Purpose
To help Data, Engineering & Analytics (DE&A) leaders assess current maturity across the five BHAG areas, identify natural strengths, and agree three actions to progress capability and culture.
BHAG 1: Culture & Stakeholder Engagement
Theme: How people use, trust, and talk about data and information.
Ask:
- How often are data or information sources referenced in business discussions or decisions?
- ☐ Rarely or inconsistently
- ☐ Occasionally, often led by individuals
- ☐ Regularly in some teams or reviews
- ☐ Routinely across projects and management levels
- ☐ Embedded as standard practice across the organisation
- How well do teams understand where their data and insights come from?
- ☐ Very limited understanding
- ☐ Some awareness in technical teams only
- ☐ Most teams can identify their main sources
- ☐ Teams routinely check provenance before using data
- ☐ Data lineage and ownership are clearly communicated and understood organisation-wide
- How is data confidence built and maintained within your team?
- ☐ Not actively discussed
- ☐ Based on trust in certain reports or individuals
- ☐ Verified through defined processes for accuracy
- ☐ Supported by quality metrics, reviews, or governance dashboards
- ☐ Fully embedded in the way teams work and make decisions
BHAG 2: Data Acquisition & Integration
Theme: How reliably and efficiently data moves across systems and sources.
Ask:
- How are key datasets shared or exchanged between systems?
- ☐ Manual export/import (e.g. spreadsheets)
- ☐ Automated in some areas
- ☐ Consistent automated integrations across key systems
- ☐ Standardised and reusable interfaces
- ☐ Fully orchestrated integrations with monitoring and version control
- How is data quality maintained during transfer or integration?
- ☐ No defined checks
- ☐ Basic checks (e.g. row counts)
- ☐ Defined validation rules for core integrations
- ☐ Continuous monitoring and alerting for data drift or anomalies
- ☐ Self-healing or automated correction processes are in place
- How easily can a new data source be connected into your environment?
- ☐ Requires bespoke development
- ☐ Possible with moderate effort
- ☐ Straightforward using known patterns or templates
- ☐ Mostly automated through metadata-driven design
- ☐ Fully adaptive — new data sources integrate with minimal human intervention
BHAG 3: Analytics & Insights
Theme: How effectively insight is created, shared, and acted upon.
Ask:
- How are insights currently delivered?
- ☐ Static reports with limited interactivity
- ☐ Dashboards refreshed manually
- ☐ Automated dashboards with standard metrics
- ☐ Interactive BI tools used by business users
- ☐ Embedded analytics and predictive models driving proactive decisions
- How well do reports and dashboards align with strategic and operational needs?
- ☐ Reactive — mainly focused on past activity
- ☐ Some strategic indicators emerging
- ☐ Balanced mix of operational and forward-looking metrics
- ☐ Fully aligned with business KPIs and planning cycles
- ☐ Continuously refined through feedback and performance review
- How accessible is insight to non-technical users?
- ☐ Limited to data teams
- ☐ Shared via email or presentation
- ☐ Available in central BI portals
- ☐ Self-service exploration encouraged and supported
- ☐ Insight embedded directly in daily business systems or apps
BHAG 4: Platform & Tools
Theme: How stable, scalable, and intelligent the technical environment is.
Ask:
- How consistent and reliable is your current data platform?
- ☐ Prone to outages or inconsistencies
- ☐ Stable in core areas
- ☐ Monitored and maintained through defined processes
- ☐ Optimised for cost, performance, and scale
- ☐ Predictive, self-monitoring, and seamlessly integrated with future technologies
- How are new tools or technologies adopted?
- ☐ Ad hoc, driven by individual initiatives
- ☐ Piloted within teams with limited integration
- ☐ Assessed and approved through governance
- ☐ Standardised and rolled out with training and support
- ☐ Continuously improved through innovation and automation
- How accessible are tools for analysis, integration, and visualisation?
- ☐ Restricted to specialists
- ☐ Available but difficult to use
- ☐ Supported by documentation and common standards
- ☐ Easy to access with self-service capability
- ☐ Unified, secure, and designed around user experience and innovation
BHAG 5: Data Governance & Quality
Theme: How trusted, ethical, and well-managed data is across its lifecycle.
Ask:
- How are data ownership and stewardship managed?
- ☐ Unclear or informal
- ☐ Some roles identified for key datasets
- ☐ Formal owners and stewards assigned with responsibilities
- ☐ Fully embedded in business operations and data workflows
- ☐ Widely understood, with active collaboration between stewards and users
- How visible is data quality across systems?
- ☐ Quality issues identified reactively
- ☐ Ad hoc checks and reviews
- ☐ Routine measurement and reporting on quality
- ☐ Continuous monitoring with remediation processes
- ☐ Automated, governed, and transparently communicated quality management
- How is compliance and ethical data use assured?
- ☐ Dependent on individual awareness
- ☐ Guided by general policy documents
- ☐ Supported by formal governance processes
- ☐ Embedded in automation, access control, and audit trails
- ☐ Proactively managed, with ethical principles visible in decision-making