Demonstrating Value

Getting Started

Everything an organization does should tie to one of three universal value drivers

  1. Increase revenue and value
  2. Manage cost and complexity
  3. Support Risk Management and Compliance efforts, and increase confidence.

Data Governance efforts MUST tie back to one or more of these drivers.  And YOU must communicate how it does.

Demonstrating Value

Here are some of the ways a Data Governance effort can benefit you:

Increase revenue / value of assets

  • Improve the value of the company to those who would acquire it
  • Create “sellable” information products
  • Utilize information assets to make new sales
  • Utilize data to achieve new business capabilities
  • Better understand customers
  • Better understand product (and other) hierarchies

Reduce costs

  • Reduce duplicate data and its costs
  • Reduce duplicate data management processes (example: costs of data modeling, data administration, data quality)
  • Reduce likelihood of errors and associated costs (in software development, report development, information interpretation) due to lack of understanding of data or poor quality data

Support Compliance While Reducing Costs

  • Achieve compliance goals
  • Avoid cost of penalties associated with non-compliance
  • Avoidance of reputational hit (brand impact)
  • Avoid higher audit fees due to lack of confidence in “authoritative data”
  • Reduce management attestation/certification costs
  • Reduce costs of pre-audit testing

Support Impact Analysis

  • Increase ability to do useful impact analysis (by providing authoritative business rules, system of record information, and data lineage metadata)
  • Provide a capability to assess cross-functional impacts of data-related decisions

Help Align Efforts

  • Assist business teams (Business Continuity, Disaster Recovery, Security, and Privacy) to articulate their data-related business rules and requirements to IT, Architecture, and Data Management teams
  • Consider requirements and controls in an integrated fashion
  • Avoid “undoing” work or rendering controls invalid
  • Craft cross-functional accountabilities

Improve Data Repositories

  • Provide accountability and support for improving the quality of data in the repository so it can become an authoritative source of information
  • Reduce likelihood of architectural decisions that limit the organization’s ability to analyze its information
  • Increase ability to find authoritative information quickly

Improve Confidence in Data

  • Increase confidence in data-related decisions
  • Increase ability to make timely data-related decisions (this can affect time-to-market for projects and applications)
  • Increase confidence in data appearing in financial and management reports
  • Increase confidence in data strategy by providing a cross-functional team to weigh in on key decisions

Read Next:

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...
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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...
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Starting a Data Governance Program

A successful Data Governance program 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...
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Focus Areas for Data Governance

All Data Governance programs are not alike. Quite the contrary: programs can use the same framework, employ the same processes, and still appear very different. Why is this? It’s because of what the organization is trying to make decisions about or enforce rules for....
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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...
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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 &...
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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...
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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...
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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...
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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...
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