How to approach Data Literacy

By modeling data literacy behavior, running pilot programs, scaling with effective communication, and tailoring programs for different departments, organizations can foster a data-driven culture and empower employees to make informed decisions, contributing to overall success and competitiveness.

For us at AINSYS, data literacy holds significant personal importance, as it should for any IT company. IT specialists play a crucial role in transforming raw data into valuable insights. By promoting data literacy, they help foster a data-driven culture, empower employees to make informed decisions, and contribute to the overall success and competitiveness of the organization. We believe it’s vital for them to view it from an individual perspective, taking into account its relevance in both work and life. The definition we use encompasses the ability to read, write, and communicate with data in context, which means it’s not a one-size-fits-all proposition. To truly understand data literacy, we need to consider mindset, language, and skills, as well as people’s attitudes and beliefs.

What is Data Literacy?

The concept of data literacy in context resonates with us because it highlights the need for personalization in the data literacy journey. A crucial aspect of this journey is securing executive buy-in. For example, our CEO recognizes the importance of data literacy for our organization, but other specialists may encounter resistance when trying to secure executive support for data upskilling initiatives. To tackle this challenge, we must effectively communicate the significance of data literacy and data upskilling.

TIP: AINSYS specialists use a triangle mnemonic called the VIA model to explain any use case of data, which comprises three sets of terms: business value, information, and analysis. Experts in data governance, stewardship, and engineering excel in the “I” portion, while quants, developers, AI modelers, business intelligence experts, and analytics center of excellence professionals specialize in the “A.” Business stakeholders, process management, business analysts, and leaders, on the other hand, know the “V” or business value aspect best.

Securing Executive Buy-In

A key question today is how to engage executives or senior leaders in supporting data literacy initiatives. To address this, you must:

1. Identify potential sponsors for the data literacy program, typically from the data office.
2. Establish partnerships with learning or talent teams to secure sponsorship and alignment.
3. Capture the attention of other senior leaders by highlighting the relevance of data literacy to their organization’s strategic objectives.
4. Connect data literacy to aspects such as sales, efficiency, quality, or customer experience to demonstrate its importance.
5. Provide examples of how data literacy affects specific areas, like data quality in inventory control or customer service experiences.
6. Focus on what senior leaders care about and demonstrate how data literacy relates to their strategic objectives.
7. Emphasize the return on investment (ROI) from data literacy development and the risk of ignoring this need within the workforce.
8. Encourage open dialogue and discussions about data literacy with senior leaders to foster a culture of understanding and support.
9. Continuously update senior leaders on the progress and success of data literacy initiatives to maintain their engagement and buy-in.

Modeling Data Literacy Behavior

Leaders play a crucial role in teaching and modeling data literacy within their organizations. While endorsing data literacy initiatives and allocating resources is important, leaders should also model strong data literacy themselves. This can involve using live dashboards or visualizations in meetings instead of relying solely on PowerPoint presentations, as well as openly admitting when they don’t know something or asking for clarification on terms.

When leaders demonstrate strong data literacy, it sets a powerful example for their teams and encourages a culture of curiosity and learning. By openly discussing terms like AI ethics, for instance, leaders can foster a deeper understanding of these concepts within their organization. Ultimately, when leaders actively support and model data literacy, they contribute to the success of their organization’s data upskilling initiatives.

Pilot Programs and Scaling Data Literacy

Approaching data like a scientist and encouraging leaders to explain their thought processes can be powerful in a data-driven organization. When discussing the next steps after securing executive buy-in, pilot programs are a common way to introduce data literacy initiatives within a smaller population.

An effective pilot program should start with a receptive audience and focus on areas where there’s interest and engagement. It’s important to choose a topic that’s relatable and can demonstrate clear before-and-after results. Identifying the right target population for the pilot program involves looking for welcoming parties with certain characteristics, such as enthusiasm, curiosity, and openness to learning new skills. The company’s leaders can help foster a successful pilot program and contribute to a strong data-driven culture within the organization.

It’s crucial for leaders to ensure that learning objectives are integrated with organizational goals. One way to achieve this is by utilizing the “five why’s” technique, which encourages digging deeper into the reasons behind the desired outcomes. This helps leaders focus on transformational outcomes rather than skill-based outcomes, ultimately providing more value for the organization.

