Remember our (long) definition for Data Governance?

“Data Governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.”

Focus on Architecture

Yes, Data Governance is about enforcing rules. But just as important, usually, is ensuring that the right stakeholders are involved in making the rules.

Sometimes – especially for compliance-related rules – it’s easy to know who should decide on a rule. But other times it’s hard. And most organizations have lots of examples from their own histories of decisions that were made without input from key stakeholders. They can tell stories of the problems created when the right groups were not consulted.

So a best practice is that before any rule is created or any data-related decision is made, a prior decision must be addressed: who gets to make the decision, and when, and using what process?

This practice is called establishing “Decision Rights” for the decision.

It is the responsibility of Data Governance program facilitators to know (or discover) who should be involved in making different types of governance decisions. It is also generally a responsibility of the program to facilitate (and to sometimes document and store) the collection of decision rights that are the “metadata” of data-related decisions.

Read Next:

Focus Areas for Data Governance: Data Quality

This type of program typically comes into existence because of issues around the quality, integrity, or usability of data. It may be sponsored by a Data Quality group or a business team that needs better quality data. (For example: Data Acquisition or  Mergers &...

Establishing a Data Governance Office

Most organizations that begin a formal Data Governance and Stewardship effort need a support team to facilitate and coordinate activities of councils, stewards, and stakeholders. This support team may be individual contributors who have been doing this work informally...

Governance Communications

At a Data Governance Conference in Orlando, Florida (USA), a group of managers of successful Data Governance programs reached a startling consensus: They agreed that Data Governance is actually somewhere between 80 and 95% communications!How can this be? They said...

Choosing Governance Models

It’s important to define the organizational structure of your Data Governance program. But before you can do that you have to define your governance model at a higher level. You need to consider what types of decisions your governance bodies will be called upon to...

Focus Areas for Data Governance: Management Alignment

This type of program typically comes into existence when managers find it difficult to make “routine” data-related management decisions because of their potential effect on operations or compliance efforts.Managers may realize they need to come together to make...

Governance and Alignment

Data Governance is a balancing act. On the one hand, you need to exert control over how groups create data, manage data, and use data. On the other hand, you need to promote appropriate levels of flexibility. You need to ensure that data-related efforts support the...

Focus Areas for Data Governance: Privacy, Compliance, Security

This type of program typically comes into existence because of concerns about Data Information Security controls, or compliance. Compliance, in this context, may refer to regulatory compliance, contractual compliance, or compliance with internal requirements.This...

Focus Areas for Data Governance: Data Warehouses and Business Intelligence (BI)

This type of program typically comes into existence in conjunction with a specific data warehouse, data mart, or BI tool. These types of efforts require tough data-related decisions, so organizations often implement governance to help make initial decisions, to...

Governance and Issue Resolution

One of the three most important jobs of a Data Governance program is to help resolve data-related issues. These may be conflicting data definitions, data usage concerns, or problems with how data is sourced, how it is integrated, how it is protected, or a myriad of...

Implementing Change Management

Most organizations have string change management – or at least change control – mechanisms for technology. They usually have change management for software applications. They have change management for websites. And yet, many organizations do not practice structured...