IT Services
IT Services
Services & Consulting
Sourcing
Nearshoring
Solutions
7N Academy
Expertise
Data & AI
Cybersecurity
IT Architecture
Infrastructure & Cloud
Software
IT Project Optimization
Digital Operations
UX & UI Design
Industries
Industries
Energy
Finance
Insurance
Life Science
Logistics
Manufacturing
Public Sector
Retail
Technology
For Consultants
Insights & Cases
Insights & Cases
IT Articles
Case Studies
About
About
Who We Are
Corporate Responsibility
Press & Reports
Contact Us
Newsroom
Careers
Data Maturity Assessment Tool
An evaluation based on 7N's Data Intelligence Transformation Framework
Instructions
Complete all 25 questions across 5 dimensions
Score each question from 1-5 (1 = Not at all, 5 = Excellent)
Click "Generate Excel Report" to download your assessment
The Excel file will include scoring, charts, and recommendations
Dimension 1: Leadership's Understanding og Data Complexity
Q1.1: To what extent does senior leadership understand the technical complexity of your organization's data landscape?
To what extent does senior leadership understand the technical complexity of your organization's data landscape?
Select the score that best reflects your organization's situation ...
1. Leadership has minimal understanding of data complexity
2. Sometimes underestimates requirements, leading to project delays
3. Good recognition with regular strategic data discussions
4. Regular, clear communication of data priorities
5. Limited budget with frequent resource constraints
How well does leadership appreciate the time and resources required for data transformation initiatives?
Select the score that best reflects your organization's situation ...
1. Consistently underestimates time and resource requirements
2. Sometimes underestimates requirements, leading to project delays
3. Generally realistic but occasional misalignment on scope
4. Usually accurate in estimating requirements
5. Consistently realistic and provides adequate resources
To what degree does leadership recognize data as a strategic asset rather than just an operational necessity?
Select the score that best reflects your organization's situation ...
1. Consistently underestimates time and resource requirements
2. Sometimes underestimates requirements, leading to project delays
3. Generally realistic but occasional misalignment on scope
4. Usually accurate in estimating requirements
5. Consistently realistic and provides adequate resources
How effectively does leadership communicate data priorities and vision across the organization?
Select the score that best reflects your organization's situation ...
1. No clear communication of data vision
2. Occasional mentions but unclear priorities
3. Some communication but lacks consistency
4. Regular, clear communication of data priorities
5. Compelling, consistent data vision communicated organization-wide
To what extent does leadership demonstrate commitment through budget allocation and resource dedication to data initiatives?
Select the score that best reflects your organization's situation ...
1. Minimal budget allocation, resources often redirected
2. Limited budget with frequent resource constraints
3. Adequate budget but competing priorities impact resources
4. Good budget allocation with consistent resource support
5. Strong financial commitment with protected data initiative resources
Dimension 2: Organizational Appetite for Foundational Work
How willing is your organization to invest in data infrastructure and foundational capabilities that may not show immediate ROI?
Select the score that best reflects your organization's situation ...
1. Strong resistance to foundational investments
2. Limited willingness, requires immediate ROI justification
3. Some willingness but needs clear short-term benefits
4. Generally supportive of foundational investments
5. Strong appetite for long-term foundational investments
To what degree does your organization prioritize data quality and governance initiatives over quick-win analytics projects?
Select the score that best reflects your organization's situation ...
1. Always prioritizes quick wins over foundational work
2. Rarely invests in governance, prefers immediate results
3. Balances both but leans toward quick wins
4. Good balance with recognition of governance importance
5. Consistently prioritizes foundational governance work
How tolerant is your organization of the temporary disruption that comes with implementing proper data management practices?
Select the score that best reflects your organization's situation ...
1. Very low tolerance, avoids any disruption
2. Limited tolerance, disruption often stops initiatives
3. Moderate tolerance but concerns frequently arise
4. Good tolerance with proper change management
5. High tolerance, views disruption as necessary investment
To what extent does your organization invest in data literacy and skills development across teams?
Select the score that best reflects your organization's situation ...
1. No systematic investment in data skills development
2. Minimal training, mostly ad-hoc learning
3. Some training programs but limited scope
4. Regular skills development with structured programs
5. Comprehensive data literacy programs across all levels
How committed is your organization to standardizing data practices and tools, even when it requires teams to change existing workflows?
Select the score that best reflects your organization's situation ...
1. Strong resistance to standardization efforts
2. Limited commitment, teams often maintain separate practices
3. Some standardization but many exceptions allowed
4. Good commitment with structured standardization approach
5. Strong commitment to organization-wide standardization
Dimension 3: Current Process Documentation and Ownership
To what extent are your data processes formally documented and maintained?
Select the score that best reflects your organization's situation ...
