Organizations are joining the wave and adopting machine learning and artificial intelligence (AI) to unlock the value in their data and power their competitive advantage. But to succeed with these complex analytics programs, they need to begin by looking at their data – empowering their people to realize and embrace the valuable insights within the organization’s data.
The key to achieve becoming a data-driven organization is to foster a strong data culture and equip employees with data skills through an organization-wide data literacy program.
Our Advice
Critical Insight
- Start with real business problems in a hands-on format to demonstrate the value of data.
- Use a formalized organization-wide approach to data literacy program to bridge the data skills gap.
- Provide relevant and practical training programs tailored to different learning styles and tenures (e.g. onboarding, development plan).
Impact and Result
Data literacy is critical to the success of digital transformation and AI analytics. Info-Tech’s approach to creating a sustainable and effective data literacy program is recognizing it is:
- More than just technical training. A data literacy program isn’t just about data; it encompasses aspects of business, IT, and data.
- More than a one-off exercise. To keep the literacy skills alive the program must be regular, sustainable, and tailored to different needs across all levels of the organization.
- More than one delivery format. Different delivery methods need to be considered to suit various learning styles to ensure an effective delivery.
Member Testimonials
After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.
10.0/10
Overall Impact
$13,700
Average $ Saved
115
Average Days Saved
Client
Experience
Impact
$ Saved
Days Saved
Milwaukee County Department of Administrative Services – Information Management Division (DAS-IMSD)
Guided Implementation
10/10
$13,700
115
Andrea was extremely helpful - I look forward to working with her.
Foster Data-Driven Culture With Data Literacy
Data literacy is an essential part of a data-driven culture, bridging the data knowledge gaps across all levels of the organization.
Analyst Perspective
Data literacy is the missing link to becoming a data-driven organization.
“Digital transformation” and “data driven” are two terms that are inseparable. With organizations accelerating in their digital transformation roadmap implementation, organizations need to invest in developing data skills with their people. Talent is scarce and the demand for data skills is huge, with 70% of employees expected to work heavily with data by 2025. There is no time like the present to launch an organization-wide data literacy program to bridge the data knowledge gap and foster a data-driven culture.
Data literacy training is as important as your cybersecurity training. It impacts all levels of the organization. Data literacy is critical to success with digital transformation and AI analytics.
Annabel Lui
Principal Advisory Director, Data & Analytics Practice
Info-Tech Research Group
Executive Summary
Your ChallengeOrganizations are joining the wave and adopting machine learning (ML) and artificial intelligence (AI) to unlock the value in their data and power their competitive advantage. But to succeed with these complex analytics programs, they need to begin by empowering their people to realize and embrace the valuable insights within the organization’s data. The key to becoming a data-driven organization is to foster a strong data culture and equip people with data skills through an organization-wide data literacy program. |
Common ObstaclesChallenges the data leadership is likely to face as digital transformation initiatives drive intensified competition:
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Info-Tech's ApproachWe interviewed data leaders and instructors to gather insights about investing in data:
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Info-Tech Insight
By thoughtfully designing a data literacy training program for the audience's own experience, maturity level, and learning style, organizations build the data-driven and engaged culture that helps them to unlock their data's full potential and outperform other organizations.
Your Challenge
Data literacy is the missing link to drive business outcomes from data.
- Having a data-driven culture as an organization’s mission statement without implementing a data literacy program is like making an empty promise and leaving the value unrealized and unattainable.
- A study conducted by the Data Literacy Project clearly indicates that organizations with aggressive data literacy programs will outperform those who do not have such programs. By 2030, data literacy will be one of the most sought-after skill sets. All employees require data literacy skills.
- Everyone has a role in data. From employees who are actively involved in data collection to operational teams who create reports with analytics tools and finally to executives who use data to make business decisions – they all require continuous data literacy training in a data-driven organization. Because of differences in maturity, data literacy strategies cannot be one-size-fits-all.
“Data literacy is the ability to read, work with, analyze, and communicate with data. It's a skill that empowers all levels of workers to ask the right questions of data and machines, build knowledge, make decisions, and communicate meaning to others.” – Qlik, n.d.
75% of organizational employees have access to data tools – only 21% demonstrated confidence in their data skills.
Source: Accenture, 2020.
89% of C-level executives expect team members to explain how data has informed their decisions, but only 11% employees are fully confident in their ability to read, analyze, work with, and communicate with data
Source: Qlik, 2022.
Data debt or data asset?
Manage your data as strategic assets.
“[Data debt is] when you have undocumented, unused, incomplete, and inconsistent data,” according to Secoda (2023). “When … data debt is not solved, data teams could risk wasting time managing reports no one uses and producing data that no one understands.”
Signs of data debt when considering investing in data literacy:
- Lack of definition and understanding of data terms, therefore they don’t speak the same language. Without data literacy, an organization will not succeed in becoming a data-driven organization.
- Putting data literacy as a low priority. Organization sees this as “another” training to put on the list and keeps it on the back burner.
- Data literacy is not seen as the number one skill set needed in the organization. However, anyone who works with data requires data skills.
- End users are not trained on self-serve features and tools.
- Focusing on a minority group of people rather than everyone in the organization or seeing it as a one-off exercise.
- Delays or failure to deliver digital transformation projects due to lack of data skills and data access issues.
66%
of organizations say a backlog of data debt is impacting new data management initiatives.
40%
of organizations say individuals within the business do not trust data insights.
