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Before continuing your MDM roadmap journey, Larry explains what you need to know about data hub ownership and usage

As we’ve journeyed along our MDM roadmap, we’ve discussed the costs, benefits and domains of MDM, as well as some of the key facets of data, relationships and hierarchies, and the importance of letting go.

Data hubs are at the center of any MDM implementation, and thus require a thorough review. Specifically, while investigating MDM, you must look at how the data hubs are used and who owns them.

Usage Styles

There are three primary MDM usage styles that determine the focus of MDM:

• Analytical
• Operational
• Collaborative

Analytical MDM concentrates on data warehousing, business intelligence, reporting and analytical applications. Within an analytical MDM implementation the data hub obtains data from operational systems, processes the data to resolve entities and relationships and sends high quality data to the consuming analytical systems.

An integration style where the data flows in one directions and bi-directional synchronization is not required results in lower risks and costs. Analytical MDM has the lowest costs and implementation risks.

Operational MDM typically requires bi-directional synchronization between the data hub and operational systems, which increases the cost and risk.

Collaborative MDM supports complex workflows and can include the needs to support a supply chain with multiple branching points that depend on the actions and choices of the workflow stakeholders. This process is quite typical for Product Information Management (PIM) and can be fairly complex.

(I covered these MDM usage styles in more detail in a December blog post.)

When estimating the benefits of MDM, you must consider all possible usage styles. They can collectively contribute to the total benefits of an MDM program. Similarly, the total cost depends on the usage styles and when in the MDM roadmap these styles are employed.

The MDM usage style can evolve over phases of the MDM program. From the cost and risk perspective, it is practical if the initiative begins with analytical MDM. Business requirements can change the focus and usage style implementation sequence, e.g. the business prefers an operational MDM focus from the very beginning. This is likely to cause an increase of the implementation cost.

Data Hub Ownership Styles

There are also three primary data hub ownership styles:

• Registry
• Hybrid
• Transaction

Typically, the registry style (possibly with some hybrid features) is the least risky and the most efficient way to implement the data hub while maximizing business benefits and minimizing risks and costs. The registry style arbitrates the data across multiple operating systems that retain the ownership of the master data.

Two scenarios are ideal for the transaction style.

• The master entity that is to be managed by the hub has not been supported by the present operations. For instance, an organization wants to build an entity "Provider" that has not been managed before.
• The other scenario that favors the transaction hub choice for implementation applies to the projects when the existing processes are already entity-centric, such as a customer-centric situation. The MDM project objective is to replace the existing customer-centric database with a new industrial strength MDM data hub while preserving the entity-centric flows.

Obviously, the hybrid style falls somewhere in between, with a combination of attributes from the registry and transaction styles.

Before beginning, you must take into account the complexity of match and merge (attribute survivorship) rules, as well as split rules. You should fully analyze your solution options and their associated costs and benefits.

Next week, we’ll review how the volume of data impacts performance and what considerations must be made.

This is part of a series, Building an MDM Roadmap. For other posts and a complete index, view the Table of Contents.