ServicesData & AIHealth CheckFixed scope · weeks
An independent, practical view of your data health.
Get a clear read on the health of your data so you can prioritise what matters, reduce delivery risk, and get the benefits your business needs from your data, with confidence.
The offer
A clear view of data health, risk and readiness.
Turn fragmented data into trusted insight and measurable value.
A rapid, structured assessment of your data landscape (governance, architecture, quality, reporting and platform utilisation), benchmarked against best practice, with a prioritised roadmap to improve trust, accessibility and the strategic use of your data.
In just weeks, you gain clarity on:
- Where your data is fragmented, duplicated or under-utilised
- Why reporting and dashboards are slow or unreliable
- Risks across governance, security and compliance
- Opportunities to unlock AI, automation and advanced analytics
- The practical steps to move from reactive reporting to proactive insight
Best for: executives, sponsors and delivery leaders seeking an objective view of data health and a practical roadmap for improvement.
Why it matters
Confidence, alignment and a clear path forward.
Confidence
An independent view of the health of your data environment, so leadership decisions are based on trusted, reliable and secure information.
Alignment
A clear understanding of how your data supports strategy, performance, customer outcomes and growth, beyond siloed systems and reporting.
Actionable
A prioritised roadmap that cuts through complexity and focuses funding and effort on the initiatives that deliver measurable business value.
Readiness
A view of whether your data foundations can support advanced analytics, automation and AI, and what needs to change to unlock future capability.
Your outcomes
Clear insight. Stronger control. A roadmap to unlock the full value of your data.
Through targeted stakeholder interviews, platform reviews and artefact analysis, we benchmark your current data maturity against industry best practice and contemporary delivery models. We assess not just technology, but the operating model, ownership, controls and behaviours required to turn data into measurable value.
A clear, practical set of findings and recommendations.
Rather than producing a theoretical strategy, we deliver actionable direction: strengthening trust in your data, improving decision-making speed, and positioning your organisation for digital and AI-driven growth.
Our method
A structured, evidence-based assessment.
Our Data Health Check combines executive interviews, stakeholder workshops, and artefact and platform reviews to assess the health of your data environment. We benchmark current practices against recognised standards for data governance, analytics maturity and modern data platform architecture.
Our method considers both traditional data management disciplines and contemporary data delivery approaches, including cloud-native platforms, real-time analytics, AI enablement and data-product thinking.
- Step 01
Executive interviews
We hear directly from leaders and sponsors on ambition, pain points and where data must perform.
- Step 02
Stakeholder workshops
Working sessions across the business surface how data is produced, governed and consumed day to day.
- Step 03
Artefact & platform reviews
We examine architecture, pipelines, reporting and controls against the evidence, not the org chart.
- Step 04
Benchmark & roadmap
We measure maturity against best practice and sequence the moves that matter most, first.
What we assess
Ten areas of focus.
Data Strategy
The strategic direction for data: vision, objectives, investment rationale, and how data enables business outcomes. Ensures data investment is purposeful, measurable and aligned.
Data Governance
The framework of decision rights, accountability, policies and forums used to govern data assets. Ensures data is managed consistently, with clear accountability across domains.
Data Architecture
The structures, platforms, integration patterns and design standards used to collect, store, transform and distribute data. Ensures the ecosystem is scalable, maintainable and consistent.
Quality Management
The processes and controls used to define, measure, monitor and improve accuracy, completeness, timeliness and consistency. Ensures data is fit for purpose and trusted in reporting.
Operations Management
The day-to-day capability to run, support and continuously improve data pipelines, platforms and services. Ensures data services are stable, predictable and resilient.
Security & Privacy
The controls used to protect data from unauthorised access and misuse, while meeting privacy obligations. Ensures sensitive data is protected and risk exposure is reduced.
Usage & Analytics
The ability to enable consumption of trusted data for reporting, analytics and operational decisions. Ensures data is actually used to improve decision quality and outcomes.
Risk Management
The approach to identifying, assessing and mitigating data risk: quality, security, compliance, availability and misuse. Minimises operational and regulatory exposure.
Change Management
The structured approach to driving adoption of data practices, roles, tools and behaviours. Ensures new ways of working stick and people can operate in the new model.
Performance Management
The measurement of data capability using defined metrics, targets and continuous improvement. Ensures performance is visible and uplift is prioritised over time.