All programs have lifecycles. The Data Governance Life Cycle has seven phases:

  1. Develop a value statement
  2. Prepare a roadmap
  3. Plan and fund
  4. Design
  5. Deploy
  6. Govern
  7. Monitor, measure, report.
Data Governance Program Phases

Note that Data Governance does not begin with the design of the program! 

  • Before you start deciding who goes on what committee, you should be clear about your program’s value statement.
  • You should have developed a roadmap to share with stakeholders.
  • Those stakeholders will want to know the WHO / WHAT / WHEN / WHERE / WHY / HOW of your program before they decide to support it, so you need to anticipate their questions. You’ll need preliminary answers, even if they’re only assumptions until you do your actual program design

As you perform the activities needed to gain support and funding, remember that your program may plan to address multiple focus areas. Each new effort should be introduced using the seven steps of the life cycle. Even specific governance-led projects, such as creating a set of data standards, will want to follow the Data Governance Life Cycle steps.

A note about the final phase in the Data Governance Life Cycle: Each time you consider a new set of activities, you’ll want to anticipate stakeholders’ expectations for monitoring efforts, measuring success, and reporting status. Your ability to deliver industry-standard metrics that satisfy stakeholders can be the difference between program activities that are chronically painful and those that become routine.

Read Next:

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...

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...

Engaging Stewards and Stakeholders

It seems like there are two types of Data Governance and Stewardship programs: Thriving ones, with highly-engaged stakeholders, and Ones whose futures are in question, since stakeholders and stewards are only sporadically involved or give only weak support to the...

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...

Dealing With Politics

It’s essential that Data Governance and Stewardship program facilitators avoid being “caught up” in politics. It’s our jobs to acknowledge the realities of the situations we work with, while avoiding taking sides or engaging in behaviors that could be perceived as favoring one set of data stakeholders at the expense of others.

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...

Funding Models: Funding Data Governance

The DGI Data Governance Framework addresses funding two ways: Obtaining funding and support is a phase in the Data Governance Life Cycle Funding is part of one of the components of the framework. What type of funding is needed? Data Governance programs need to...

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 Decision-Making

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...

Defining Data Governance

How you define your program will influence your ability to manage it — to keep all participants on focus, in sync, and striving toward the same goals.