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:

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...

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: 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...

Data Governance Program Phases

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.

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.

Setting Governance Roles and Responsibilities

Who does what in a Data Governance program? First, a group of individuals (or a hierarchy of groups) representing a cross-section of stakeholder groups makes a set of rules in the form of policies, standards, requirements, guidelines, or data definitions. (Or, they...

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...

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.

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.

Working with Data Stewards

Approaches to Assigning Data Ownership and Stewardship Organizations can take multiple approaches to assigning Data Owners and Data Stewards for enterprise data. In doing so, they need to consider several factors and answer the following questions.Question #1:  Should...