Empowering Learning Leaders: Using Training Analytics for L&D Success

This blog post highlights some of the most popular questions we see learning leaders asking. We invite you to consider which insights you’d love to unlock using the data in your ecosystem.

In this blog series, we'll explore the concept of learning analytics and its role in future-proofing your learning programs while addressing business pain points we commonly hear from the C-Suite—including learning leaders, compliance and legal, sales, and human resources.

We'll delve into the importance of using data, L&D and HR strategies, and practical tips for implementing learning analytics effectively. We’ll provide links to related resources, and we’re here to chat if you’d like to find out more on how to get started. Let’s begin by discussing how L&D data can help learning leaders.

How can learning leaders and practitioners benefit from L&D data?

Learner leaders and practitioners can use L&D data to:

• Inform learning strategies. By analyzing L&D data, you can identify what's working and what's not and make necessary adjustments to your learning initiatives.
• Personalize the learning experience. By understanding employees' learning preferences and needs, you can create personalized learning paths catering to their jobs and needed skills.
• Measure the impact of your learning initiatives. By tracking key metrics like course completion rates, assessment scores, and on-the-job performance, you can demonstrate your learning programs’ impact and help secure continued investment in learning and development.
• Get a real-time view of organizational skills. Understand where your organization currently sits in terms of existing and needed skill sets at any given time.

Gain insights into the learner experience

Providing a positive learning experience is crucial for the success of your learning and development initiatives. But what exactly is "learner experience," and why is it important?

Learner experience refers to learners' overall experience during their learning journey. This includes factors such as the quality of the learning content, the ease of access to learning resources, and the level of support provided during the learning process.

A positive learner experience enhances learning outcomes and boosts learner engagement and motivation. After all, when learners enjoy their learning experience, they're more likely to engage with the learning content and apply what they've learned on the job. And this leads to improved performance and productivity.

Moreover, by collecting learner experience data, you gain valuable insights into how learners interact with training resources and content. You can identify any challenges they face, gaps in L&D content, and areas where you can improve the overall learner experience. You can combine a data-led approach to understanding how your content is utilized with traditional learner feedback (e.g., happy sheets) to paint a far more compelling case of learner satisfaction.

Dashboards that are simple to use are essential for analyzing learner data because the people who will use them are typically line managers—who may lack experience working with data.

For example, the following dashboard shows how learner data can inform managers about where to focus, how their team is performing, who is excelling, and who needs help. They can also spot trends or see who is licensed to do specific jobs.

Real-world insights for informed decision-making

At Applied Industrial Technologies, coaches enrich their coaching sessions with managers using L&D reports. These reports outline competency strengths and weaknesses, drawing insights from learning assessment data and business performance metrics.

The comprehensive L&D reports enable coaches to make informed recommendations for addressing weaknesses and driving improvement. By implementing learner analytics, coaches gain valuable insights into the precise training needs of managers, allowing for more tailored and practical training and coaching programs that directly cater to their development needs.

Another real-world example is a pharmaceutical company's sales team, which used Watershed to analyze salespeople's quiz game scores following an in-person training event. This analysis revealed that many salespeople had missed the main point of the training, prompting the team to provide additional targeted training to bridge the knowledge gap effectively.

Uncover organizational learning needs with hierarchy data

Hierarchy data refers to the hierarchical structure of an organization—including the relationships between different departments, teams, and individuals.

You can use hierarchy data to better understand your organization’s learning needs. For example, the sales team’s learning needs may differ vastly from the IT team’s. Understanding these differences allows you to create tailored learning programs catering to each team’s needs.

Hierarchy data also helps track the progress of your learning initiatives at different levels of the organization. You can see how each team performs throughout their training, identify any lagging teams, and implement necessary interventions.

And finally, you can use hierarchy data to align learning initiatives with organizational goals. By understanding each team’s strategic objectives, you can design learning programs that support these objectives and drive business growth.

How is hierarchy data used in practice by learning leaders?

At Watershed, we see organizations use hierarchy data in very practical and powerful ways. Global organizations often roll out training initiatives in response to region-specific issues, using bespoke reporting to assess impact.

When this data shows either proof of training success, or indeed highlights source causes of the original issues (i.e., automotive dealerships noting repeat battery replacements in EVs), it becomes easier for L&D to capture C-Suite attention.

