Data governance is the process of planning, monitoring and enforcing the management of data assets. DAMA states that the objective is to treat data as a strategic asset by providing principles, policies, processes, framework, metrics, and oversight. The goal is to guide data management activities.

An ambitious vision of a company focused on data and its capabilities.

Operating Model for Governance

Data Governance needs to keep it simple and display ground results to secure company endorsement.
Deploy an Operating Model which consists of:

  • Design role and responsibility
  • Identify, train and mentor data owner
  • Steer & support data life cycle
  • Quantify and demonstrate business value of Data Initiatives
  • Apply continuous improvement of value and trust to data
  • Set the pace with Data Architecture team.

Maximize the value and trust of your data

  • Translating your strategic objectives into data objectives and principles
  • Support for data identification with a tailored governance methodology from a catalog
  • Support for organization evolution via a governance model
  • Governance team training
  • Predefined IPCs and positioning of your company on a maturity matrix
  • Roadmap and operational model

"In our approach to data governance, people, processes and tools are the three pillars that converge to transform data into opportunities."

Frédéric ROBERT Data Advisory Director, Expert Data Literacy

Our approach to defining an operational model.

Discovery

  • Gain insight into the context and interview key stakeholders to pinpoint business needs and challenges (pain points).
  • Discover and capitalize on existing efforts.
  • Establish consensus on the path forward and define expectations and success metrics.
  • Develop a project plan.

From vision to action: avoiding pitfalls and maximizing the value of your data.

Main Pitfalls to Avoid

Many data governance initiatives fail not due to a lack of tools, but because of misalignment with organizational realities or an unbalanced approach. Here are the most common pitfalls:

  • Neglecting one of the three pillars: People, Process, Technology
  • Treating governance as a one-shot project instead of a continuous practice
  • Starting too big instead of focusing on SMART, scoped objectives
  • Leading governance purely from IT, without business sponsorship

Maximize the value and trust of your data

At APGAR, we provide end-to-end support to help you structure, operationalize, and scale your data governance efforts:

  • Translate board-level strategy into actionable data governance principles
  • Support data identification with a tailored methodology
  • Design and deploy an operating model for governance
  • Train your governance team on new responsibilities
  • Provide predefined KPIs and position your company on a maturity matrix
  • Build a data governance roadmap aligned with your organization’s evolution

Ils nous ont fait confiance.

Need more information?

Frédéric can advise and support you in your Data Governance program.

Frédéric Robert

Data Advisory Director, Expert Data Literacy