Enterprises now acknowledge the value of having a highly capable workforce. Furthermore, the ever-changing business landscape now demands workers to continually up-skill and re-skill. Therefore, most organisations are now reinforcing their human resources and learning departments to help them address this need. This inevitably results in increasing volumes of learning sessions to be conducted. With that, employees also has doubts regarding the effectiveness of training programs.
Thus, this is where data analytics comes into play, to bridge the gaps. The adoption of technologies such as learning management systems (LMS), knowledge bases, and communication & collaboration platforms in employee training and human resources has also increased the data available to enable analytics in playing a role in this business area. So here are ways how can training departments leverage their data analytics to overcome employee training challenges.
Insights and Predictions
With the presence of data analytics, training departments are now be able to draw insights on how they can better cater to the actual needs of employees in their respective functions. Trainers can check their LMS data and observe course progression, test results, completion rates, and even feedback to see how employees respond to the various topics. Training efforts can also be used to track against other HR metrics such as employee performance. This way, managers are able to track if their employees benefit from the training. In doing so, training departments could investigate the performance gaps and root causes behind them. This may include eliminating unpopular training programs and promoting those that do lead to improved performance.
Another way data analytics can be used to improve training programs is through automation. Not only does this address the challenges brought about due to scheduling, but also increases consistency and productivity of trainers. Many training programs are now designed to be asynchronous and even self-paced. However, this requires employees to be disciplined enough to finish the training. LMS can be configured to track employee progression and based on completion rates and stagnancy, automatically notify, and encourage learners to continue. Learning materials can also be programmed to be gamified to increase engagement.
Additionally, chatbots and virtual trainers can also be used to take over the more routine training sessions, such as onboarding sessions on company policies. AI’s improving natural language capabilities are now capable of facilitating employee questions, giving such programs an added dimension of engagement and interaction.