6 Expert Tips for Scaling Data Governance from Pilots to Successful Programs

Did you know that in a recent survey, 52% of data leaders cited improved governance over their data and processes as their top data strategy priority? A primary driver for this trend is that a larger share of the workforce needs accurate, reliable and trusted data for decision-making.

Companies are looking for modern data governance solutions that can help them track how data is used across their organization. These solutions can improve data flow and maintain data quality, trust and security. Today's data-driven businesses need to scale quickly and confidently as they handle more and more data. This is particularly important for applications that rely on data, such as AI and analytics.

Implementing data governance strategies can be daunting for companies looking to expand their digital business. However, simply having a plan in place is not enough. For the program to be successful, it needs to be embraced by the entire organization and built on a foundation of trust. Without this support, the initiative loses momentum and can be forgotten or sidelined. To avoid this, it's essential to ensure that everyone understands the benefits and is fully committed to the plan.

Expert Tip:  Informatica provides step-by-step guidance on scaling data governance programs in the workbook Cloud Data Governance Adoption Guide: 8 Best Practices for Success. Download now to gather insights and recommendations based on our experience driving successful customer adoption worldwide.

When implementing and expanding a data governance program, it's important to remember that it is just the beginning of a longer journey toward establishing a data-driven culture in your organization. Buying the best solution does not guarantee success with your data governance initiatives. The end goal is to create a system where effective data management is automatic and transparent, with minimal need for manual intervention or time-consuming maintenance of processes and procedures. To guarantee successful data governance and establish trust in data use, it's necessary to make a cultural shift. This shift will help avoid risks associated with mishandling data and prevent new data-driven business initiatives from stalling.

Because every organization is unique, its journey will align with its business objectives, size and current data management practices. However, there are some common obstacles that organizations may face. Let’s explore some of them.

Expert Tip: To create a successful data governance program, it's crucial to identify the critical business drivers and pain points that cause inefficiencies, create confusion or hinder progress. Understanding these factors makes it easier to establish a shared purpose and generate excitement for the program.

Ensure organizational alignment and commitment.  It can be challenging for data leaders to define the purpose of a data governance program. This is because different parts of an organization have other ideas of what data governance means. It's important to align the program's goals with the organization's values to make it easier to get support for the program. This will help find sponsors willing to contribute resources and gather support for the program, even when other competing priorities exist.

Expert Tip: Start small, start simple, but think big. The key is to carefully select pilot projects that deliver results that stakeholders care about. Choose initiatives that have achievable goals and introduce complexity gradually. This way, you can demonstrate early value and build momentum for the mission.

Manage expectations. Data governance could get caught in the trap of overpromising and underachieving. As time passes and focus increases, the scale and complexity of tasks can grow. However, sometimes organizations set unrealistic goals that demand too much too soon. This puts pressure on data governance teams to deliver unachievable results and leaves little room to explore the best ways to use data governance solutions. Giving these teams the freedom to do their job well is essential.

Expert Tip: When trying to get more people to use something, focusing on the people first is essential. This means changing how things are done, like job roles and the process, to make it more engaging. Teaching people how to use it early on can help them trust it and feel more confident about using it for what they need. Making sure people understand how to use information can help them use it more often and make it a more critical part of their work.

Look beyond technology to drive data governance. When companies adopt data governance, they need to do more than just use the technology. They also need to consider how it affects people and processes. Advanced capabilities like AI and automation, or better data delivery solutions like data marketplaces, offer a chance to revisit the data governance operating model. This means companies can change roles, expectations and responsibilities. They can also improve workflows and skills. If companies don't do this, they risk having the same problems they had before.

Expert Tip: To make sure that your pilot project can demonstrate success to all its stakeholders, it's essential to start by involving a cross-functional team. This will enable a diverse set of people to support the success of the data governance program throughout the organization, which is crucial for establishing credibility as the program scales.

Foster collaboration and create opportunities for feedback. Data governance implementations often operate top-down, with policies, councils, committees and many different roles. This approach can lead to fragmented governance. It can also cause problems when important stakeholders are not involved from the beginning or when they are brought in too late. Furthermore, failing to document learnings and best practices for the program creates dependencies and can make it difficult to onboard new user groups. To prevent these problems, it is essential to document learnings and best practices.

Expert Tip: It's important to remember that numbers don't always tell the whole story. Sometimes, it's essential to consider improvements that can't be easily measured, such as boosting user confidence, improving understanding of data and making it easier to add new sources. These outcomes can be just as significant as quantitative improvements.

Demonstrate measurable outcomes. Effective data governance can be difficult for organizations to measure, especially in the early stages of the program. It's challenging to demonstrate the value of data governance by highlighting risks prevented, and relying on productivity and efficiency gains may lead to underwhelming results. To showcase early progress and build momentum, it's better to use examples that illustrate common pain points and show how they were resolved. You can also use directional indicators to show progress and highlight success:

• The number of data steward assignments
• An increasing number of data assets with clear owners
• Documented growth in datasets subject to data quality measurement 

When it comes to driving data governance adoption, there are many similarities with shaping a company culture. Both require aligning with the company's purpose and introducing desired behaviors while being inclusive of diverse stakeholders and adaptable to evolving business needs. Each organization may face unique challenges along the way, so it's okay to only have some of the answers before starting. The important thing is to begin at some point and keep moving forward.

As you find nuances for your data governance program, apply agile principles that help you engage, review, learn and scale iteratively.

Learn how to evangelize data governance and produce business value across your company. Get your copy of our workbook, Cloud Data Governance Adoption Guide: 8 Best Practices for Success.