David StottMBA

Executive Assessment

Enterprise Data Readiness Assessment

Assess whether enterprise data can support trusted decisions, integrated work, analytics, and responsible AI use.

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Weighted Readiness Profile

Score the operating evidence, not the ambition.

Use a five-point scale. All questions are required so each weighted dimension is represented in the executive summary.

0 of 18 questions0% complete
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01

15% weight

Business purpose

Priority data is connected to business decisions, capabilities, and outcomes.

1Priority data is tied to defined business decisions and outcomes.
2The organization can distinguish critical data from data that is merely available.
3Data investment priorities reflect business capability needs.
02

20% weight

Ownership and governance

Business accountability and decision rights for data are operational.

1Critical data domains have accountable business owners.
2Stewardship responsibilities and decision rights are clear.
3Governance resolves definitions, access, quality, and risk issues at the required pace.
03

20% weight

Quality and definitions

Critical information is consistently defined and fit for intended use.

1Material business terms and metrics have agreed definitions.
2Data quality is measured against intended use rather than generic completeness.
3Quality issues have visible owners, impact, priority, and resolution evidence.
04

15% weight

Access and integration

Trusted information moves with work across system and organizational boundaries.

1Authorized users can access fit-for-purpose information when decisions occur.
2Authoritative sources and integration responsibilities are explicit.
3Teams do not routinely rebuild the same context through spreadsheets or manual reconciliation.
05

15% weight

Privacy, security, and lifecycle

Use, protection, retention, lineage, and disposal controls match business and regulatory obligations.

1Data classification and permissible use are understood.
2Privacy, security, retention, lineage, and disposal controls are applied consistently.
3Control exceptions and incidents have accountable escalation and response.
06

15% weight

Decision and AI fitness

Data limitations are understood for analytics, automation, and AI-enabled decisions.

1Data timeliness and context match the decisions it supports.
2Limitations, uncertainty, representativeness, and potential bias are documented.
3AI and analytics outputs can be traced to governed evidence where the risk requires it.

Answer all questions to calculate the weighted result.