Enterprises and growing organizations are increasingly using HR data to optimize their workforce. But within this realm, learning and development (L&D) teams face a unique challenge: translating raw HR data, specifically learning data, into actionable insights and using it to tell a story. Here's where data literacy and data storytelling come in.
Data literacy and data storytelling in L&D aren’t about presenting elaborate charts or graphs. It's about understanding and building a narrative that gives numbers meaning – showing the impact of learning programs on your organization's human capital. This skill allows L&D teams to measure the impact of programs and continuously refine training to ensure a more skilled and engaged workforce.
Above all, it translates to business value. According to research from Gartner, enterprises with higher corporate data literacy scores can have between $320 and $534 million in higher enterprise value.
What is data literacy in L&D?
Data literacy, the ability to access, analyze, and interpret data, is a necessary skill for L&D teams. Moving beyond basic metrics like course completion rates, data literacy for L&D professionals provides a nuanced understanding of how learning translates to tangible business outcomes.
And it’s’ more important today than ever. According to Datacamp, 89% of UK leaders and 78% of US leaders believe that data literacy is important for their teams' daily tasks.
For example, HR data like employee performance reviews or skills gap analyses can pinpoint specific training needs. Data literacy allows you to turn this information into actionable insights for targeted learning programs that fill skill gaps. This ability to transform data into clear next steps contributes to a knowledgeable workforce.
Understanding data storytelling in L&D and its benefits
Data literacy and data storytelling are closely linked skills, but they serve different purposes. Think of data literacy as the groundwork. As noted earlier, it's the ability to access, understand, analyze, and interpret data. Data storytelling takes the insights gained from data literacy and uses them to craft a compelling narrative.
Some of the advantages of using learning data to drive your decisions include:
- Demonstrate ROI: Stakeholders often question the value of L&D programs. Data storytelling allows you to quantify the impact of training on key metrics, like increased productivity, improved customer satisfaction, or reduced error rates. By painting a clear picture of how learning drives financial benefits, you can secure continued support for your initiatives.
- Identify learning gaps: Data analysis can reveal areas where learners struggle or where knowledge retention is low. By translating this data into a compelling story, you can pinpoint specific weaknesses in your training programs and prioritize areas for improvement.
- Personalized learning experiences: HR data analytics provides insights into individual learning styles and preferences. Data storytelling can help you use this information to inform the development of individual learning experiences, catering to diverse learners and maximizing engagement.
- Drive continuous improvement: The learning environment isn't static. Data storytelling allows you to track learner progress over time, identify trends, and adapt your programs accordingly. By weaving a data driven HR narrative, you can champion a culture of continuous improvement within your L&D function.
Read the blog: Harness LMS Analytics to Improve Data-Driven Decision-Making
Measuring training impact with HR data
So, how do we measure the impact of training with data? This is where L&D reporting and analytics come into play. HR data analytics allows L&D teams to track and measure key metrics beyond just participation.
Based on the 2023 LinkedIn Learning Report, here are some of the top ways L&D teams measure success:
- Employee satisfaction
- Number of employees taking training or courses
- Employee performance on post-learning quizzes
- Number of courses or training each employee completes
- Improved performance reviews
- Team or org business metrics
- Improved employee productivity
- Improved employee retention
- Number of hours spent learning
- Progress toward closing skill gaps
- Number of new skills learned
We’ll use these focus areas to explain how to measure and analyze L&D data.
Steps to analyze employee learning data
Okay, so we understand the data we’re after. But how do we collect it and use it to tell a story? It’s important to recognize that data analysis is a multi-step process. Here’s how you can measure and analyze factors related to your employee learning:
1. Identifying the right data: Data literacy helps you determine which data points are relevant to each factor. For example, to measure employee satisfaction, you might look at survey responses, not just course completion rates.
2. Data quality and cleaning: An estimated 47% of new data collected by companies have one or more critical errors. Data literacy equips you to assess data quality and correct inconsistent formats, missing entries, or inaccurate metrics. By taking these actions, you’ll end up with consistent data for reliable analysis.
For instance, employee productivity improvements can be measured in many formats such as:
- Quantity of work: This could be units produced, tasks completed, sales closed, etc., depending on the role.
- Quality of work: Track error rates, customer satisfaction scores, or rework needed.
- Time management: Monitor completion times for tasks or projects.
- Goal achievement: See if employees are consistently meeting or exceeding pre-set goals.
When using L&D reporting and analytics, you must choose focus areas and make sure they’re recorded consistently for proper analysis.
3. Choosing the right metrics: Not all metrics are created equal. Data literacy helps you choose metrics that truly reflect the desired outcome. For example, the number of hours spent learning might not equate to improved performance. It’s crucial to look at related metrics like improvements in productivity and performance reviews for a more in-depth analysis of your training impact.
4. Data analysis and interpretation: Data literacy allows you to analyze data using appropriate tools and techniques. You can identify trends, correlations, and cause-and-effect relationships between factors like training completion and performance improvement.
5. Visualization and communication: Data storytelling is key. Data literacy enables you to present findings in clear and compelling visualizations like charts and graphs. This allows stakeholders to easily understand the impact of learning initiatives.
The future of data storytelling in L&D
While data storytelling has become a powerful tool for L&D professionals, the future promises even more exciting possibilities:
AI-powered data analysis
Artificial intelligence (AI) is poised to reinvent data analysis in L&D. AI can automate repetitive tasks like data cleaning and trend identification, freeing up L&D professionals to focus on interpreting insights and crafting narratives.
Advanced data visualization tools
Data visualization tools are constantly evolving, making it easier than ever to present complex data in an engaging and digestible way. Interactive dashboards, for example, will allow stakeholders to explore data from multiple angles and gain deeper insights into the impact of learning initiatives. Additionally, AI-powered tools can help create customized visualizations tailored to specific audiences, further enhancing communication and buy-in.
Microlearning and personalized learning experiences
The future of learning is likely to be personalized and bite-sized. According to the Association for Talent Development, “When this is repeated over time, microlearning can increase knowledge retention and proficiency in ways that “one and done” training methods don’t.” Data storytelling can play a crucial role in informing the development of microlearning modules and personalized learning pathways. Learning data can reveal individual learning styles, strengths, and weaknesses. Data also informs the creation of targeted learning experiences that cater to diverse learners and maximize engagement.
Focus on predictive analytics
HR University gives a succinct explanation of how predictive analytics will play into the future of employee data. “Predictive analytics are used to predict what will happen in the future. Suppose we wanted to indicate whether an employee was likely to leave their job within 12 months. In that case, we could use predictive statistics to determine whether they had previously left their position within the last 12 months.”
Similarly, as data analysis becomes more sophisticated, L&D teams will be able to use predictive analytics to anticipate future learning needs. Using data to identify potential skill gaps within the workforce before they arise is becoming the norm and allowing for proactive development of targeted training programs. This forward-thinking approach can ensure a more prepared and adaptable workforce.
Using your LMS to support data storytelling in L&D
Data literacy empowers L&D professionals to become strategic partners in their organizations. With the ability to measure the impact of training programs, L&D can continually refine and improve learning initiatives, ensuring they stay aligned with evolving business needs.
Data storytelling takes this a step further, turning data into a powerful communication tool. By weaving data into compelling narratives, L&D professionals gain the necessary buy-in to support their programs.
Ready to unlock the power of data storytelling in your L&D practice? A learning management system (LMS) like Absorb LMS is a powerful tool for data driven HR teams by providing valuable insights into employee learning and development. Learn more by scheduling a demo today.
