How dashboards, reports, and analytical outputs accurately and consistently represent the organisation's data through agreed definitions and calculations.
DST-01
Enterprise adoption of self-service analytics and a certified semantic layer
How broadly has self-service business intelligence, built on a consistent, certified semantic layer, actually been adopted across the organisation, as opposed to remaining confined to a small number of advanced teams?
Maturity level descriptions
No self-service analytics capability exists organisation-wide; all reporting requires a dedicated technical resource to produce. Business teams cannot access or build their own reports; every analytical request depends on a technical team's availability.
Self-service analytics exists but is confined to a small number of advanced teams, with no consistent semantic layer underpinning it. A handful of technically capable teams use self-service tools independently, each with their own, inconsistent definitions.
A certified semantic layer exists and self-service analytics is available to priority business units, with defined metric definitions. Priority business units access self-service analytics tools drawing on a certified semantic layer with agreed metric definitions.
Self-service analytics adoption is tracked across the organisation, with usage and semantic layer coverage expanding on a defined roadmap and reported to the executive team. Adoption metrics and semantic layer coverage are tracked against a roadmap, with expansion progress reported to the executive team.
Self-service analytics on a certified semantic layer is the organisation-wide default, with adoption and trust measured as a standing enterprise capability metric benchmarked externally. Self-service, semantic-layer-backed analytics is the default way business teams access insight organisation-wide, with adoption and trust levels benchmarked against external standards.
DST-02
Standardised KPI reporting and single source of truth
When the executive team or board looks at a key performance indicator, how confident can they be that everyone in the organisation, looking at the same KPI, sees the same number, calculated the same way?
Maturity level descriptions
The same KPI routinely shows different values depending on who produced the report, with no single source of truth and no awareness this is a systemic problem. Different teams calculate and report the same named KPI differently, with no mechanism to reconcile or prevent divergence.
Inconsistencies are noticed occasionally and resolved case by case, without a systemic fix or governed definition process. KPI discrepancies are investigated and resolved individually when noticed, without addressing the underlying lack of a governed definition.
A governed process exists for defining and certifying enterprise KPIs, with priority KPIs having a single, documented, agreed calculation. Priority enterprise KPIs are defined and certified through a governed process, with the agreed calculation documented and communicated.
All material enterprise KPIs are certified and consistency is systematically checked across reports, with discrepancies tracked to resolution. Comprehensive KPI certification covers all material enterprise metrics, with systematic consistency checks and tracked resolution of any discrepancy found.
All enterprise KPIs are calculated from exactly one governed source, making divergent calculation structurally impossible, with the executive team and board relying on this as a trusted, single source of truth. Certified KPI calculations exist in exactly one governed location that all reports and dashboards reference, eliminating the structural possibility of divergence.
DST-03
Business teams' ability to discover and consume certified assets
How easily can business teams across the organisation find and confidently use certified, trustworthy data assets (datasets, reports, metrics), without relying on personal networks or tribal knowledge to know what exists and what can be trusted?
Maturity level descriptions
Certified data assets, where they exist, are not discoverable by business teams; finding anything requires knowing exactly who to ask. Business teams have no way to search for or discover available data assets; access depends entirely on personal relationships and informal knowledge.
Some assets are discoverable through scattered, informal channels, but there is no organisation-wide catalogue or trust signal. Assets can sometimes be found through known but informal channels (shared drives, team contacts), without a searchable, trust-indicating catalogue.
A data catalogue exists, covering priority certified assets, with basic trust or certification indicators, accessible to business teams. A searchable catalogue covering priority assets, with certification status visible, is accessible to business teams organisation-wide.
Catalogue coverage extends across all material certified assets, with usage tracked to understand and improve business team discovery and adoption. Comprehensive catalogue coverage is tracked for usage, with discovery and adoption patterns actively used to improve the catalogue's value to business teams.
Certified assets are proactively surfaced to business teams at the point of need (e.g. embedded in tools they already use), with discovery friction treated as a measured, continuously improved enterprise experience. Certified assets are surfaced directly within the tools business teams already use, with discovery experience measured and continuously improved as a standing capability.