Technology has fundamentally changed the way we deal with data in the learning and development (L&D) profession. We have access to an amazing array of tools that allow us to gain more insights about how we learn, what content is most useful, where we need to allocate more resources and how learning can directly impact on-the-job performance. However, to take advantage of these tools and make use of the analytics, we need a data-literate workforce.
Data literacy means more than the ability to analyze data. We need to be able to discover, identify, collect, process, interpret and communicate data — essentially covering the entire data journey from creation to dissemination. Data literacy is often cited as a critical skill for the 21st century, but according to a study by Accenture, “Just 21 percent of the global workforce are fully confident in their data literacy skills.”
Data literacy is a skill that we needed yesterday. I propose the following four steps in building data literacy in your organization:
Define Data Literacy
Data literacy encompasses a wide range of skills, including data ethics, policy, analysis, storytelling and visualization. Take time to explore where the organization is on the digital transformation journey, what its business functions and industry standards are and which data literacy skills are best suited (and to what levels based on job roles) to support the organization and respective departments.
Get Executive Buy-in
Decision-makers have the power to influence the culture and approve finances and resources, as well as embody behaviors by being data literate and valuing data-driven insights. To achieve executive buy-in, we must align the data literacy initiative to the shared goals and objectives of the organization and demonstrate the power of data with a small pilot program that is grounded on actual use cases.
Conduct a Readiness Assessment and Develop a Competency Framework
As not all staff have the same level of data literacy, it is useful to conduct a readiness assessment to gauge people’s abilities, capacities, attitudes and experiences to establish a baseline. The readiness assessment will help identify, prioritize and measure the impact of your data literacy initiative. If you are unsure of how to go about creating a readiness assessment and what competency framework to use, I recommend this Statistics Canada study — it provides a comprehensive overview on data literacy competency frameworks, as well as the assessment tools used to measure them.
Scaffold and Customize the Learning
Once the skills gap is identified, we can create and scaffold customized learning paths that map to different department functions or job roles. An effective plan needs to be based on the balance between the learner’s professional goals and the employer’s needs. Therefore, we ought to take into consideration the learner’s context and connect the learning to their day-to-day tasks. A learning path should be more than a course selection guide; it should address specific learning objectives that align with each person’s or each department’s performance objectives. When possible, co-design the learning paths with your learners to help them take ownership of their learning and make assessment relevant to their work.
Developing organizational data literacy requires a good understanding of organizational context, thoughtful instructional design, regular assessment and a flexible and personalized approach. While achieving the desired level of data literacy takes time, it is a journey worth taking to harness the power of data to build a data-informed decision-making culture.