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.
Funding Data Governance

What type of funding is needed? Data Governance programs need to establish funding for four types of Data Governance and Stewardship efforts:

  1. The initial design and implementation of the Data Governance program
  2. Ongoing Data Governance / Stewardship / Compliance / Access Management efforts
  3. Ongoing Data Stewardship / Data Quality efforts
  4. Recommended projects and efforts that come from governance-led issue analysis.

It is this last type of funding that typically poses the greatest challenge for companies. We’ll look at options for funding issue-analysis recommendations. But first, let’s look at typical funding models for the first three types of Data Governance efforts.

 

Funding the Design of a Data Governance Program

Typically, organizations choose one of four models for creating a formal and acknowledged Data Governance program.

  1. A project to build a program
  2. Line item in other project
  3. Special funding by a stakeholder group
  4. Data Governance included in IT / Data Management / Data Architecture efforts.

1. A project to build a program

With this approach, a formal project is created to design and implement the program. Often, this project includes a prototype effort to which Data Governance is applied, such as a JAD session of Data Stakeholders or Data Stewards to address a legacy data issue.
Note: many “boilerplate” project plans are designed for the development of a piece of software, not for the development of a program. They can include steps and deliverables that don’t make sense for a program development project. Also, a certain amount of flexibility needs to be built into program development project plans, or project managers can find themselves having to process change requests when efforts to define scope and focus require multiple iterations, or meetings to discuss stakeholder needs are rescheduled.

 

2. Line item in another project

With this approach, a project that requires Data Governance to succeed in its objectives will include activities to initiate and fund the design and deployment of a formal Data Governance program. Examples would be SOA or Master Data Management initiatives or Data Warehouse projects.

 

3. Special funding from a stakeholder group

With this approach, a department or program with a major stake in the proper governance of data will initiate and fund the design and deployment of a formal Data Governance program. Examples would be SOA or Master Data Management programs, Data Warehouse initiatives, compliance initiatives such as Basel II or Sarbanes-Oxley, or Privacy/Access Control programs.

 

4. Data Governance included in IT / Data Management / Data Architecture efforts

With this approach, Data Governance is included in another technology or data-related program. If Data Governance is included in Enterprise Data Management efforts, for example, the program may be given a bucket of money to implement governance without being held to the type of spending oversight generally required of projects.

Read Next:

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: Architecture, Integration

This type of program typically comes into existence in conjunction with a major system acquisition, development effort, or update that requires new levels of cross-functional decision-making and accountabilities.What other types of groups and initiatives might want...

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 &...

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...

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.

Defining Organizational Structures

There is no single “right” way to organize Data Governance and Stewardship. Some organizations have distinct Data Governance programs. Others embed Data Governance activities into Data Quality or Master Data Management programs.

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...

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...