Organizations often respond—reactively rather than proactively—when data issues arise.

In fact, it serves as a valuable wake-up call for adopting a more strategic approach. Find out six steps to help build an influential data-driven organization.

The wake-up call

It’s 2:00 a.m., and the head of analytics receives a call from the CIO. Something has gone terribly wrong with an ETL job. For the next 16 hours, the team attempts to address the issue, all the while under pressure from the CIO to work faster “to preserve the organization’s reputation.” After this issue is resolved, the analytics lead discovers the incident really only affected one person working on a special project. It was not at all related to the organization’s core operations, yet the team halted its regular responsibilities for nearly two days to resolve it.

This incident illustrates how organizations often respond—reactively rather than proactively—when data issues arise. In fact, it serves as a valuable wake-up call for adopting a more strategic approach.

That strategic approach requires data governance

In an environment of rapidly evolving technology, customer behavior, and competition, data has become one of an organization’s most important and valuable assets. Organizations establish cutting-edge reporting and analytics tools and sophisticated data warehouses, yet many still struggle to realize greater value from their wealth of data. One of the key reasons is that they lack an effective data governance framework—the people, processes, and tools for managing complex and interrelated data across the organization.

What might a successful data governance structure look like?

Effective data governance structures can take different forms, but all share some common elements:

  • A tie to the overall business strategy
  • Shared business/IT ownership
  • Linkage with other enterprise and IT process and governance structures
  • An emphasis on how the organization uses data to drive innovation, continuous improvement, and/or effective decision making

Following is an example of a data governance structure that has worked well for data-rich, mid-sized organizations. This model includes each of the elements listed above. It links to the corporate strategy by integrating input from executive and business unit sponsors. It ensures continued focus on data through the Data Governance Council and data “stewards.” Its cross-functional project task force provides responsive and timely execution support. And its coordinator ensures centralized accountability and alignment with other governance processes. Most of all, it fosters effective communication through champions at various levels.

Six steps to establishing an influential data governance framework and structure

Following these six basic steps can help you establish an influential and effective framework tailored to your organization and is cultural values.

Align. Start by understanding the organizational landscape and considering the cultural and strategic requirements for establishing a data governance structure that supports your organization’s roles.

Appeal. Promote the opportunities that will stem from data governance in order to establish relevance and a sense of urgency. Ask key leaders to help deliver these messages across the organization.

Engage. Engage the right stakeholders to be part of the Data Governance team and build a broad change network comprised of people with various skills and perspectives. Engaging these key individuals to establish preliminary processes (e.g., how the team prioritizes data issues, changes, and projects) and a general approach will help build substantial momentum for a larger effort.

Act. Identify data stewards and subcommittees within your organization to act on the established processes and initiatives. Initiate data requests and document the respective steps for taking action on those requests. Then, institute processes and procedures using master data management and data quality management tools such as Microsoft Master Data Services and Data Quality Services.

Unite. Make sure the group connects periodically to promote collaboration and ensure progress against the measures established for each data initiative. In addition, facilitate knowledge sharing by providing training sessions for any newly introduced tools or processes.

Convey. Last but definitely not least, measure the results of each data request or initiative and communicate those results to the organization through various media. In fact, this activity is critical from the start and throughout the process to ensure people value the effort and are aware of how it impacts them. Consider leveraging the established change network to share information. The “what’s in it for me” message should be a capstone for each conversation.

A word about the importance of change management

Implementing data governance relies on new behaviors and new ways of thinking; for example, use of common process terminology (for instance, consistent definitions of “lead” or “prospect” in a CRM system). Applying proven organizational change management principles can help expedite the path to enhanced data governance. Effective communication and collaboration are important, as are careful consideration of culture, an influential change network, and training.

A thoughtful change management approach reduces business disruption and prepares individuals for change, which in turn improves productivity and enhances the speed at which your business realizes the benefits of data governance.

For more information about establishing effective data governance structures and principles, please contact Gordana Radmilovic, data governance lead, or Michael Hughes, organizational change management lead.