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BI adoption — Microsoft Fabric / Power BI

How do you sustainably roll out a self-service analytics platform without losing control? Microsoft's answer, structured as a maturity matrix.

≈ 3 min readReading
At a glance
  • Levels 100 to 500 (Initial → Efficient).
  • 12 themes to assess separately.
  • Microsoft advises aiming for at least 300 or 400.
On this page
  1. Profile
  2. Why this matrix matters in my field
  3. The maturity scale
    1. Initial (initial / performed)
    2. Repeatable (repeatable / managed)
    3. Defined (defined)
    4. Capable (capable / measured)
    5. Efficient (efficient / optimizing)
  4. The dimensions assessed
    1. Data culture
    2. Executive sponsorship
    3. Business alignment
    4. Content ownership and management
    5. Content delivery scope
    6. Center of Excellence
    7. Governance
    8. Mentoring and user enablement
    9. Community of practice
    10. User support
    11. System oversight
    12. Change management
  5. How to use it
  6. Limitations and precautions
  7. Sources and verification

Profile#

Publisher
Microsoft
Document
Microsoft Fabric adoption roadmap (formerly Power BI adoption roadmap), a series of articles on Microsoft Learn
Purpose
Guide the adoption of an analytics and BI platform: governance, usage, user support
Organizational scale
5 levels: 100 Initial, 200 Repeatable, 300 Defined, 400 Capable, 500 Efficient
Other scales
Adoption stages for users (4) and adoption phases for solutions (4)
Reference
Aligns with the five levels of the Capability Maturity Model, complemented by ISACA's Data Management Maturity model (retired)
Access
Free, public documentation

Why this matrix matters in my field#

This is the matrix closest to the day-to-day work of a Power BI team: it links governance to the user experience and to the value of solutions. It recalls a simple idea: maturity does not depend on the technology, but on the practices around it — center of excellence, community, training, monitoring, change management.

The maturity scale#

The levels below summarize Microsoft's documentation (version consulted in October 2026). Microsoft specifies that these characteristics are general and that each theme should be assessed independently.

  1. Initial (initial / performed)#

    Starting point: new, undocumented investments, with no process discipline.

    • Pockets of success and experimentation, without a coordinated strategy or governance.
    • Undocumented practices; heavy reliance on tacit knowledge.
    • Few formal data management processes; risk due to lack of awareness of usage.

  2. Repeatable (repeatable / managed)#

    Data management is planned and carried out; defined processes exist but are not applied uniformly.

    • Some content becomes critical or heavily used.
    • Attempts to document repeatable practices, in silos and reactively.
    • An internal community emerges; the value of a center of excellence is recognized.

  3. Defined (defined)#

    Standardized processes are established and applied consistently across organizational boundaries.

    • Measurable success in the use of analytics.
    • The center of excellence is established, with clear objectives and scope.
    • Executive sponsor engaged; roles and responsibilities understood; first governance model.

  4. Capable (capable / measured)#

    Data is well managed throughout its life cycle.

    • Significant value; approved tools for critical content.
    • Governance model accepted by the main business units.
    • Standardized usage monitoring; active network of champions.

  5. Efficient (efficient / optimizing)#

    The focus is on automation and continuous improvement.

    • The value of analytics is widely recognized.
    • Self-sustaining community, not dependent on a few individuals.
    • Indicators are tracked regularly; automation increases productivity or reduces risk.

The dimensions assessed#

Twelve themes structure the article series; Microsoft recommends assessing each one independently.

  • Data culture#

    The place of data in decisions and work habits.

  • A credible, influential person who supports the data culture and platform adoption.

  • Business alignment#

    The extent to which the data culture and strategy help the business units achieve their objectives.

  • Content ownership and management#

    Who creates, owns and maintains content and semantic models.

  • Content delivery scope#

    Personal, team, department or organization: requirements grow with the audience.

  • Center of Excellence#

    Team that defines practices, provides guidance and oversees.

  • Governance#

    Rules, roles, controls proportionate to risk.

  • Mentoring and user enablement#

    Training, documentation, templates, user support.

  • Community of practice#

    Exchanges between users, network of champions.

  • User support#

    Support tiers, escalation paths, documentation.

  • System oversight#

    Auditing, monitoring of usage and capacity, problem detection.

  • Change management#

    Supporting changes to the platform and to practices.

How to use it#

  1. Assess each theme separately; departments within the same organization evolve at different paces.
  2. Aim for at least 300 or 400 (Microsoft's recommendation); aiming for 500 everywhere is unrealistic.
  3. Link organizational maturity to user adoption (awareness, understanding, momentum, proficiency) and to solution value (exploration, functional, valuable, essential).
  4. Prioritize according to risk and value.

Limitations and precautions#

  • The documentation has been renamed (Power BI → Fabric): cite the version and the date consulted.
  • It describes a Microsoft platform; the spirit is transferable, not the detail.
  • The three perspectives (organization, users, solutions) influence one another: progressing on one without the others quickly hits a ceiling.

Sources and verification#