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Data Quality Assessment and Vendor Evaluation Lay Groundwork for RFI

By Melanie Deardorff

Our client’s focus on data quality could have been more consistent because only some of its business areas actively monitored quality and quality best practices. The First San Francisco Partners team helped the client set new guidelines for quality consistency across the organization while allowing specific business areas the flexibility to monitor quality in ways that best served their areas.


Industry: Financial services

Background: Wealth management division of an almost century-old investment management firm

Engagement Type

Data quality assessment and tool recommendation, including support for the company’s RFI (request for information) inquiry

Opportunity Areas

  • Improve data quality and enterprise reporting across business units
  • Evaluate the effectiveness of the federated-style* governance office to improve governance of data quality and enterprise guidance and oversight
  • Implement an enterprise-wide data quality tool

Engagement Snapshot

Data change impact assessment

  • Support data quality work and provide a data-change impact assessment definition
  • Identify process entry points and develop a standard to define the process for data-change initiation, review, approval and implementation
  • Process includes utilization of the data governance operating model to ensure and uphold communication around and completion of impact assessments
  • Create an end-user questionnaire to qualify changes and score the impact assessment, delivering specific governance recommendations based on survey inputs

Established a data quality framework for the organization to be owned and led by the data governance office

  • Define a future-state target
  • Following vision establishment, define enterprise guidance vs. business-unit autonomy within the federated constructs of the organization
  • Perform gap analysis at organization and business-unit levels to prepare recommendations and detailed roadmap to reach target maturity

Identified three business units and interviewed their team members to assess existing data quality practices and pain points

  • Prioritize use cases across business units to present enterprise need
  • Map requirements to use cases for data quality capabilities and determine necessary guidance from the enterprise

Data quality tool RFI, evaluation and recommendation

  • Establish requirements based on identified use cases
  • Prioritize use cases and requirements accordingly
  • Assess leading tools on the market against the organization’s needs
  • Recommend list of vendors to participate in the RFI process
  • Support RFI process
  • Review responses and provide a short list of vendors to deliver a demo
  • Score demos and provide final recommendation for data quality tool selection


  • Created and used a framework and roadmap to establish an enterprise data quality capability
  • Recommended a data quality tool and an implementation roadmap to prioritize the tool’s capabilities to best support critical use cases
  • Engaged with business units to establish data quality practices according to enterprise guidance and recommendations
  • Client is well-positioned to move forward and choose a data quality tool provider and implement the governance roadmap

*Federated data governance is a centralized strategy with decentralized execution and implementation. The structure can benefit lines of business with differing governance requirements.

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