Automation and analytics: The future of learning

Libby Cross, Senior Marketing Executive

The adoption of data, technology, and digital platforms for organizational learning has increased dramatically in recent years. Automation and analytics are key drivers behind the future of learning, aiding businesses in their ability to leverage data for learning solutions.

Organizations are now turning to digital innovations such as AI-infused analytics platforms to enhance and grow the knowledge of their teams and talent. A recent study by Learning Pool revealed 76% of mature metrics practices are enabled by technology that integrates data from multiple sources.

In this article, we’ll dig into the ways organizations’ educational needs have evolved, how AI helps learning and development professionals get more out of their data, and how automation will advance and deepen organizational evolution.

Navigating a changing training and education landscape with AI

Understanding data on learning habits and preferences is key to optimizing learning and development (L&D) outcomes in the evolving workplace. Data from social courses are especially rich and useful for an organization — not just scores and completion percentages, but real learning-conversation data. Organizations are capturing more data on learning actions using standard formats like Experience API (xAPI) and then storing the data in a Learning Record Store (LRS) for subsequent analysis.

Learning Pool’s white paper Measuring the Modern Learner Experience explains how an LRS specifically stores xAPI statements, which at their most basic level combine an actor, a verb, and an object. These seemingly unrelated learning elements are then unified by a standard that other systems understand.

An AI-infused analytics platform like Sisense helps businesses understand the value that learning/training is providing in the workplace. Analytics models, supercharged with AI, are being leveraged to recommend content to users based on who they are and where they work. The captured data determines how engaged a learner is in a specific topic or how well they understand that topic.

A recent Learning Pool report highlights four ways organizations can use learning data and make it integral for their business analytics:

Understand that “things the business cares about” is a moving target: What a business needs to know about in any given year, quarter, or month changes rapidly, with new priorities being shaped by events often out of its control.
Don’t focus on information about the past: Historical data is only compelling to the extent that it can help the business grapple with the critical issues it’s facing ‘in the moment’ and going forward.
Show users the bottom line on learning outcomes: If you only measure outcomes, you might know that learning succeeded but not why it succeeded (or didn’t). While that’s really important info for you, the learning professional, the business may only be interested in final outcomes (the ROI or a measurable change in performance or behavior, etc.).
Don’t rely too heavily on dashboard data: Learning data is most useful when it’s analyzed, embraced, and acted upon (ideally by being infused into user workflows – when and where it’s most relevant).

Analytics must be super-simple and infused everywhere

When it comes to infusing analytics in learning platforms, simplicity is key. Collating and analyzing complex data is challenging for non-technical users. Some barriers they encounter include inefficiency (analytics platform not delivering insights in a timely fashion), inertia (not wanting to leave their usual workflow tools), training mindset (tools being difficult to use), and manager engagement (not having a management-led analytics culture).

Simply put, organizations shouldn’t need to have a team of data specialists simply to make good use of learning data. They have the skills and knowledge to use the insights from their data — they just need to have the data available in a more accessible, simpler-to-use, and easier-to-understand way.

This is where leveraging tools like Sisense helps remove any barriers to understanding data.

Learning Pool recently announced that it is embedding Sisense to combine the power of its leading AI-driven analytics platform with Stream Data Cloud. With more than a billion data points under management, Learning Pool offers Learning Locker to customers to help them manage their learning records.

This partnership has culminated in a valuable new addition to the Learning Pool suite, ‘Insights’, which serves up granular learning data combined with Sisense’s AI capabilities to bring personalized and automatic intelligence to every user.

Insights create AI-powered dashboards built specifically for learning data analysis. By presenting accessible, adaptable, and actionable visualizations that are grouped together in a meaningful way, Insights provides clients with guidance about the past, current, and potential future performance of their learning ecosystem and learners.

A recent Learning Pool study asked learning professionals what aspects of analytics mattered most to them. The respondents noted two key requirements. First, they need to understand the learner and learning performance. They want their analytics to show them how businesses could optimize learning paths to ensure courses and learning campaigns are of the highest possible quality.

Second, they need to uncover actionable insights. Getting insights out of their data is only the beginning — it isn’t actionable. Respondents stated that they want to bring news about learning data that was meaningful, delivered business benefits, and was actionable.

Another way to empower learners that Learning Pool has focused on recently is automation.

Unlocking the power of learning through automation

Automation can accelerate learning practice.

When properly implemented, automation isn’t about replacing the trainer or learning professional. Rather it’s about leveraging efficiencies in workflows so that these humans can put their expertise and time to best use. Automating tasks allows them to focus on more complex interventions and apply their knowledge and skills at scale, creating learning and communication pathways that optimize learning.

Similar to automation, when analytics are properly utilized, they can strengthen learning and development within an organization.

Villeroy & Boch uses xAPI to enhance learning

Learning Pool has hundreds of use cases and ideas from learning professionals who have leveraged their learning data better for both analysis and automation.

Villeroy & Boch (V&B) is a ceramics provider, creating both premium tableware and designer bathrooms. V&B wanted to create brand ambassadors: customers who proactively recommend the V&B brand and stores.

A blended learning approach — combining online social learning delivered via Stream LXP, face-to-face workshops, webinars, and monthly newsletters — was conceived to deliver the brand ambassador program.

Using these tools, V&B was able to demonstrate a €2.5 million return on its training investment, using xAPI.

Building the future of learning analytics

To keep abreast of change it’s important to build data literacy and really understand how to educate within the new normal. Those who fail to keep up run a real risk of losing value in the workplace.

Fortunately, new and innovative ways of leveraging the power of learning analytics give users of all skill levels the ability to decipher data. This opens up new doors for developing unique learning experiences and expands career opportunities for L&D specialists.

Meanwhile, aspiring managers who embrace learning analytics will become more relevant, more valuable, and regarded as integral team members, a win for both the employee and the organization.

Mastery of data is helping humans overcome their challenges in every field; education and training is no different. Whatever your role and whatever your organization’s educational focus, analytics will be a vital part of helping you and your team excel in an evolving world.

This blog was originally published on the Sisense blog.