Where Learning Analytics Fit on the Digital Workplace Agenda
The No. 1 way learning and development professionals measure the impact of online learning is through qualitative feedback from employees, according to the LinkedIn 2020 Workplace Learning report.
About 43% of respondents chose that route, ahead of other measures such as number of online courses completed (38%), number of employees who consistently learn online (35%), employee satisfaction (34%) and qualitative feedback about behavioral change (31%).
At the same time, a little more than one in three say investments in learning analytics, like evaluation and dashboards, will be a top area of L&D technology spending, according to Chief Learning Officer magazine's 2020 "Learning State of the Industry" report.
So what’s the right approach for learning analytics that considers technology, organizational objectives and ultimately helps L&D professionals demonstrate value from the programs they measure?
Choose Strategy Over Novelty
Shelley Osborne, vice president of learning at Udemy, an online learning marketplace, said one of the pivotal first steps before investing in learning analytics has nothing to do with data. It’s about alignment.
“Every team, company and industry is flooded with data, but unless we can first get on the same page about what our company objectives and business strategy are, any other insights will be useless," Osborne said. "We need to think about it in the same way we think about other emerging technologies: It must be strategy over novelty. It’s critical to understand what we’re trying to accomplish for the business before we can glean any insights from our learning analytics.”
Understand how learning can impact the business then further analyze what learning levers to pull in order to impact change, she added. She cited examples like improved operational efficiencies, growth initiatives like increased revenue, employee engagement through wellness programs, or leadership development.
“From here, learning analytics can become the glue that bonds together tactical and strategic objectives and provides visibility into downstream outcomes,” Osborne said. “The true future state is when we can start using learning analytics and trends in data to start behaving predictively. Recognizing patterns of behaviors and their connection to learning initiatives could allow us to plan, design and implement learning more effectively.”
Related Article: Online Learning Market Soars as Pandemic Fuels Rapid Reskilling
Analyzing Usage and Efficiency
Greg Rosen, data analyst at BenchPrep, which offers an online learning management system (LMS), said he sees learning analytics in two main categories, and that is usually dependent on the stage of a company's learning program.
At first, he said, they look at usage. Are learners picking up the product and which features are they favoring once they do? Later, they want to know about efficacy. Are they absorbing the material? And, if so, why or why not?
“It's important for your LMS partner to provide personalized learning plans with an adaptive learning structure, one that focuses on improving your learners' experience and performance during the course,” Rosen said. “With rich analytics on learner progress and results, organizations can track learner engagement, identify skills gaps, analyze dropout points and ultimately improve both engagement and outcomes with gamification and new content to fill those gaps.”
Rosen said every learning organization should have people who can look at data, understand it and decide what to do about it, as well as access to clear, actionable data that ties their programs back to business goals.
How Learning Analytics Applies on Multiple Levels
Organizations are leveraging learning analytics in many ways, from micro-level applications that inform individual learning experience design to macro-level usages that permit trend assessments across entire catalog offerings and broad learner populations, according to Todd Moran, chief learning strategist at NovoEd, which offers a learning platform.
On the granular level, organizations use evaluation and usage data to pinpoint where learners may be disengaging within a course or program, Moran said, then modify its design with a collaborative discussion segment or a reflective practice element to ensure engagement. “This level of analytics is exceedingly helpful for instructional designers, facilitators and practitioners at large within an organization,” Moran said.
On the expansive level, organizations perform broad analysis of consumption and completion data sets across whole curricula and workforce populations to inform which learning and development offerings are landing and which employees are being best served within their companies. “This level of analytics is most beneficial for learning and development leaders and executives making decisions on content investments, delivery models and platform selection,” Moran said.
Related Article: 5 Ways to Improve Training Opportunities for Remote Teams
Tie Analytics to Engagement and Performance
Immersive learning experiences can be critical to driving employee engagement, Moran added. Analysis of evaluations, engagement levels and course completion rates are telling a story of exhaustion among employees, Moran added. Right now, employees’ primary means of knowledge acquisition and skill development usually comes from another video conference or virtual course.
“And, more often than not, organizations find it difficult to capture data that points to true business impacts of learning and development programs,” Moran said.
Having learning data at hand informs which deployment models are resonating with the workforce, what courses are trending positively and even where specific learning redesigns may need to occur.
However, Moran said, most learning analytics are isolated and they lack connection to and consideration of other critical company-wide systems like performance, sales and talent. “This analysis in isolation means that learning and development leaders are missing a prime opportunity to quantify the impact of their training efforts on key organizational goals like revenue growth, retention and internal mobility,” he said.
Granular, Holistic and Flexible Investments
According to Moran, the nature of these learning analytics investments should be granular, holistic and flexible:
- Granular: metrics must detail nuanced and specific data points rather than overall enrollments or course completions. The most valuable solutions look beyond these base-level measures to provide insights into social contribution counts and frequencies, peer-to-peer interactions and exit points.
- Holistic: dashboards and visualizations need to span the breadth of learning offerings across an organization (courses, programs and entire curricula) as well as the expanse of populations served, with the ability to slice across a variety of parameters, such as job role, function and geography.
- Flexible: data insights must be made not just with learning-centric events and activities from a closed system, but rather combined with inputs housed within other enterprise systems, like people, performance and talent platforms.
“CLOs who shape their learning analytics investments around a compilation of these three aspects in the coming year and beyond will ensure their ability to assess and detail their overall efforts,” Moran said.
“This is especially critical as learning and development leaders receive increasing downward pressures from CEOs to directly impact business outcomes most important to their organization, like talent, revenue, growth, profitability and operational excellence.”
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