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Identitylab Executive Assessment™

Executive report

Example Organisation · Transformation Readiness Assessment

Illustrative example — not based on a real client assessment.

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Page 01

Executive summary

67/ 100

MaturityDeveloping → Defined
The organisation has a strong technological and operational base, but organisational knowledge, governance and AI readiness currently limit the ability to scale transformation.
Page 02

Executive scorecard

StrategyLeadershipPeopleKnowledgeDataTechnologyAIGovernanceSecurityOperationsInnovation
Scores per dimension on a scale of 0 to 100. Illustrative example.
Executive Transformation Score

67/ 100

Maturity
Developing → Defined
Assessment
Directional management instrument, not an exact measurement
  • Strategy72Integrated
  • Leadership76Integrated
  • People & culture61Defined
  • Knowledge & information48Developing
  • Data55Defined
  • Technology74Integrated
  • AI57Defined
  • Governance52Defined
  • Identity & security68Integrated
  • Processes & operations70Integrated
  • Innovation & growth65Defined
Page 03

Key strengths

  1. 01

    Strong technological foundation74

    Observation
    The platform landscape is standardised, managed and largely cloud-based.
    Business meaning
    New capabilities can be added without first working away technical debt.
  2. 02

    Clear ambition in leadership76

    Observation
    The executive team formulates a consistent direction and acknowledges the need for transformation.
    Business meaning
    Decisions can be taken quickly once priorities are sharpened.
  3. 03

    Operational discipline70

    Observation
    Core processes are documented and followed up with fixed indicators.
    Business meaning
    Automation and AI can be applied to stable processes instead of amplifying chaos.
Page 04

Critical gaps

  1. 01

    Organisational knowledge remains fragmented48

    Observed situation
    Critical knowledge is spread across personal drives, mailboxes and dozens of sites without an owner.
    Possible impact
    Employees lose time, decisions are made on outdated information and AI cannot be deployed reliably.
    Recommended response
    A knowledge architecture with ownership per domain and one validated source per knowledge area.
  2. 02

    AI initiatives lack a governance framework57

    Observed situation
    Several AI experiments are running without shared policy on data, quality, risk and approval.
    Possible impact
    Value stays local, risks become organisation-wide and scaling is re-debated every time.
    Recommended response
    An AI policy with decision rights, a use case portfolio and clear quality and risk criteria.
  3. 03

    Ownership of transformation is scattered52

    Observed situation
    Initiatives are driven per department, without one place where priorities and dependencies come together.
    Possible impact
    Budget and capacity are diluted across too many simultaneous tracks.
    Recommended response
    A transformation portfolio with one owner, a fixed decision rhythm and measurable priorities.
Page 05

Opportunity map

  • 01

    Knowledge architecture

    One structured knowledge model with ownership, metadata and a validated source per domain.

    Knowledge Management · 3–6 months
  • 02

    AI governance

    Policy, decision rights and quality criteria for deploying and scaling AI.

    AI & organisational intelligence · 0–3 months
  • 03

    Enterprise search

    Searching across systems on validated sources, as a step towards AI-supported search.

    Enterprise Search & RAG · 3–9 months
  • 04

    Digital workplace optimisation

    Align Microsoft 365 and collaboration structures with the way teams actually work.

    Cloud & Digital Workplace · 0–6 months
  • 05

    Process automation

    Automate repetitive steps in core processes where quality and volume justify it.

    Business Process Optimisation · 6–12 months
  • 06

    IAM optimisation

    Simplify and automate roles, rights and access reviews.

    Identity & Access Management · 3–9 months
  • 07

    AI use case portfolio

    A limited, prioritised set of use cases with owner, value assessment and measurement points.

    AI strategy & adoption · 3–6 months
Page 06

Priority matrix

Example initiatives

Hover over an initiative for more explanation.

Page 07

Recommendations

Knowledge architecture

3–6 months
What
One structured knowledge model with ownership, metadata and a validated source per domain.
Why
Without reliable knowledge, AI and digital collaboration deliver no lasting value.
Expected impact
Less search time, better decisions and a usable basis for AI.
Next step
Record knowledge domains and owners in a working session with the executives involved.
Knowledge Managementimpact very high · effort medium

AI governance

0–3 months
What
Policy, decision rights and quality criteria for deploying and scaling AI.
Why
Governance is the fastest way to turn experiments into controlled scaling.
Expected impact
Approve what has value faster, stop what does not in a controlled way.
Next step
Record AI principles and the approval path in one executive decision.
AI & organisational intelligenceimpact high · effort low

Enterprise search

3–9 months
What
Searching across systems on validated sources, as a step towards AI-supported search.
Why
Findability is the first tangible win for every employee.
Expected impact
Demonstrably less search time and less duplicate work.
Next step
Map search scenarios per role and unlock a first domain.
Enterprise Search & RAGimpact high · effort medium

Digital workplace optimisation

0–6 months
What
Align Microsoft 365 and collaboration structures with the way teams actually work.
Why
Small interventions in structure and habits quickly bring noticeable calm.
Expected impact
Higher adoption and fewer shadow solutions.
Next step
Review the structure and rights model per team.
Cloud & Digital Workplaceimpact medium · effort low
Page 08

Roadmap

  1. 01

    0–3 months

    Foundation
    • Record ownership of transformation
    • Consolidate priorities into one portfolio
    • Define AI principles and decision rights
    • Identify critical knowledge gaps
  2. 02

    3–6 months

    Enable
    • Knowledge architecture and ownership per domain
    • Make governance operational
    • Execute first priority use cases
    • Optimise the digital workplace
  3. 03

    6–12 months

    Scale
    • AI agents in core processes
    • Automation of repetitive work
    • Enterprise knowledge unlocking
    • Transformation programmes with fixed follow-up
  4. 04

    12–24 months

    Optimise
    • Continuous improvement based on measurements
    • More advanced AI applications
    • Organisational intelligence as a permanent capability
    • Scalable digital capabilities
Page 09

Turn insight into action.

Recommended next step: an Executive Transformation Blueprint, in which the executive team records priorities, ownership and measurement points.

Discuss the findings Our methodology

Illustrative example — not based on a real client assessment.