Data governance you can believe in

Our client is a Fortune 1000 national mattress and bedding manufacturer with more than 4,000 employees and $1.85 billion in annual revenue.

Client Challenge

Our client’s employees were confused, frustrated, and overwhelmed by the lack of data quality and consistency within their organization. Data consumers in both business and operations roles could not rely on the accuracy or timeliness of critical information the business needed. They also struggled to navigate limited documentation and discovery capabilities, decipher inconsistently defined data rules and definitions, and find data without a reliable source of truth.

In addition to data quality issues, our client faced a significant challenge in governing its data assets. Without formal roles, responsibilities, or direction established, employees performed data governance activities with little direction or accountability. Further, because there were no defined or published metrics in place to evaluate success, teams were unable to measure whether data governance methods were successful – or whether they were in harmony with other departments’ processes. As a result, data quality issue monitoring, management, and resolution happened sporadically in the organization, but with no consistency in the process, communication, or implementation methods used.

After multiple failed attempts to implement data governance across the organization, our client partnered with Turnberry to craft a comprehensive, sustainable, long-term data solution.

Our solution

A Turnberry Data Strategy & Intelligence team developed a comprehensive solution to improve the overall maturity of this client’s enterprise data governance by growing and enhancing its data cataloging and data quality capabilities. First, we worked with the client to better understand the challenges the organization had faced during previous attempts to implement data governance and quality measures. Next, we assessed the client’s current data catalog approach and governance model to understand what – if anything – already worked well, and what needed to change. Then, we took a three-pronged solution approach based on our findings:

1. In one track, we developed an operating model, strategy, and roadmap to implement an enterprise data catalog for the organization. This enterprise data catalog provided the client a way to promote data literacy, align on shared data definitions, provide transparency through data lineage, and increase users’ trust in the data.
2. In conjunction with the enterprise data catalog, we also designed and implemented a Data Quality Center of Excellence (CoE). This new organization offered a centralized way for the client’s teams to identify, manage, and resolve data quality issues consistently. Turnberry also created a data quality roadmap, including a detailed talent strategy that would allow the client to follow the roadmap from start to finish.
3. Lastly, the Turnberry team worked with the client to define a high-level governance operating model, as well as roles, responsibilities, and related process flows to support the model.

As is our hallmark with all data governance implementations, we worked throughout the life of the initiative to promote data governance concepts and educate key stakeholders on the business value of dependable data.