformsTools such as Confluence, SharePoint, or specialized knowledge databases.

instance:A software company uses Confluence as a central documentation platform for processes, guidelines, and product knowledge, eliminating silos in emails and local files.

4. What makes for a good SSOT?

An effective SSOT has the following characteristics:

• Accessibility: All authorized users can easily access the data.
• Topicality: Data is updated promptly and reflects the current status.
• Consistency: Data is free from contradictions and follows uniform standards.
• Comprehensiveness: All relevant information is available in the system.
• Precision: Data is accurate and reliable.
• Surety: Appropriate access controls and data protection measures have been implemented.
• Scalability: The system can keep pace with the growth of the company and increasing amounts of data.
• Integrability: The system can be connected to other business applications.

5. Areas of application and optimization

SSOT can be used in various areas of a company:

• ‍Customer management: Unified view of customers across all touchpoints (360-degree customer view).
• ‍Product management: Consistent product data for marketing, sales, e-commerce, and support.
• ‍Finance: Centralized financial reporting and analysis for well-founded decisions.
• ‍Human resources: Uniform employee data for personnel planning, performance appraisal and administration.
• ‍Knowledge management: Centralize business expertise, documentation, and best practices.
• ‍Compliance and risk management: Uniform database for compliance with regulatory requirements.

The following measures can be taken to optimize an SSOT system:

• Regular data cleansing and validation
• Automate data integration processes
• implementation of Data quality checks
• Training employees to maintain data correctly
• Regular review and update of data structures
• Klare Governance processes for data access and changes

6. Benefits of SSOT

There are many benefits of implementing an SSOT:

• ‍Improved decision making: All decision makers work with the same reliable data.
• ‍Higher efficiency: Reduced effort for data search and reconciliation, less time to correct data errors.
• ‍Increased data quality: Fewer redundancies and inconsistencies result in more trustworthy data.
• ‍Better collaboration: Teams can work together more easily when they have access to the same information.
• ‍Simplified compliance: Uniform database makes it easier to comply with regulatory requirements.
• ‍Cost reduction: Fewer resources for data maintenance and correction, fewer costly errors due to incorrect data.
• ‍Agility and Innovation: Freeing up resources for innovation instead of managing and correcting data.

7. Disadvantages and Limitations of SSOT

Despite the many benefits, there are some challenges and limitations:

• ‍Implementation effort: Setting up an SSOT requires significant resources and time.
• ‍Cultural change: Employees must change their way of working and get used to new processes.
• ‍Single point of failure: If there are technical problems with the central data source, all dependent systems can be affected.
• ‍Complex migration paths: Integrating existing legacy systems into an SSOT can be technically demanding.
• ‍Governance challenges: Clear rules for data access, change, and ownership must be established.
• ‍Scaling issues: Performance problems can arise as the volume of data and the number of users grows.
• ‍Compromises with special requirements: Central systems cannot always meet all the specific requirements of individual departments.

8. FAQ about Single Source of Truth

How is SSOT different from Source of Record?

SSOT refers to the concept that there is only one authoritative source for each data point, while “source of record” refers to the specific system that serves as an official storage location for specific data. A company can have multiple sources of record (e.g. HR system for employee data, CRM for customer data), which together form the SSOT approach.

How do I start implementing an SSOT in my company?

Start by taking stock of your current data systems and processes. Identify areas of data inconsistencies or duplicates Define the authoritative source for each type of data and then develop a step-by-step plan for integration or consolidation, starting with the most critical business data.

Is a data warehouse the same as SSOT?

No, a data warehouse is a technical system for storing data, while SSOT is a concept or philosophy for data management. A data warehouse can be part of an SSOT strategy, but SSOT also includes processes, governance, and organizational aspects.

How do I deal with data that is stored offline or in legacy systems?

Integrate this data through APIs, extract, transform, load (ETL) processes, or middleware solutions. User-defined interfaces or regular batch synchronizations can be implemented for important legacy systems without modern integration options.

How do I measure the success of my SSOT initiative?

Success can be measured through metrics such as reduced error rate in reports, shorter time to search and consolidate data, higher user adoption, or direct business benefits such as faster time to market. Establish baseline measurements before implementation and track improvements.

Does ALL company data really have to be stored in a single system?

No, SSOT doesn't necessarily mean a single physical system. It is more about the existence of a clearly defined authoritative source for each data type. This can consist of several interconnected systems as long as clear rules for data ownership and synchronization are set.

How can I ensure that my SSOT stays up to date and relevant?

Implement continuous data validation processes, automated quality controls, and regular audits. Establish clear responsibilities for data maintenance and ensure that changes to business processes also lead to appropriate adjustments in the SSOT.

9. Conclusion Single Source of Truth

Single Source of Truth (SSOT) is a fundamental concept in modern data management that helps organizations provide consistent, accurate, and reliable data for informed decisions. By centralizing data and ensuring that every piece of data is managed in just one place, companies can break down data silos, improve collaboration, and increase operational efficiency.

Implementing an SSOT requires careful planning, appropriate technologies, and cultural change in the organization. Despite the challenges, the benefits in the form of better decision-making, higher data quality and increased efficiency clearly outweigh them.

For a successful SSOT strategy, it is crucial not only to consider the technical aspects, but also to establish clear governance structures, processes and responsibilities. With the right approach, SSOT can become an important competitive advantage in the data-driven business world.

Related terms: Master Data Management (MDM), Data Governance, data integration, Data warehouse, Enterprise Service Bus (ESB), data quality management, information architecture, Data Lake