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Assessment Prepares Telecom Business for New Data Governance Roadmap

A current-state assessment of our client’s business’ data governance program revealed opportunities for developing an enterprise operating model and choosing a metadata tool that supported the project team’s goals of a more recognized and mature governance program.


Our client is a leading broadband communications provider, serving nearly 1.1 million residential and business customers with scalable, cost-effective solutions that help companies grow, compete and succeed. It originally evolved from a traditional cable provider to a full-service provider connecting customers to work, family and entertainment.

Industry: Broadband communications

Background: This client needed a comprehensive data governance strategy and roadmap to reach its growth and maturity targets. Although it deemed data protection and compliance important, the client struggled with manual processes and siloed teams that distrusted the data. It needed help finding ways to improve operations, reporting and business analytics. The client also required a third-party metadata management tool but needed help knowing where to begin and what capabilities it needed.

Engagement Type

Provide a current data governance assessment to to help develop a comprehensive data governance roadmap.

Opportunity Areas

  • Develop a comprehensive data governance strategy and roadmap to maximize the value of enterprise data assets to achieve growth and maturity targets
  • Ensure data governance strategies are adopted and communicated effectively
  • Provide guidance to help improve operations functions, develop reports and support business analytics
  • Assist in the selection of a third-party metadata management tool that best supports data governance capabilities and requirements and drives enterprise data growth and maturity

Engagement Snapshot

Growth, Goals and Governance

For our client to achieve its long-term goals and objectives, a critical aspect of our engagement was to guide them in three primary ways that include:

  • Current-state assessment: FSFP provided a detailed evaluation, recommendations and roadmap for the existing data governance program, as well as a short- and long-term plan for developing an enterprise operating model, enterprise awareness and marketing, and an enterprise metadata tool selection and implementation plan. The program focused on business strategies for success.
  • Flex Bench: FSFP provided resources (Flex Bench) designated to support and cross-train the client’s enterprise data governance team and burgeoning data council to meet immediate needs and provide the support needed to onboard additional resources to staff the governance team in the future.
  • Metadata management tool selection and purchase: Using a robust set of RFP and proof-of-concept (POC) requirements and execution plans, we helped the client evaluate, assess, purchase and implement the tools necessary to support the growth and maturity of its data governance program.


Our engagement with the client resulted in the following outcomes:

  • Data governance goals are aligned with current business objectives in a short-term (3 –6 months) and long-term (three-year) strategic roadmap.
  • The client’s comprehensive and flexible data governance operating model supports decision-making and active enterprise engagement across all business functions.
  • Our client developed a comprehensive metadata management roadmap and is developing robust capabilities for defining enterprise critical data, ensuring data stewardship, and making data discoverable, consumable and trustworthy.
  • Soon, the client will conduct RFPs and vendor POCs to select, buy and implement a metadata management system.

Plans for the Future

We look forward to further developing the client’s existing data governance strategies, which include:

  • Comprehensive metadata management tool RFP and selection process to build out future capabilities
  • Continued maturity of data quality, master data management and data lineaging in a second and third phases
  • Focus on enabling customer self-service (AI and machine learning for external self-service), internal self-service and customer needs (BI, analytics and data science)