30%
of organizations are unable to become data-driven.
Source: Experian, 2020
Info-Tech’s Approach
Data literacy is critical to success with digital transformation and AI analytics.
The Info-Tech difference:
- More than just technical training. Data literacy program isn’t just about data but rather encompasses aspects of business, IT, and data.
- More than a one-off exercise. To keep literacy skills alive, the program must be routine and sustainable, tailored to different needs across all levels of the organization.
- More than one delivery format. Different delivery methods need to be considered to suit various learning styles.
Data needs to be processed
Data – facts – are organized, processed, and given meaning to become insights.
Image source: Welocalize, 2020.
Data represents a discrete fact or event without relation to other things (e.g. it is raining). Data is unorganized and not useful on its own.
Information organizes and structures data so that it is meaningful and valuable for a specific purpose (i.e. it answers questions). Information is a refined form of data.
When information is combined with experience and intuition, it results in knowledge. It is our personal map/model of the world.
Knowledge set with context generates insight. We become knowledgeable as a result of reading, researching, and memorizing (i.e. accumulating information).
Wisdom means the ability to make sound judgments. Wisdom synthesizes knowledge and experiences into insights.
Investment in data literacy is a game changer.
Data literacy is the ability to collect, manage, evaluate, and apply data in a critical manner.
A data-driven culture is “an operating environment that seeks to leverage data whenever and wherever possible to enhance business efficiency and effectiveness” (Forbes).
Info-Tech Insight
Data-driven culture refers to a workplace where decisions are made based on data evidence, not on gut instinct.
Info-Tech’s methodology for building a data literacy program
Phase Steps |
1. Define Data Literacy Objectives1.1 Understand organization’s needs 1.2 Create vision and objective for data literacy program |
2. Assess Learning Style and Align to Program Design2.1 Create persona and identify audience 2.2 Assess learning style and align to program design 2.3 Determine the right delivery method |
3. Socialize Roadmap and Milestones3.1 Establish a roadmap 3.2 Set key performance metrics and milestones |
Phase Outcomes |
Identify key objectives to establish and grow the data literacy program by articulating the problem and solutions proposed. |
Assess each audience’s learning style and adapt the program to their unique needs. |
Show a roadmap with key performance indicators to track each milestone and tell a data story. |
Insight Summary
“In a world of more data, the companies with more data-literate people are the ones that are going to win.”
– Miro Kazakoff, senior lecturer, MIT Sloan, in MIT Sloan School of Management, 2021
Overarching insight
By thoughtfully designing a data literacy training program personalized to each audience's maturity level, learning style, and experience, organizations can develop and grow a data-driven culture that unlocks the data's full potential for competitive differentiation.
Module 1 insight
We can learn a lot from each other. Literacy works both ways – business data stewards learn to “speak data” while IT data custodians understand the business context and value. Everyone should strive to exchange knowledge.
Module 2 insight
Avoid traditional classroom teaching – create a data literacy program that is learner-centric to allow participants to learn and experiment with data.
Aligning program design to those learning styles will make participants more likely to be receptive to learning a new skill.
Module 3 insight
A data literacy program isn’t just about data but rather encompasses aspects of business, IT, and data. With executive support and partnership with business, running a data literacy program means that it won’t end up being just another technical training. The program needs to address why, what, how questions.
Tactical insight
A lot of programs don’t include the fundamentals. To get data concepts to stick, focus on socializing the data/information/knowledge/wisdom foundation.
Tactical insight
Many programs speak in abstract terms. We present case studies and tangible use cases to personalize training to the audience’s world and showcase opportunities enabled through data.
Key performance indicators (KPIs) for your data literacy program
How do you know if your data literacy program is successful? Here are some useful KPIs:
Program Adoption Metrics
- Percentage of employees attending data literacy training
- Percentage of participants who report gains in data management knowledge after training sessions
- Maturity assessment result
- Survey and diagnostic feedback before and after training
- Trend analysis of overall data literacy program
Operational Metrics
- Number of requests for analytics/reporting services
- Number of reports created by users
- Speed and quality of business decisions
- User satisfaction with reports and analytics services
- Improved business performance (customer satisfaction)
- Improved valuation of organization data
A data-driven culture builds tools and skills, builds users’ trust in the quality of data across sources, and raises the skills and understanding among the frontlines by encouraging everyone to leverage data for critical thinking and innovation.
Info-Tech offers various levels of support to best suit your needs
DIY Toolkit
"Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful."
Guided Implementation
"Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track."
Workshop
"We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place."
Consulting
"Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of the project."
Diagnostics and consistent frameworks are used throughout all four options.
Workshop Overview
Contact your account representative for more information.
workshops@infotech.com 1-888-670-8889
Session 1 | Session 2 | Session 3 | Session 4 | |
Activities | Define Data Literacy Objectives1.1 Review Data Culture Diagnostic results 1.2 Identify business context: business goals, initiatives 1.3 Create vision and objective for data literacy program | Assess Learning Style and Align to Program Design2.1 Identify audience 2.2 Assess learning style and align to program design 2.3 Determine the right delivery method | Build a Data Literacy Roadmap and Milestones3.1 Identify program initiatives and topics 3.2 Determine delivery methods 3.3 Build the data literacy roadmap | Operational Strategy to implement Data Literacy4.1 Identify key performance metrics 4.2 Identify owners and document RACI matrix 4.3 Discuss next steps and wrap up. |
Deliverables |
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