1. No formal documentation exists
2. Minimal documentation, mostly outdated
3. Some documentation but gaps and inconsistencies
4. Good documentation with regular updates
5. Comprehensive, current documentation across all processes
How clearly defined are data ownership and stewardship roles across your organization?
Select the score that best reflects your organization's situation ...
1. No defined data ownership roles
2. Informal ownership, unclear responsibilities
3. Some defined roles but gaps in coverage
4. Well-defined roles with clear accountability
5. Comprehensive ownership model with active stewardship
To what degree are data lineage and dependencies documented and understood?
Select the score that best reflects your organization's situation ...
1. No understanding of data lineage
2. Limited knowledge, mostly tribal knowledge
3. Some documentation but incomplete coverage
4. Good lineage documentation for most critical data
5. Comprehensive data lineage with automated tracking
How well-established are your data quality monitoring and issue resolution processes?
Select the score that best reflects your organization's situation ...
1. No formal quality monitoring processes
2. Ad-hoc quality checks with no systematic approach
3. Basic monitoring but limited resolution processes
4. Good monitoring with defined resolution workflows
5. Comprehensive quality management with proactive monitoring
To what extent are data access and security policies documented and consistently enforced?
Select the score that best reflects your organization's situation ...
1. No formal data access policies
2. Basic policies but inconsistent enforcement
3. Documented policies with moderate enforcement
4. Well-documented policies with good enforcement
5. Comprehensive, consistently enforced security framework
Dimension 4: Technical Debt and Integration Readiness
How would you assess the current state of technical debt in your data systems and infrastructure?
Select the score that best reflects your organization's situation ...
1. Significant technical debt severely limiting capabilities
2. High technical debt creating frequent issues
3. Moderate debt with manageable impact
4. Low debt with occasional technical challenges
5. Minimal technical debt, modern architecture
To what extent can your current systems easily integrate with new data sources and technologies?
Select the score that best reflects your organization's situation ...
1. Very difficult integration, requires extensive custom work
2. Limited integration capabilities, significant effort required
3. Moderate integration ability with some challenges
4. Good integration capabilities with standard approaches
5. Excellent integration readiness with modern APIs and standards
How scalable is your current data architecture to handle growing data volumes and complexity?
Select the score that best reflects your organization's situation ...
1. Not scalable, frequent performance issues
2. Limited scalability, approaching capacity constraints
3. Moderately scalable but requires planning for growth
4. Good scalability with clear growth path
5. Highly scalable, cloud-native architecture
To what degree do you have automated data pipelines and reduced manual data processing?
Select the score that best reflects your organization's situation ...
1. Mostly manual processes with minimal automation
2. Some automation but significant manual intervention required
3. Moderate automation with occasional manual steps
4. Good automation with minimal manual processes
5. Highly automated, self-service data pipelines
How effectively does your technology stack support real-time or near-real-time data processing requirements?
Select the score that best reflects your organization's situation ...
1. No real-time capabilities, batch processing only
2. Limited real-time processing with significant constraints
3. Some real-time capabilities but not comprehensive
4. Good real-time processing for most use cases
5. Comprehensive real-time and streaming capabilities
Dimension 5: Position Relative to Competitors
How does your organization's data analytics capabilities compare to industry leaders in your sector?
Select the score that best reflects your organization's situation ...
1. Significantly behind industry standards
2. Below average compared to industry peers
3. Average capabilities, meeting basic industry standards
4. Above average, approaching industry leaders
5. Industry-leading analytics capabilities
To what extent does your organization leverage advanced analytics and AI/ML compared to industry benchmarks?
Select the score that best reflects your organization's situation ...
1. No advanced analytics or AI/ML usage
2. Very limited use, well behind industry
3. Basic usage, meeting minimum industry expectations
4. Good usage, competitive with industry standards
5. Advanced usage, exceeding industry benchmarks
How does your data governance maturity compare to recognized industry frameworks and best practices?
Select the score that best reflects your organization's situation ...
1. No formal governance, far from industry standards
2. Basic governance, below industry norms
3. Moderate governance, meeting basic industry requirements
4. Good governance, aligned with industry best practices
5. Exemplary governance, exceeding industry standards
To what degree does your organization's data culture and literacy match or exceed industry expectations?
Select the score that best reflects your organization's situation ...
1. Weak data culture, well below industry norms
2. Limited data culture, behind industry peers
3. Developing culture, meeting basic industry expectations
4. Strong culture, competitive with industry leaders
5. Exceptional data culture, setting industry standards
How does your data monetization and value creation compare to industry benchmarks?
Select the score that best reflects your organization's situation ...
1. No measurable data value creation
2. Limited value creation, below industry average
3. Moderate value creation, meeting industry norms
4. Good value creation, above industry average
5. Exceptional value creation, industry-leading ROI