Measuring the impact of a data literacy program can be challenging, but one metric that has gained traction is the net promoter score, which evaluates participants’ willingness to advocate for the program. Other metrics can be grouped into three categories: engagement, development, and enablement. Each category has specific metrics that can provide insights into the success of the data literacy program.

Effective Communication for Scaling

When it comes to scaling a data upskilling program, effective communication is vital. To successfully scale, organizations should focus on creating clear and multifaceted communication strategies that engage employees and promote the benefits of the program. This includes sharing success stories from pilot programs, providing regular updates on progress, and making resources easily accessible to all employees. By prioritizing communication, organizations can ensure that their data literacy initiatives are embraced and supported throughout the company.

The communication aspect of a data literacy program is indeed crucial, particularly when moving into phase three, where the goal is to scale the program after a successful pilot and achieve transformational outcomes. Effective communication models for scaling a data upskilling program can be divided into grassroots and top-down approaches:

• Grassroots communication: Engage the groundswell movement and let it take on a life of its own. Encourage employees to become data literacy ambassadors, complete digital badges, and volunteer to run workshops or record subject matter expert videos. Successful grassroots communication is evident when program ideas, techniques, and coaching tips spread throughout the organization, even to those who haven’t been directly trained.
• Top-down communication: Ensure leaders are intentionally embedding data literacy into their ways of working and organizational culture. This can include incorporating data literacy discussions into onboarding processes or all-hands meetings.

Thinking of communication as marketing can also be beneficial. Innovative communication methods used by organizations include:

• Program branding: Create a distinct brand identity, logo, and tagline for the data literacy program to avoid it being perceived as just another corporate change initiative.
• Infusing data literacy into the organization’s workflow: Embed data literacy concepts into the daily business activities and make them relevant when needed, rather than treating them as separate meetings or agenda items.

By combining grassroots and top-down communication methods with marketing-like strategies, organizations can effectively scale their data literacy programs and engage a wider audience within the organization.

Tailoring Data Literacy Programs for Different Departments

Let’s move beyond marketing and discuss the administration of the learning program. Scaling a program beyond a pilot project while maintaining personalization for a wider organization and various departments can be challenging. To address the first challenge, effective ways to tailor data literacy to the specific needs of different departments and units include:

• Establishing a clear foundation: Develop a consistent understanding of data literacy essentials and provide relevant courses and learning paths that span functions and divisions.
• Layering contextualized learning: Build upon the foundational understanding of data literacy by introducing department-specific use cases, bias and ethics discussions, and data storytelling that aligns with the unique business problems and opportunities of each division or domain.

For personalizing learning beyond the foundational level, consider adopting different learning modalities, such as an ambassador program, online learning, instructor-led learning, and workshops. The community aspect, involving local coaches and data ambassadors, can help with personalization:

• Maximizing existing communities: Utilize existing communities, such as analytics centers of excellence or user groups, and equip them with data literacy toolkits, mnemonics, and consistent essentials to operate effectively.
• Connecting with change agents: Collaborate with talent development, future of work, people officers, and learning and development teams to integrate data literacy into broader organizational agendas.

The Future of Data Literacy

Data literacy’s power lies in creating a common language within the organization. We’ve talked about getting executive buy-in, setting up a pilot program, and scaling the program. But what’s next for data literacy, you might ask? Data literacy is becoming a societal thing, not just a workforce development program, with recent legislation such as the Data Science and Literacy Act in the US. As a result, there needs to be consistency and standards across this landscape. We see education, consistency across the domain, and professional development certifications as a future trend for data literacy, similar to what Six Sigma approach does. Joining forces is our final call to action for leaders, enthusiasts, and data scientists. If some of you are already doing something in this area, offer a helping hand and get involved.

While this article focuses on the human side, we should also keep an eye on automation and technology, as there is a lot to watch out for in this space. AINSYS offers a comprehensive tool for achieving complete data literacy within your company via:

• Intuitive no-code GUI for business users and technical teams;
• AI-assisted requirement management for rapid implementation;
• Pre-built industry-specific templates for seamless integration;
• Customizable, modular architecture for tailored solutions;
• On-premise or cloud-based deployment options for flexibility and security.

AINSYS offers these and other tools and syncs data between every tool and platform your IT team employs, helping you achieve data literacy within your organization. By implementing AINSYS tools, any business can organize proper data literacy to make the right decisions for your organization and keep up with the ever-changing technology landscape.

‍