How data literacy, evidence-backed decision-making, collaboration, and continuous learning are embedded in the organisation's culture.
CUL-01
Enterprise data literacy strategy and investment
Does the organisation have an executive-sponsored data literacy strategy, with defined, resourced learning and development pathways, or does data capability depend entirely on what individuals choose to learn on their own initiative?
Maturity level descriptions
No data literacy strategy exists; whatever data capability exists in the organisation was acquired entirely through individual initiative, with no organisational investment. The organisation provides no structured learning pathway or investment in data literacy; capability depends entirely on what individuals pursue independently.
Some ad hoc training opportunities are available, but there is no strategy, no defined pathway, and no consistent investment. Occasional, unstructured training opportunities may be offered, without a defined strategy or consistent investment commitment.
A data literacy strategy is documented and endorsed, with defined learning pathways for at least priority roles, and a dedicated budget allocation. An endorsed strategy defines learning pathways for priority roles, backed by a dedicated budget allocation.
Literacy pathway participation and outcomes are tracked across the organisation, with investment adjusted based on measured skill gaps and reported to the executive team. Participation and outcome data across literacy pathways inform adjusted investment, reported to the executive team on a defined cycle.
Data literacy is treated as a continuously evolving, benchmarked enterprise capability, with investment proactively adjusted ahead of emerging skill needs (including AI-related literacy) and reported at board level. The literacy strategy proactively anticipates emerging skill needs, including AI-related capability, with investment and outcomes benchmarked externally and reported to the board.
CUL-02
Evidence-backed decision-making as an executive and board norm
At the executive team and board level, how consistently are significant decisions actually backed by data and evidence, as opposed to being made on intuition or precedent, with data invoked only afterward if at all?
Maturity level descriptions
Executive and board decisions are made without reference to data as standard practice; data-based arguments are routinely overridden by seniority or precedent. Significant decisions proceed based on judgement or precedent, with data-backed input rarely sought and easily dismissed when offered.
Data is occasionally referenced in executive discussions, depending on the individual, but is not a consistent or expected input to decisions. Data may be referenced in some executive discussions depending on who is presenting, without it being a consistent expectation.
For significant decisions, referencing supporting data is a defined, expected part of the executive decision process (e.g. a business case template). A defined decision process for significant matters requires supporting data to be presented, generally followed at executive level.
Evidence-backed decision-making is the observed norm at executive and board level for most significant decisions, with decision quality and data usage periodically reviewed. Data-referencing is periodically reviewed as part of executive decision governance, with evidence-backed decisions being the observed norm.
Evidence-backed decision-making is fully embedded in executive and board culture, with decision outcomes tracked against their original data-based rationale and the practice actively modelled and reinforced from the top. The board and executive team proactively bring data into decisions by default, track outcomes against original rationale, and visibly model and reinforce evidence-based practice.
CUL-03
Enterprise cross-functional collaboration model
Has the organisation established and resourced a structural model for collaboration between data functions and business teams at enterprise level, or does effective collaboration depend on individual relationships that happen to exist?
Maturity level descriptions
No structural collaboration model exists between data functions and business teams; interaction, where it happens, is entirely dependent on individual relationships. Data and business teams operate largely separately, with collaboration happening only where individuals have personally built relationships.
Some informal collaboration exists in pockets of the organisation, but there is no enterprise-wide structure, and it is not resourced or sustained deliberately. Pockets of good collaboration exist informally, dependent on specific individuals, without deliberate enterprise-wide structure or resourcing.
A defined enterprise collaboration model exists (e.g. embedded analyst roles, cross-functional forums) applied to priority business areas. A documented model — embedded roles, recurring forums, or similar — is applied to at least priority business areas.
The collaboration model extends across the organisation's material business areas, with effectiveness tracked and reported to the executive team. Comprehensive collaboration model coverage is tracked for effectiveness, with results reported to the executive team on a defined cycle.
Data and business functions operate as a genuinely integrated enterprise capability, with the collaboration model continuously refined based on outcome evidence and treated as a source of competitive advantage. Integration between data and business functions is deep enough that formal mechanisms are refined based on outcomes, with the model recognised as a source of competitive advantage.