Training and learning programs are major tools for organizations to use - but only if they are designed, built and managed in a way that actually increases employee productivity. E-learning platforms can be used to increase employee engagement and retention and help improve the productivity and performance of both individuals and the company as a whole. Relying on traditional approaches, though, such as self-assessments or PowerPoint presentations is not sufficient in today's ever-evolving world of technological advancements and artificial intelligence. Those who rely on outdated, run-of-the-mill strategies and programs are putting themselves at a severe disadvantage.
Research has found that today's workers want training, learning and growth opportunities from employers. But they also want them a certain way. The vast amounts of data that companies now have available to them present an advantageous opportunity to enhance and personalize e-learning. And it is the collection, analysis, interpretation and presentation of this information that can make the difference between a mediocre training program and a successful one.
Strategic solutions for digital learning development
The benefits of corporate learning solutions can be realized only when content creators are able to adapt and leverage analytics to obtain better insight and guidance on how to improve the user experience. This information can help managers understand what is and isn't necessary to use in training materials, ultimately making the education delivery more efficient. As Jim Walker pointed out in a piece for Training Industry, using predictive analytics allows business leaders to customize content in accordance with the preferred learning style of individual users - something that the advanced algorithms of e-learning tools now allow. By improving the effectiveness of these programs through data analysis, businesses are able to increase participation, engagement and, therefore, retention rates - resulting in a better return on investment for the organization.
"Predictive analytics, along with machine learning, can be used to predict key future events for employees, including whether or not an employee will pass a course, and whether or not their engagement is about to drop," the source explained. "The data collected can then identify key behavioral traits and patterns that correlate to success in a course. Armed with these insights, new strategies can be developed to improve future performance."
A growing number of organizations are beginning to leverage artificial intelligence to gain a competitive advantage. According to Forbes Contributor Gill Press, within the next two years, AI technologies - which includes machine and deep learning, predictive analytics, voice recognition and more - will be used by over 60 percent of enterprises, almost 40 percent of which already do. Furthermore, a study conducted by the National Business Research Institute found that the amount of business executives who are efficient in big data and also using AI technologies jumped from 59 percent to 95 percent in the past year alone. This significant spike in adoption can be attributed to the rapid development and sophistication of big data for deep learning initiatives.
Utilizing the right analytics
The problem, however, is not so much that company leaders do not understand the power of predictive analytics and big data in the learning environment but, rather, how to aggregate, analyze and use the appropriate sets of information. According to Forbes, nearly 60 percent of survey participants agreed that limited access to data scientists and skills has kept them from adequately realizing the benefits of big data, which is why many are turning to AI tools.
"Providing training materials doesn't automatically mean the user is learning."
In an article for PC Magazine, Rob Marvin further elaborated on the usefulness of using predictive analytics to gain better business intelligence and insights - ones that can be used to improve corporate learning and training programs. Neural networking, deep learning and other machine learning advancements take unstructured sets of data and process them with more speed and accuracy than data scientists could - which, he added, is the type of approach major tech companies such as IBM and Google have taken with their analytics and open-source frameworks.
"The big change feeding into the predictive analytics boom is not just the advancement of ML and AI, but that it's not just data scientists using these techniques anymore," Marvin explained. "BI and data visualization tools, along with open-source organizations like the Apache Software Foundation, are making Big Data analysis tools more accessible, more efficient and easier to use than ever before."
Choosing a third-party supplier
Still, many organizations are limited in the time, resources and skills they have to effectively succeed in applying the e-learning innovations, tools and software to employee education. The design and development of corporate training and learning programs should be highly tailored to the specific needs of the user. Instructional design initiatives should not be started without first ensuring that the content development technology, analytics and other tools used will produce materials that are beneficial to any and all members of the organization.
Providing training materials does not automatically mean that businesses are teaching their workers. To make sure that it translates into learning for the user, the right content needs to be used, in the right format, at the appropriate time. Different modalities should be used for training development applications, offering a variety of simulations and content delivery of e-Learning tools to ensure the appropriate audience is able to access the information through the channel that makes the most sense for them.
To make the solutions both versatile and individualized, organizations need to leverage the assistance of IT service companies who specialize in digital content and learning strategies. The supplier organizations use to design, develop and manage a training program should be one that has extensive industry experience and skills and is well-versed in the best content development technologies, as well as the predictive analytics and big data methodologies.