Building a Data Governance program from the ground up can be a huge undertaking, much like a puzzle, but with no picture as a guide. The Chief Data Officer at American Fidelity Insurance, Ryan Doupe, spoke at DATAVERSITY® Enterprise Data World Conference and presented a practical ten-step plan for starting or improving a Data Governance program. “If you get all these ten pieces right, you are more than likely going to have a successful Data Governance Program.”

Doupe recommends assembling these ten interlocking pieces in sequence, although doing them in order is not essential if some elements are already in place, and existing areas can be revisited as each piece is considered.

1. Establish Executive Ownership

The first step to starting a Data Governance program is to establish a single executive owner. It’s best to have one ultimate decision-maker rather than two or three, so decisions can be made quickly and the project can keep moving forward.  

This individual should be accountable to the overall program, with budget authority and the ability to make decisions. The owner doesn’t need to be involved in the day-to-day workings of Data Management and governance, but they must have a vested interest in the pursuit of better data.

They should also be involved with the company’s highest level strategic planning efforts and have a broad view of the organization, with a commitment to supporting the program and helping to overcome major roadblocks, he said.

2. Identify an Employee Dedicated to Enterprise Data 24/7

The next piece of the puzzle is to identify a lead for the Data Governance program, someone to drive governance and be willing to go down a rabbit hole if it’s absolutely necessary, he said. This should be the same person who defines and drives the company’s Data Strategy: ideally, the CDO or CTO.

It’s possible to have a Data Governance Program Manager in this position but the most important takeaway is that the program needs a person who is 100% dedicated to Data Governance.

3. Determine an Objective

The next step is to explore why data is important to the company. This process should involve consulting with different people across the organization, and their input will form the Data Governance objectives for the program.

Answers might range from improving analytics, or making more data-driven decisions, to creating a sustainable long-term advantage in the marketplace or changing the company’s business model. It helps to craft a “future state” vision statement to guide decisions, he said.

4. Create a Data Governance Structure

Doupe suggests a three-level Data Governance program structure. The top strategic/executive level should consist of two to four C-level executives with wide influence, one of whom serves as the executive sponsor. The second level, tactical/data owners, is composed of three-to-ten senior managers or directors who are data owners accountable for the data within their domains. Operational/data stewards and subject matter experts with significant organizational knowledge about the company’s data make up the third level. These are people who often do Data Management activities, even if those duties are not explicitly listed in their job description.

5. Create a Data Governance Committee Charter

Creating a formal Data Governance Committee Charter clarifies roles and responsibilities and engenders a sense of responsibility in participants. It provides a forum to discuss progress and get decisions on some of the more challenging conversations regarding Data Management.

Formalizing the committee via a charter also sets up the purpose and mission of the team, the objectives, how results will be measured, the scope of the committee and what decisions they will be making, how the committee should operate, and how they will make decisions.

Gathering feedback up front from all members of the Data Governance Committee and incorporating

that feedback into the team’s charter can generate a tremendous amount of goodwill, he said. Having a formal vote on the charter early in the process gives committee members an opportunity to put their charter-defined voting process into action from the beginning.

6. Create a Data Steward Community

Data Governance cannot be successful without data stewards with significant first-hand knowledge of the data, and those employees need a clear understanding of expectations before they are engaged in the process.

Training is critical for data stewards because most of them have day jobs, and being a data steward is not their full-time role. Most data stewards will enjoy opportunities to enhance their skills and become more effective, and the investment will show them that their work is valued.

Doupe recommends holding a Data Summit event to build community among stewards and to provide information that can help them in their roles. Summit topics don’t necessarily have to be focused on data — guest speakers and executives can talk about how Steward activities contribute to the success of the broader company strategy.

7. Set up Data Governance Tools

As the seventh piece, Doupe recommends finding the funds to procure third party tools rather than creating homegrown options. “Tools from the vendors have been built with feedback from dozens of clients that they have. As a result, there’s a lot of functionality,” he said, which can immediately improve Data Management practices.

The minimum needed is a business glossary, which documents the program’s standardized terminology and definitions, as well as a data dictionary, which contains various metadata attributes concerning data assets across the organization.

A second must-have tool is a Data Quality tool for data profiling. Data profiling documents the descriptive statistics of a data set, such as the format of the data, the number of rows or values, and how often they occur. “A Data Quality tool will also allow you to create and run data rules to produce Data Quality metrics.”

Not essential but nice to have is a dashboard that makes Data Quality metrics highly visible to everyone in the organization. “That will help your Data Governance program get additional traction,” he said.

8. Do a Data Management Maturity Assessment

A Data Management Maturity assessment shows the areas where the organization’s current practices support success, and where they could use improvement. “You need to understand your current state before you can create a roadmap for data maturity advancement.” There are quite a few available assessment tools, but Doupe recommends the CMMI Institute’s Data Management Maturity Model.

The CMMI model looks at six major categories: Data Governance, Data Management Strategy, Data Quality, Platform and Architecture, Data Operations, and Supporting Processes. Each of these six categories are evaluated using a one-to-five-point score. Ideally, have a third-party Data Management consulting company perform the assessment to provide an unbiased external viewpoint.

9. Define Goals and Create a Roadmap

An objective Data Management Maturity Assessment will provide both beginning and ending points on a roadmap to success, he said. “Your roadmap should answer two questions: One, what are you trying to accomplish? And two, how are you going to get there?”

Fill in the steps in an implementation plan by mapping out milestones along the way. Ensure that objectives are S.M.A.R.T.: Specific, Measurable, Attainable, Relevant, and Time-based. It should be very clear whether a milestone or deliverable was achieved; this should be able to be answered with a “yes” or a “no.”

A Data Management roadmap should be built and developed with two key inputs: Undeveloped areas in need of improvement as defined by the maturity assessment, and issues or areas the Data Governance Committee has identified that need to be addressed.

10. Communicate

The last piece of the puzzle is to continually broadcast the importance of data. “If you’re leading a Data Governance program, your side role needs to be chief communicator,” he said. This is critical.

Communication about the Data Governance program generates two things: it generates awareness, and it generates desire.

Awareness is generated by answering these questions:

• “Why do we have a Data Governance program?”
• “Why is data important to the organization?”
• “Why should we be focused on improving our Data Management practices?”

Desire is generated by answering the question: “What’s in it for me?”

A data steward, for example, might want to devote themselves to Data Governance efforts to learn new skills, to advance along a career path, or to provide opportunities to be recognized. “You’ve got to put yourself in their shoes and figure out what incentivizes them to be part of this effort,” he said.

Key messaging should stress:

• Why is data important?
• What are we doing to get better?
• What do we need from you?
• Who are the “unsung heroes” among the data stewards?

Use existing communication channels as well as adding new ways to promote the program, such as town halls or putting out governance program newsletters.

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