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Exercising Data Governance: 5 Steps to Keep Your Resolution for Organizational Health

Have you ever planned to wake up early in the morning to work out, but found yourself lying in bed and catching up on some sleep instead? It can happen even after you've committed—mentally, at least—to a new workout regimen.

That’s because the hard part isn’t resolving to do something new; it’s adjusting your daily habits and generating enough momentum to carry the changes forward. It’s building up discipline and drive.

The same challenges apply to data governance initiatives. If you have ever been part of a data governance program that hesitated, backfired, or stopped completely in its tracks, you're familiar with this feeling. As businesses accrue ever-increasing amounts of data, they want to be able to transform all that information into insights the same way you want to get in shape.

The thing is, getting your organization to buy into a new program conceptually is the easy part. Acting and sticking to it is much more challenging. That’s why the final step on the roadmap to transformation is governance: creating a data movement in your company.

A diagram showing the five steps to data transformation: Strateize, Capture, Equip, Integrate, and Govern

What is data governance?

On the roadmap, governance means managing data and engaging people. While both elements appear in earlier steps—you can’t build a data strategy without understanding how your people want to use your data, for example—governance is the final maturation of technology, policies, and people management.

Many organizations believe that implementing technology, such as a data lake or a platform that enables the entire organization to access and aggregate diverse data, is tantamount to transformation. But does simply buying workout equipment mean you get healthier?

Tools will help streamline your organizational processes, and they’ll complement information governance and information management, but building and maintaining a culture that treats data as an asset to your organization is the key to ongoing success.

So how do you get there?

A team of speed skaters practicing together on a track

5 steps to successful data governance

Here are the five key factors to building good habits that will generate momentum once your data governance program is underway:

1. Impart a sense of urgency for the program.

Once an organization devises a plan to manage its data assets, there must be a sense of urgency to keep the plan in place. The reasons are unique from org to org, but they might be driven by compliance, customer satisfaction, revenue gain, or M&A opportunities. Regardless of what the reason is, it needs to resonate with senior leadership and ideally be tied to the company’s strategic goals in order to be most effective.

2. Communicate, communicate, communicate.

The cornerstone of a successful data governance program is a well-organized, cross-departmental communication plan. A solid plan helps remove the silos and maintain company-wide support for the initiative. A wise course is to seek out champions throughout the org and meet with key stakeholders regularly to document their pain points. It’s important to get people engaged early to keep the excitement going.

3. Operationalize change within the organization.

Delivery needs to be agile in nature because the original plan put into place is bound to evolve. The goal is to learn what works within the organization early on, to ensure the data management team delivers value quickly and that the process is sustainable moving forward. By completing tasks iteratively and agreeing upon a small set of high-value data attributes, the org will validate the data governance process.

4. Make the plan as RACI as possible.

Active listening—to supporters and detractors—and including a RACI (Responsible, Accountable, Consulted, Informed) model in the change plan helps everyone on the governance team understand their roles and responsibilities throughout the process. This plan will keep the team focused and guide initiatives forward. Forming a strong governance organizational structure, with defined roles for data ownership, stewardship, data champions, and approvals, drastically increases the odds of success.

5. Measure, share, and repeat.

Organizations can’t manage what they don’t measure. It is vital to face the facts and communicate findings at many steps along the governance path. Documenting and implementing KPIs (Key Performance Indictors) to measure the initiative’s progress over time helps connect pieces that may not obviously be cause and effect. Linking the KPIs to revenue or sales loss, for example, is meaningful to stakeholders and could be an excellent impetus for greater employee buy-in as the data transformation process moves forward.

Building up the data governance muscle

Like sticking to a workout regimen, data governance demands discipline that takes time and commitment to develop and fine-tune. This requires changing years of undisciplined behaviors regarding data within your organization, and the change will not happen overnight. Changing these behaviors is an ongoing process that needs to resonate throughout an organization’s culture in order for success to occur.

In addition, it’s important to keep things fresh. When working out, you need to rotate though different core muscle groups and vary the routine to keep things interesting and progressive. It’s the same with data governance initiatives. Don’t let people get bored with the same repetitive activities that happen day in and day out.

Instead, try conducting data discovery sessions where team members present findings from an internal or external dataset that would be interesting to other team members. You can also start a conversation by sharing successes and learnings from past data-related projects. Another suggestion: Discuss future cross-departmental data projects (or “wishlist” items), which can lead into great data roadmap discussions. 

The objective of all these options: Keep everyone engaged and finding value in meetings so that the team continues to show up and make progress on the org’s data transformation.

Remember that data governance is a journey that requires commitment and hard work. As with exercise, working hard for a month is a great start, but it’s only with continued dedication that you really start to notice the change. If you want to take your organization to the next level, you need to develop the discipline toward information management that your organization requires for long-term sustainable success.

 

To move from equipping your organization with data to managing that data and engaging your people—to set up your workout plan, if you will—start with Launch’s personalized Future State of Data vision workshop.

