Why Employee Training and Big Data Should Work Together

The flood of data available today is growing by leaps and bounds as expanding networks are able to capture real-time user decisions in an instant. The ability to analyze this data for trends and insights is becoming an eagerly-sought advantage for corporate training companies and organizations of all kinds. But more of them are beginning to discover that it poses benefits beyond marketing forecasts and instant statistics. Big data is being adapted to e-learning processes to train better employees.

Data-driven approaches are being used to perfect adaptive learning, create better courses, and provide electronic monitoring and testing in ways a single human instructor couldn’t cope with. Around 77% of US companies offer e-learning, but little of it leverages big data. Here’s why every company should bring big data to employee training.

Big data computing can return analytics that quantify all the results of employee training – lesson retention, employee learning needs, more productive curriculum and techniques, and improved learning software. Learning directors are able to look at a number of different factors and determine which works and which doesn’t.

Organizations can develop metrics for each training module based on employee learning time, test results, questions, and feedback. Do certain methods work better with some learning topics than others? Companies should treat employee training the same way they approach user testing. Analysis can determine and focus on which parts of training employees find most engaging, and which parts require special emphasis or have little real-world value.

Gauging employee results and feedback on their e-learning progress provides insights on how learners relate to the material that’s presented. In addition to narrowing down the options for the most effective approaches, by establishing quizzes and interactions at strategic points trainers can determine exactly which lessons incur the most errors or misunderstandings. This allows the trainers to adapt programs to be more effective even in the most granular and subtle ways, leading to iteration, that provides a better learning experience as a constant process of improvement.