Data & AI Literacy Insight:
DATA LITERACY SCORE
- At what stage is your organization in its data maturity journey?
- Which categories are strong, and which require further investment?
- What are the hidden barriers within your data culture?
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20-25 minutes
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50 Likert + 2 Multi-Select+ 1 open-ended question
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20 participants (Team/Organization)
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Data & AI Literacy Insight
What is the Data Literacy Score?
Data Literacy Score™ is an organizational assessment built on five years of research and insights gathered from thousands of professionals. It provides a clear picture of your company’s level of data literacy and delivers actionable insights for improvement.
The assessment consists of 50 Likert-scale questions, multiple-choice questions designed to identify strengths and barriers, and open-ended questions that capture the subjective insights of your team members.
7 Category Comprehensive Assessment
Purpose
Is data being used to achieve core organizational goals?
Data
Is high-quality data accessible to those who need it?
People
Do employees have the right knowledge and skills?
Culture
Does the team culture encourage the use of data?
Ethics
Is data used for positive purposes, or could it be used in harmful ways?
Technology
Are the right tools and systems being used?
Process
Do processes effectively leverage data?
6 Powerful Assessment Components
Customizable categorical questions (for subgroup analysis)
Fifty subjective scoring questions (Data Literacy)
Two multiple-choice questions (strengths & barriers)
One open-ended question (employee suggestions)
OPTIONAL: 15 AI literacy questions
OPTIONAL: Objective knowledge test questions
What Does the Data Literacy Score Provide for Your Organization?
| Challenge | Cost | Solution | Outcome |
|---|---|---|---|
| Uncertainty about literacy levels | Misguided investments | 5-stage literacy model | Clear roadmap |
| Category blindness | Partial improvement | 7-category analysis | Holistic view |
| Hidden barriers | Resistance to change | Identification of barriers | Targeted intervention |
| Subjective evaluation | Reliability concerns | Objective test questions | Proven capability |
| Gaps in AI readiness | Risk of falling behind | AI literacy component | Future-ready organization |