Making the case that a regional issue should be considered at an organizational level is much more compelling when the problem has been “trialed” at a regional level.

Save time and keep stakeholders in the loop with automated L&D reports

In the world of learning and development, data should be king. But with so much information to sift through, how do you make sense of it all? This is where automated reports come into play. Automated reports help you analyze your L&D data and derive meaningful insights.

Automated reports provide a wealth of information—from detailed performance reports to anomaly or trend analysis reports. They show how learners progress in their training programs, which learning modules are the most effective, and how learning initiatives contribute to business results.

Automated reports also mean you can track L&D KPIs in real-time. Monitor your training programs' performance and make necessary adjustments on the fly. They also save you a significant amount of time and effort by eliminating the need for manual data analysis and report generation.

Automating your reports solves two more common learning leader pain points:

1. The first is ensuring the correct permissions are set to ensure the reports only show the personal data relevant for the recipients—especially important when global L&D teams have to navigate different regional data protection laws. Regional managers may have access to relevant aggregated views, whereas line managers will need individual track records.
2. The second pain point is removing the restriction of L&D relying on other departments (IT) to produce reports on an ad-hoc basis. Powering your learning function with the data to analyze nurtures a curious mindset, one of the core essentials when it comes to building L&D’s analytic capabilities.

Optimize L&D investments with learning content analytics

Effective learning leaders constantly examine utilization and where they can save money or make money, save time or make time, and make the lives of everyone around them better to truly develop people.

So, the most logical question to start with here is:

Are my platforms, courses, and user licenses being utilized?

From there:

If I have these licenses associated with courses or libraries, how can I go back and renegotiate those license terms?

The whole point of content analytics is to improve the content, plain and simple. Here's how:

• Spotting what needs fixing: Training content analytics gives you the lowdown on what's working and what's not—so you can make the necessary content improvements.
• Ditching the dead weight: It also helps you figure out which content is taking up space so you can remove unnecessary, dated, or other irrelevant resources.
• Creating top-notch content: By seeing and understanding what great L&D content looks like, instructional designers and content curators up their game and produce better training material.
• Filling in the blanks: Content analytics show where your content might be lacking, ensuring you cover all the bases for your learners.

For example, Alfonso Riley, L&D Strategist at Caterpillar, used content analytics to pinpoint the most popular training videos on CAT’s Kaltura video platform. After analyzing data from multiple months, he found that around five or six videos garnered significantly more views than the others in the platform's extensive video library.

Taking a closer look at these videos, he delved into why they were popular. As a result, he applied these insights to shape his approach to launching and promoting new video content.

In other words, having all your data in a standard normalized format makes the lift easier.

The burning questions L&D data can answer for learning leaders

In summary, learning in a global organization leaves traces across a variety of platforms and systems. Once you can aggregate, cleanse and align this data (with the option of throwing HRIS and business performance data, aka KPIs) you can look to answer your burning L&D questions in meaningful ways that engage the wider business.

If you look at the summary of the questions we’ve covered here, you start to sense the breadth of powerful insights you can achieve through applying learning analytics to your training programs:

• Can we improve the learner experience?
• Are we meeting demand - what are learners searching for?
• Are we focusing our coaching in the right areas?
• Is our learning content actually covering the core topics?
• Can I scale my insights using hierarchy data (by job role, by region, by department)?
• Can I optimize our system to do the fancy stuff? (ecosystem-wide credentialing, automated workflows and prompts)
• Do we empower line managers / L&D with localized insights and automated reports?
• Is licensed content being utilized?
• Are the content and systems we’re paying for actually being used?
• Is ILT outperforming my online offerings?
• Is training impacting business KPIs?
• Can we prove the impact of specific initiatives?
• How do I overcome siloed reporting from our global ecosystem?

Up Next: How can Compliance and Legal benefit from L&D data?

So, which areas of the business really benefit from learning analytics? Considering all that stakeholder pressure, it's across the board. In other words, learning data and analytics help drive results everywhere in the business.

Some business areas are finding rewards from simply having that alignment with L&D. You can use L&D data to see how employees perform in their training programs, their engagement levels, learning content effectiveness, and more. Essentially, it provides you with a wealth of insights into your learning initiatives, helping you identify what's working and what needs improvement.

Join us for our next blog post as we discuss how Compliance and Legal teams can benefit from using L&D data and learning analytics.