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Have you ever planned to wake up early in the morning to work out, but found yourself lying in bed and catching up on some sleep instead? It can happen even after you've committed—mentally, at least—to a new workout regimen.

That’s because the hard part isn’t resolving to do something new; it’s adjusting your daily habits and generating enough momentum to carry the changes forward. It’s building up discipline and drive.

The same challenges apply to data governance initiatives. If you have ever been part of a data governance program that hesitated, backfired, or stopped completely in its tracks, you're familiar with this feeling. As businesses accrue ever-increasing amounts of data, they want to be able to transform all that information into insights the same way you want to get in shape.

The thing is, getting your organization to buy into a new program conceptually is the easy part. Acting and sticking to it is much more challenging. That’s why the final step on the roadmap to transformation is governance: creating a data movement in your company.

A diagram showing the five steps to data transformation: Strateize, Capture, Equip, Integrate, and Govern

What is data governance?

On the roadmap, governance means managing data and engaging people. While both elements appear in earlier steps—you can’t build a data strategy without understanding how your people want to use your data, for example—governance is the final maturation of technology, policies, and people management.

Many organizations believe that implementing technology, such as a data lake or a platform that enables the entire organization to access and aggregate diverse data, is tantamount to transformation. But does simply buying workout equipment mean you get healthier?

Tools will help streamline your organizational processes, and they’ll complement information governance and information management, but building and maintaining a culture that treats data as an asset to your organization is the key to ongoing success.

So how do you get there?

A team of speed skaters practicing together on a track

5 steps to successful data governance

Here are the five key factors to building good habits that will generate momentum once your data governance program is underway:

1. Impart a sense of urgency for the program.

Once an organization devises a plan to manage its data assets, there must be a sense of urgency to keep the plan in place. The reasons are unique from org to org, but they might be driven by compliance, customer satisfaction, revenue gain, or M&A opportunities. Regardless of what the reason is, it needs to resonate with senior leadership and ideally be tied to the company’s strategic goals in order to be most effective.

2. Communicate, communicate, communicate.

The cornerstone of a successful data governance program is a well-organized, cross-departmental communication plan. A solid plan helps remove the silos and maintain company-wide support for the initiative. A wise course is to seek out champions throughout the org and meet with key stakeholders regularly to document their pain points. It’s important to get people engaged early to keep the excitement going.

3. Operationalize change within the organization.

Delivery needs to be agile in nature because the original plan put into place is bound to evolve. The goal is to learn what works within the organization early on, to ensure the data management team delivers value quickly and that the process is sustainable moving forward. By completing tasks iteratively and agreeing upon a small set of high-value data attributes, the org will validate the data governance process.

4. Make the plan as RACI as possible.

Active listening—to supporters and detractors—and including a RACI (Responsible, Accountable, Consulted, Informed) model in the change plan helps everyone on the governance team understand their roles and responsibilities throughout the process. This plan will keep the team focused and guide initiatives forward. Forming a strong governance organizational structure, with defined roles for data ownership, stewardship, data champions, and approvals, drastically increases the odds of success.

5. Measure, share, and repeat.

Organizations can’t manage what they don’t measure. It is vital to face the facts and communicate findings at many steps along the governance path. Documenting and implementing KPIs (Key Performance Indictors) to measure the initiative’s progress over time helps connect pieces that may not obviously be cause and effect. Linking the KPIs to revenue or sales loss, for example, is meaningful to stakeholders and could be an excellent impetus for greater employee buy-in as the data transformation process moves forward.

Building up the data governance muscle

Like sticking to a workout regimen, data governance demands discipline that takes time and commitment to develop and fine-tune. This requires changing years of undisciplined behaviors regarding data within your organization, and the change will not happen overnight. Changing these behaviors is an ongoing process that needs to resonate throughout an organization’s culture in order for success to occur.

In addition, it’s important to keep things fresh. When working out, you need to rotate though different core muscle groups and vary the routine to keep things interesting and progressive. It’s the same with data governance initiatives. Don’t let people get bored with the same repetitive activities that happen day in and day out.

Instead, try conducting data discovery sessions where team members present findings from an internal or external dataset that would be interesting to other team members. You can also start a conversation by sharing successes and learnings from past data-related projects. Another suggestion: Discuss future cross-departmental data projects (or “wishlist” items), which can lead into great data roadmap discussions. 

The objective of all these options: Keep everyone engaged and finding value in meetings so that the team continues to show up and make progress on the org’s data transformation.

Remember that data governance is a journey that requires commitment and hard work. As with exercise, working hard for a month is a great start, but it’s only with continued dedication that you really start to notice the change. If you want to take your organization to the next level, you need to develop the discipline toward information management that your organization requires for long-term sustainable success.

 

To move from equipping your organization with data to managing that data and engaging your people—to set up your workout plan, if you will—start with Launch’s personalized Future State of Data vision workshop.

Back to top

More from
Latest news

Discover latest posts from the NSIDE team.

Recent posts
About
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