How the organisation defines its data strategy and translates strategic enterprise data goals into measurable domain value, priorities, and investment decisions.
STR-CON-01
Awareness of data strategy
How clearly is the organisation’s Data Strategy communicated to you as a Data Consumer, and translated into practical guidance on how you are expected to find, use and rely on data in your day-to-day work?
Maturity level descriptions
No Data Strategy exists, or nothing about it has ever reached business users; the Data Consumer works with data with no reference to any stated organisational direction. Decisions about which data to use, and how, are made on individual habit or convenience, with no strategic direction available even if the Data Consumer sought it.
A Data Strategy exists, but it has not been communicated in terms meaningful to business users; awareness is incidental rather than deliberate. The Data Consumer may know a strategy document exists (through a town hall mention or an intranet link) but has not read it and has received no interpretation of what it means for their role.
The Data Strategy is communicated to business users through defined channels (briefings, onboarding, team-level summaries), with basic translation into what it means for how they use data. The Data Consumer has received at least one structured briefing or written summary explaining the strategy’s implications for business use of data, and can reference it when deciding how to source or use data.
Strategy communication to business users is systematic and measured — delivered on a defined cycle, with awareness and comprehension actively checked rather than assumed. The Data Consumer participates in periodic strategy refreshers, and the organisation measures business-user awareness (e.g. through a survey or completion tracking) and acts on the result.
Strategy communication is continuous and adaptive: business users are proactively informed of changes as they occur, and their understanding is treated as a measured outcome of strategy execution. The Data Consumer is notified of strategy changes affecting their work as they happen, and business-user comprehension is reported as a strategy execution metric rather than a communications activity.
STR-CON-02
Alignment of data provision to business goals
To what extent do the datasets, reports and dashboards actually made available to you reflect your team’s stated business objectives, as opposed to being whatever happens to have been built historically or requested most loudly?
Maturity level descriptions
The data and reports available to the Data Consumer bear no deliberate relationship to business objectives; provision is entirely historical or accidental. The Data Consumer uses whatever reports happen to exist, with no process ever having connected those assets to what the team is actually trying to achieve.
An informal sense exists of which data matters to the business, but nothing documented connects data provision to objectives. The Data Consumer and their manager have an informal view of which reports are “the important ones”, based on experience rather than any documented prioritisation.
A documented process exists for relating requested and provided data assets to business objectives, and is applied to significant new requests. When the Data Consumer’s team requests a new report or dataset, the request records which business objective it supports, using an available template or intake form.
Alignment between provided data assets and business objectives is tracked and reviewed on a defined cycle, with unaligned or unused assets identified. The Data Consumer’s area participates in a periodic review of its data assets against current objectives, with usage measured and obsolete reports retired.
Data provision is continuously optimised against evolving business objectives, with the Data Consumer’s changing needs actively anticipated rather than reactively serviced. Usage analytics and objective changes trigger proactive re-provisioning of data assets, and the Data Consumer is consulted when objectives shift rather than after reports break.
STR-CON-03
Feedback loop
When you have a data need that is unmet — data you cannot get, a report that does not exist, or an obstacle that stops you using data in your decisions — how effectively does that reach the people who set the organisation’s Data Strategy?
Maturity level descriptions
No mechanism exists for a Data Consumer’s unmet data needs to reach strategy owners; needs are worked around locally or simply abandoned. The Data Consumer builds a manual workaround (a personal spreadsheet, a request to a colleague) and the underlying need is never recorded anywhere.
An informal channel exists (a manager who sometimes passes things on), used inconsistently and with no visibility of outcome. The Data Consumer occasionally raises a need to a manager or a familiar analyst, with no record kept and no expectation of a response.
A defined channel exists (a forum, an intake form, a request category) that business users are expected to use to raise unmet data needs. The Data Consumer has used a specific, named mechanism at least once to register an unmet data need, and the process for doing so is documented.
Business-user feedback is systematically collected, tracked and reported back, closing the loop on outcomes. The Data Consumer receives acknowledgement of a raised need, a status update, and can see it either reflected in a plan or explicitly declined with reasoning.
