Data Governance Initiative for a Food Manufacturer Case Study
Clarkston Consulting recently partnered with a client on a data governance initiative. The client is a family-owned food manufacturer with over 70 years’ experience in the industry. The organization is evolving and undergoing a digital transformation to support the growing needs of the business. As the company continues to grow, the emphasis on governing organizational data assets and managing the value of their assets has increased.
As the company expanded and matured in their technology landscape, the client identified the opportunity for improvement within their digital transformation journey. Without data standards, policies and organization around data management, the client recognized this as a crucial gap to address to be able to become more effective and efficient using data and technology. As a result, the client engaged Clarkston to develop a data governance program to improve data maturity and business agility, while enhancing the business’ understanding, usage and management of data
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The primary objectives for the data governance initiative team included: identifying and developing strategies to resolve data related issues and pain points and educating stakeholders while encouraging a culture around data organization and management to ensure effective, clean, and consistent use of data. This resulted in the team administering a digital transformation survey to gain insights into the organization. They also conducted a Data Management Maturity Analysis to provide a current state assessment of data capabilities to highlight areas of improvement and reach data management goals. The team was focused on producing comprehensive data governance baseline assessments, including data architecture, organizational, and process recommendations.
The key benefits of the data governance initiative included, but were not limited to: formalized Data Governance body throughout the organization with a focus on improving data quality and processes, clear organizational process to identify, document, and resolve data related issues, and increased visibility to all systems, data sets, reports, and data owners.
