Learn How to Build a Data Governance Dream Team

by Marie Klok Crump

Learn How to Build a Data Governance Dream Team - Innovation ExcellenceIn today’s digital economy, innovation is fueled by the insights company leaders have concerning their own organizations. To effectively run a business, you need good information and data. To innovate, you need a way to play out scenarios and strategies. The success of these scenarios relies on a high degree of trust in the underlying information.

In many cases, your opportunity for innovation doesn’t arise until you analyze and interrogate your data and the patterns that emerge; these will point the way to innovation.

The organizations should first understand that data is a critical asset and that its governance is a foundational element of transformation objectives like predicative analytics, process optimization, and digitization. Then, they should begin the journey of organizing their data governance programs.

Some initial questions to ask might include:

  • How do we go about getting support throughout the enterprise?
  • What are the primary roles we need?
  • Who should be accountable for what?
  • How do we go about getting the organization started?

Many of those questions focus on the “people” part of the equation. And people are naturally the most important aspect. Creating the following three levels of ownership will not only answer those people-related questions, but it will also set up your business to use data successfully and optimally:

1. Business ownership: This level requires a management-level business data owner and an operational data owner beneath the process leadership. Further, it needs strategic support for data management initiatives to ensure alignment with the vision, goals, and objectives. It also must have the ability to make organizational, portfolio, and funding decisions while influencing projects.

2. Operational data governance: This level should actively own and manage the data management program and its people. It needs a data subject-matter expert and a data governance program leader.

3. Data management support: The third level should manage the tactical activities and support requirements for data and related processes. It should include information technology support, business support, and a “center of excellence.”

With ownership clearly defined, a data governance team works to optimize both data processes and business processes. That effort helps executives better assess the effectiveness of business operations to improve the quality of a product, reduce the complexity of a system, ensure compliance, decrease cycle times, and deliver key metrics.

From an organizational perspective, the data governance team will need the right support system to perform its roles effectively. This support system starts with contributing chief data officers who drive change from the top to ensure all organizational roles are informed and follow organizational objectives, responsibilities, and success criteria. These leaders guide and champion the overall data governance organization’s strategies and efforts, coordinating with other enterprise decision makers to ensure data is being managed as a key asset of the company.

The data governance team will also need a collaborative platform to coordinate and articulate information about the effectiveness and values of the data. A Forrester Research report states that applications for data stewardship should include both data governance policies and management components. A combination of both could allow for collaboration between business and tech stewards, and together, they could establish, manage, and analyze policies that maximize data’s efficacy. That collaboration stems from mapping key data program initiatives and imperatives that are driving the business models they support.

But the data governance team isn’t a silo — it needs to represent business functions and have an understanding of the underlying systems the business relies on. Ultimately, the data governance team needs a strong sense of trust in its ability and its data, because only by trusting its information can companies innovate.

Clearly defining the ownership of the data, describing the business consequences of not having accurate data, improving data quality, being able to maintain data, and inspiring innovation will spur trust in the team and the information businesses receive from it.

image credit: www.spreadshirt.it

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Marie Klok Crump is principal partner at DATUM LLC, an information management solutions company providing data governance software (Information Value Management®). Marie provides the leadership, management, and vision for strategic growth including brand identity, strategic alliances, channel development, and operational excellence for the customer life cycle. Follow Marie @marieDATUM

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