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Why Successful Master Data Implementations Use Hierarchies

Drive Business Growth with Hierarchies Across All Your Use Cases

If you've already read the first installment of our Master Data Knowledge Series, you know the value that mastering your data can bring to your business whether its across your enterprise or within one use case. Managing hierarchies is both one of the greatest benefits, and one of the most difficult aspects to implement. Luckily, Dun & Bradstreet can help.

How Hierarchies Help Your Data Architecture

It takes time to design, institute, govern, and maintain a hierarchical structure, but the benefits your organization can reap are well worth the effort.
 

It takes time to design, institute, govern, and maintain a hierarchical structure, but the benefits your organization can reap are well worth the effort. Hierarchies clarify the relationships within companies and can range from majority ownership which is vetted and monitored and an abstract sense which can be predicted for example when companies have relationships but are not responsible for each other's debts. From these relationships, you can:

 

  • Identify new potential prospects or partners
  • Determine cross-sell and upsell opportunities with existing customers
  • Help your supply and compliance teams understand the full impact of partnerships
  • Look for savings when contracting with an enterprise for different goods or services
  • Improve customer experience by serving consistently multiple branches of the same company

Hierarchies Address All Use cases

Typically, there isn’t one hierarchy structure that meets all your business needs. Most often the use case defines the need for accuracy, breadth and depth of hierarchies. Majority Owned Relationships are clearly defined and provide a finite group of legally linked entities. Predicted Relationships using analytics and machine learning suggest relationships between entities which start with a broader definition of a hierarchy with the ability to include or exclude candidate relationships based on the use case definition.

Often within the Marketing Use Case where the goal is to identify hierarchies or relationships expanding the marketable universe to drive more sales, a broader less rigid view of hierarchies may be acceptable. The volume of relationship candidates grows at the expense of accuracy with the marketing universe as the ability to vet each potential link becomes cost prohibitive and less risky.

On the other end of the spectrum, an example of a Financial Use Case where the need to establish who is financially responsible for paying a bill would require a stricter hierarchy where the legal structure has been established and vetted. Predicted relationships could be far too risky without having been vetted and ensured.

Dun & Bradstreet has been diligently working to expand our hierarchy capabilities to meet the broad views for every use case. Our latest offering, Dun & Bradstreet’s Extended Linkage Insight is an AI-driven hierarchy solution that provides a comprehensive view of business relationships. It goes far beyond fuzzy logic name matching deriving the types of relationships that typically require significant efforts to identify manually. Dun & Bradstreet continues to provide the scalable, repeatable non-biased hierarchy options you require from a data partner.

In the latest version of my whitepaper "Master Data: Implementing Dun & Bradstreet Hierarchies and Custom Hierarchy Views – July 2019", I incorporate all Dun & Bradstreet hierarchy options including Extended Linkage Insight and even a section on how to manipulate hierarchies to further operationalize your own definitions.

We understand that creating, enabling and maintaining hierarchies is hard - this whitepaper gives you the foundation to take it on. For further assistance Dun & Bradstreet has expert Data Advisors that will guide you through the process.

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