Business-user experience is treated as a primary strategic input, proactively sought during strategy review cycles rather than passively received. The Data Consumer is consulted as part of structured strategy reviews and can point to evidence of business-user input shaping a strategic decision.
STR-CON-04
Prioritisation and investment justification
When your area needs investment in data — a new data source, a fixed report, better access, or a tool — how transparent and strategy-based is the process by which that request is prioritised or declined?
Maturity level descriptions
Requests for data investment are approved or declined on an ad hoc, relationship-driven basis, with no visible criteria and no reference to strategy. The Data Consumer’s outcome depends on who they ask and how well they know them, with no explanation given when a request goes nowhere.
Some sense exists that requests should be justified against business value, but no structured process or criteria are applied. The Data Consumer is sometimes asked to explain why a request matters, but the explanation is not assessed against any consistent standard.
A documented request and prioritisation process exists, referencing strategic goals, and business users are expected to use it. The Data Consumer submits requests through a defined intake process that asks for the business benefit and the strategic goal supported, and receives a decision.
Prioritisation decisions are consistently made against documented criteria tied to strategic value, with outcomes and rationale tracked and visible to requesters. The Data Consumer can see where their request sits in a prioritised backlog and why it was ranked as it was, with decisions tracked over time.
Strategic contribution is the well-understood basis for securing data investment; business users can reliably anticipate and shape outcomes, and prioritisation adapts as strategy shifts. The Data Consumer routinely frames requests in strategic terms as standard practice, and the backlog is dynamically re-prioritised as strategic priorities change.
STR-CON-05
Strategic direction on AI use of data
How clearly does the organisation’s Data Strategy tell you, as a Data Consumer, which data you may use in AI/GenAI tools, for what purposes, and under what constraints?
Maturity level descriptions
No strategic direction reaches business users on AI/GenAI use of data; the Data Consumer uses AI tools with organisational data, or avoids them, with no guidance either way. Business data is pasted into publicly available GenAI tools, or deliberately withheld from approved ones, purely on individual judgement.
General awareness exists that AI is an organisational priority, but nothing connects that to what a Data Consumer may or may not do with data. The Data Consumer has heard AI described as a priority but has received no guidance on which data may be used with which tools.
Documented guidance exists, communicated to business users, stating which categories of data may be used in which AI tools and what baseline constraints apply. The Data Consumer can consult a written list or classification identifying approved AI tools, approved data categories, and baseline restrictions such as no personal information in public tools.
AI data-use guidance for business users is reviewed and updated on a defined cycle, differentiated by use case and risk, with adherence monitored. The Data Consumer receives guidance that distinguishes between use cases (drafting, summarising, analysis) with different data rules, and adherence is periodically checked.
Guidance is dynamic: as tools and use cases change, business users are proactively notified before new capability becomes available to them. The Data Consumer is informed of changes to permitted AI data use ahead of a new tool being enabled, so guidance never lags actual capability.
STR-CON-06
Maturity assessment participation
How regularly are you, as a business consumer of data, actually included in the organisation’s assessment of its own data maturity, and do you see improvement resulting from it?
Maturity level descriptions
Data maturity is never assessed, or business users are never included; the Data Consumer has no awareness of any such exercise. Any view of how well the organisation manages data is anecdotal, and business users are never asked for their experience.
A one-off assessment has occurred, but business-user input was incidental and no improvement was visibly linked to it. The Data Consumer may recall being asked a few questions once, with no feedback and no observable follow-up.
A defined periodic assessment process exists that formally includes business consumers, producing a documented current and target state. The Data Consumer participates in a scheduled assessment using a consistent instrument, and results are captured in an accessible document.
Assessment findings from business users are translated into tracked improvement actions with owners and timelines, and progress is reviewed on schedule. The Data Consumer can identify at least one improvement in their data experience that traces directly to an assessment finding, with an owner and target date.
Assessment is continuous and embedded, with business-user experience tracked as a trend and used proactively to reprioritise data improvement work. The Data Consumer’s experience is measured across multiple periods, the trend is visible to stakeholders, and it actively informs what gets improved next.