Why integrate External Data Sources into Master Data Management (MDM)?

Why integrate External Data Sources into Master Data Management (MDM)?

In today's data-driven world, organizations are constantly seeking ways to enhance their decision-making processes, optimize operations, and maintain a competitive edge. Master Data Management (MDM) is a critical component in achieving these goals by ensuring that your organization’s core master data is accurate, consistent, and complete.

Integrating external data sources into MDM is one of the most powerful ways to improve your MDM system.

What is the gain and for what use cases?

Estimates suggest that 20-50% of master data within a company can be sourced from external sources. This means that integrating external data sources can significantly enhance the accuracy, consistency, and completeness of your MDM system.

We have made a classification to what goals the usage of external data sources can contribute in the following use cases:

• Data Enrichment
  • Ensuring faster and better completion of data for your end users.
• Data Accuracy, Consistency, and Quality
  • Guaranteeing that your master data remains consistent, accurate, and of high quality even when business rules change.
• Data Compliance
  • Meeting governmental regulations and internal policies that drive the need for integrating external data.
• Data De-duplication
  • Improving the uniqueness of your master data upon manual requests and continuous uniqueness verification on existing data.
• Proactiveness in Data Management
  • Pushing changes from external data sources into your systems for quick and efficient updates.

Combining external data sources with Artificial Intelligence (AI) capabilities will further improve these use cases.

Some Real-World Examples

As the above use cases might sound a bit theoretical, we have listed some of the real-world implementations we have worked on:

• Data Enrichment
  • Based on a VAT number or even company name, we pre-filled the new request form for customers and vendors with the retrieved name, address, VAT information, etc...
• Data Accuracy, Consistency, and Quality
  • While you might introduce new data quality rules, you want those rules not only to apply to your changed data, but also the data that resides in your database for some time. Processes might be executed in your MDM system to automatically rectify that old data to your new business rules.
• Data Compliance
  • Calling the VIES database to verify and validate the obligatory check on your trading partners (see Directive - 2006/112 - EN - VAT directive - EUR-Lex (europa.eu)) Introduce automated Risk management checks within your onboarding processes for trading partners (see ISO 31000:2018(en), Risk management — Guidelines).
• Data De-duplication
  • Using AI (Artificial Intelligence) to detect duplicates more intelligently in your product database where unique identifiers such as GS1 numbers might not be available.
• Proactiveness in Data Management
  • Pushing fraudulent bank accounts or bankruptcy notifications from external data sources into your systems for quick and efficient updates.

Challenges

As you can see and feel, there are tremendous lot of manners how to integrate external data into your MDM implementation, however this also comes with some challenges.

So many external providers to choose from

Given the wide variety of available external data sources, finding the right external data provider and source for specific use cases can be challenging.

• Data coverage: Does the provider support your geographical regions or specific industries?
• Data Licensing: Understand the licensing terms and costs associated with the data.
• Data Quality: Evaluate the accuracy, completeness, and timeliness of the data provided.
• Compliance: Ensure the data usage complies with relevant regulations and standards (e.g., GDPR, ...).
• API Availability: Ensure the data provider offers robust APIs for seamless integration.

Stakeholder Engagement and Change Management

Discuss the importance of stakeholder engagement and effective change management in all of this, including:

• Communicating the benefits and potential impacts to all stakeholders.
• Providing training sessions and resources to ease the transition.
• Creating a feedback loop to address concerns and continuously improve the process.

Integration Considerations

Additionally, the integration process can become a nuisance if not managed properly:

• Pay attention to the difference in data models of the provider and your own systems
• Make sure the API is scalable and the required volume for your use case can be met
• Service Level Agreements by the external provider

By selecting the right data providers bringing value to your master data challenges and integrating them into your MDM and governance tools, you can enhance the overall quality and effectiveness of your data management strategy.

This brings benefits to all stakeholders within your organization, leading to improved decision-making, operational efficiency, and overall business performance.

Evaluate your current MDM practices and consider integrating external data sources to enhance your data management strategy. Leverage the insights and recommendations provided in this proposal to achieve better data accuracy, consistency, and completeness.