Seven Key Questions for Achieving Master Data Governance Success

Answer these seven critical questions to achieve greater success with a new master data governance program.

by Ravi Shankar

In large organizations, data governance typically germinates in one of two ways: a top-down approach led by a key executive (such as a chief financial officer) or a bottom-up approach driven by business unit stakeholders who understand the importance of data ownership and data management to their success. Either approach can readily stall, run into a political logjam, or fail if critical questions have not been raised and addressed before embarking on a solid data governance initiative.

In the report “A Data Governance Manifesto: Designing and Deploying Sustainable Data Governance,” Jill Dyché, a Baseline Consulting co-founder, warned, “Without a sound description of the problems being solved, as well as clear communications around key decisions and the authority to make them, data governance can fail before it really begins.”

What is Master Data Governance?

Although data is certainly ubiquitous across an organization, the practice of data governance is commonly limited to the most important types of data—the data necessary for efficiently managing business operations and regulatory compliance. Today, this important class of data—called master data—is emerging as a critical and central component of a company’s data governance efforts. More specifically, master data is a collection of common, core business-data entities such as customer, product, and organization and their associated attributes and values.

Master data governance, on the other hand, is the overall management of these data entities; it consists of the policies, processes, controls, and audit functions required to manage and safeguard these critical corporate data assets. As a result, data governance also includes oversight of the related domains of data availability, usability, integrity, and security.

Before implementing a master data governance program, an organization must proactively raise and answer the following seven critical questions to lay the foundation for a sound master data governance program. Thorough due-diligence upfront and buy-in from the appropriate stakeholders will ensure your data governance initiative will have a greater chance of success and you will avoid costly delays and minimize political quarrels.

Here are seven critical questions that can improve your master data governance success.

1. What data should constitute master data?

Master data will vary depending upon the industry and the fundamental business processes that rely upon the data. For example, a manufacturer trying to improve supply chain operations will define as master data such elements as products, units of measure, and kit components. A pharmaceutical company required to comply with complex marketing regulations will define health-care providers, hospitals, state licenses, and sales territories as master data; a financial services firm that manages credit and operational risk will define master data as counterparties, security, geography, and currency.

2. Who will own the master data?

Before a data governance program can be effective, it is critical that the definition for master data be uniform across the organization. This sounds like a simple task, yet many forms of master data can be quite complex—with many elements in the definition—contributed by multiple lines of business. For example, the design-related elements of a product master may be provided by the engineering department; packaging, part, and unit information may come from manufacturing; and the category and product family elements are defined by distribution.

The ultimate question to be addressed is: Should there be a single owner for the entire product master who collaborates with the other departments, or should the ownership of these elements be assigned to different departmental owners? The answer to this question will vary depending upon the master data governance policies your organization defines. Moreover, without designated owner(s), the risk of multiple definitions for master data within the organization increases, and the data governance initiative is likely to stall.

3. How many and what data sources exist for each type of master data?

Account for the number of data sources, as application systems are often widely distributed across business functions and store multiple instances of the same master data entity—which will require data consolidation. For instance, product master data will exist within the product lifecycle management (PLM) systems used by engineering, in enterprise resource planning (ERP) systems used in manufacturing, and in supply chain management (SCM) systems used by distribution. In addition, an organization’s master data may be sourced from an external data provider. The type and number of source systems determine which sources will supply the initial and ongoing data, and then determine if any new systems are planned or if any existing systems are to be retired.

4. What validation and/or verification of consistency, correctness, and completeness are sufficient?

Master data, by its very definition, needs to be reliable. The master data must be consistent, correct, and complete. Master data quality standards will vary by the type of data, its source, usage, and the overall cost of maintaining its data quality. For example, if postal codes are critical for marketing campaign effectiveness but are missing from a majority of customer records, data augmentation from an external data provider may be required to ensure data reliability.

5. What industry or regulatory standards must be supported?

Regulatory standards differ greatly by industry, so data governance initiatives will vary by an industry’s unique mandates. For instance, pharmaceutical companies are required to comply with pharmaceutical marketing regulations and prescribing drug restrictions, while financial institutions need to comply with Basel II, privacy, and MiFID regulations. Compliance with these and other evolving industry standards often dictate which additional master data entities are tracked along with data history and lineage information to support the necessary reporting and audit functions.

6. Who must have access rights to which data type and what actions can a user perform?

System and master data security access rights and policies need to be established—and enforced—to ensure that an organization’s compliance and data-quality requirements are met. As a result, determine upfront what elements or fields of master data an individual is allowed to access. What access does each individual have: read, edit, print, delete, or all privileges? These and related access and update rights and restrictions need to apply to each type of master data at a granular level. For instance, an organization needs to decide if a particular sales representative should be restricted from, or given rights to, view a specific customer’s Social Security number or other sensitive information.

7. What controls must be put in place for master data, and what level of change must be recorded over what time period?

Controls are an obvious yet necessary component to any master data governance endeavor provided these policies are maintained using configured rules to prevent certain actions or events from occurring or to provide notification when a defined action or event occurs. By establishing solid control at the onset, these controls will monitor and audit the usage of the system in real-time and alert a data steward of issues and exceptions. Additionally, all changes to master data will need to be tracked in order to document the lineage of such changes, while providing a foundation for historical reporting. The change tracking and auditing required depends upon the specific business requirements.

Master Data Governance Technical Requirements

Taking the time to answer these seven critical questions before designing your data governance process will allow you to better plan and implement a successful enterprise-wide master data governance effort. Further, these questions will help you identify and evaluate a suitable technology platform—a necessary requirement when managing your organization’s master data assets and establishing a consistent master data foundation. More specifically, the answers to these seven questions can form the basis of your technical requirements definition because vendors must be able to map your requirements to their system’s functionality. Lastly, select a technology solution that is flexible and can provide integrated capabilities to fully support all of your master data types and your organization’s master data governance processes, controls, and audit requirements.

With these seven critical questions answered in advance of embarking on a data governance initiative, you will be well on your way to avoiding costly delays, internal bottlenecks, or seemingly daunting challenges-- with a well-thought-out enterprise master data governance program. Better yet, you just might find your data governance efforts will be rewarded by defining, determining, and communicating key data decisions—along with who has the authority to make and maintain them—at the beginning of your project.

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Ravi Shankar is director of product marketing at Siperian, Inc., a master data management platform provider. You can reach the author at

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