Skillsoft revealed new capabilities as part of its multi-phase joint development effort with IBM that leverage the power of big data in enterprise learning. The current phase of the program has produced algorithms to predict optimal engagement times, a content recommendation engine and a visualization framework to provide the foundation of a next-generation adaptive learning solution.
Skillsoft is a pioneer in the field of technology-delivered learning with a long history of innovation and delivering solutions for its customers worldwide, ranging from global enterprises, government, and education to mid-sized and small businesses.
Skillsoft has an unrivaled environment of 19 million users across 60,000 learning assets. Skillsoft partnered with IBM, a leader in big data technology, to mine its rich customer base's usage data and co-invent new customer experience analytics which are expected to make their way into the Skillsoft offerings. The initial results of this work will be presented to attendees next week at the 2014 Global Skillsoft Perspectives learning industry event.
"We are excited by the early capabilities we are developing with IBM," said John Ambrose, Senior Vice President, Strategy, Corporate Development and Emerging Business, Skillsoft. "We're building a powerful new big data engine that will enable us to optimize learning experiences and uncover new learning patterns that can be applied immediately so that the system is continually improving. This is the perfect application of big data - harness it and apply it to improve individual and organizational performance."
The key components of the joint Skillsoft/IBM effort unveiled today include:
· Engagement engine - mine usage patterns to understand users' evolving interaction preferences in order to identify optimal times and channels to engage with users
· Recommendations engine - create personalized learning recommendations leveraging user-content interactions, content ontologies and temporal consumption patterns
· Visualization techniques - to provide visual context for the recommendations to explain to the user why certain personalized content recommendations are being made along three different dimensions: people similar to the user liked this content, content similar to content the user liked, and popular content
With these assets in place, companies will be enabled to increase training utilization and completion rates through targeted learning and improved engagement, proving the investment value in a learning program.
According to Anshul Sheopuri, Manager of Consumer Modeling, IBM Research, "The objective of this collaboration with Skillsoft is to significantly improve user engagement by creating personalized learning recommendations that are delivered at times preferred by the user, and delivered visually to communicate the rationale behind the recommendations. We plan to pilot these big data technologies with select Skillsoft customers and measure usage outcomes, prior to deployment."
This collaboration between Skillsoft and IBM capitalizes on the explosive growth of big data and the efforts of organizations to find new ways to maximize performance using big data technology and analysis. In 2013, Gartner reported that 64 percent of organizations invested or planned to invest in big data technology, a continual increase from previous years. The corporate learning market provides an ideal application area for big data analytics. As organizations continue to offer more online learning to their employees, they need to analyze which learning experiences are the most productive and apply that knowledge to continually improve business outcomes. This combination of business need, data and technology presents an industry landscape that is ripe for capitalizing on the full value of what big data and analytics can bring.