Decided to set up a data governance engine in your organization? Congratulations! It is an excellent—and essential step towards helping the business achieve its strategic goals. Whether you decide to work with a partner to build your governance engine or do it on your own, a systematic approach never fails. Here are some pointers to help you get started.

Step by step approach to building a data governance engine in your enterprise.
4-steps to a building data governance engine

#1 Unite stakeholders under the business rationale for data governance

While the ownership of data governance ultimately rests with the business, creating the engine and framing the policies requires collaboration between IT and the business. So, the best place to start is by bringing together all the business and IT stakeholders from across the organization. Collaboratively assess the organization’s specific set of needs and data pain points across teams. This will help you identify the value that data governance will bring for the business. Through discussions with stakeholders from different teams and functions, generate a comprehensive understanding of data flow.

One of the outcomes of this stage should be the compilation of a business data glossary. A data glossary helps align business terminology with the tech and other organizational assets. This makes search and access more accurate and efficient. The other outcome can be a data flow diagram. This is a visual representation of how all key data flows through the organization. Typically, this has four components: the data glossary term, the business unit(s) that use this, the systems that the data flows through and the final purpose of the data.

#2 Assess the maturity of the existing data governance program

The goal of this stage is to gain a comprehensive understanding of the organization’s current data governance maturity levels and evaluate where it stands vis-a-vis industry benchmarks and best practices. This stage requires the involvement of the data governance program team as well as IT representatives.

While there are multiple maturity models available for this assessment, we recommend using the Capability Maturity Model Integration (CMMI) program. This assesses and rates your organization’s governance capabilities in each function area on a scale of 1 to 5.

The goal of the organization must be to move from a chaotic stage to a stable and then, a predictive model. As Dr. Walid el Abed, Founder and CEO of Global Data Excellence, says, “If you know the impact of changing the rules and apply your changes to governance before they happen (this is the predictive model), you can realize your value target.”

#3 Structure the shared data governance program

This is the third and most “action-packed” stage in which all the business and IT stakeholders, as well as the data governance project team, come together to create a detailed data governance project charter that includes:

  • Defining the project’s vision, mission, purpose, and goals
  • Building a cross-functional project team and creating a RACI chart (this specifies who is Responsible, Accountable, Consulted and Informed for each task)
  • Outlining risks and creating a mitigation strategy (Who is likely to push back? What changes will be difficult to make? What capabilities need to be built?)
  • Constructing a project timeline with key milestones (factoring in dependencies, potential delays and buffers)
  • Defining and setting benchmarks for the business and metrics for IT

A successful data governance program calls for a balance between planning and control activities. Planning activities will be effective only with mechanisms to monitor and control them. So make sure to detail out the costs and metrics (with targets) you will use to evaluate the success of the project. Each metric must have an owner for tracking as well as someone responsible for achieving it.

Balance between planning and control is needed when building a DG program.

#4 Getting a sign-off from the board

The project charter helps communicate crucial details about the data governance project and make decisions related to resource allocation and planning. More importantly, it helps the project team or DGC present its case to the board and receive a sign-off to proceed to execution. Before pitching the charter, make sure to get it validated by senior stakeholders or sponsors within the organization. And remember, obtaining approvals is most likely to be an iterative process—be prepared to answer questions raised and even go back to the drawing board to make changes to the plan.

Need help accelerating your data governance project? We have extensive blueprints for assessments and roadmaps that we tailor to suit the requirements of your organization. Contact us at infous@iandisoft.com.

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