E-learning and online resources create masses of data, much of which is ignored by many organisations. However, there is a lot of value in this ‘big data’, which if filtered and analysed by a learning management system can be very useful to a business.
Predictive analytics is one way of using this data to create predictions about future events, using techniques such as data mining, machine learning and predictive modelling. A corporate LMS can apply predictive analytics to recruiting, career planning, personalised learning programmes and staff retention.
An LMS can use predictive analytics to search for high-performing internal and external candidates to match hiring criteria and then deliver individually tailored onboarding to help employees become productive as soon as possible after starting a new role. With research suggesting it can take a new employee 20-30 weeks before they reach optimum productivity, this is a valuable benefit.
Predictive analytics can also be used to profile existing employees by monitoring their career movements, training needs and personal development. This can help to predict whether an employee is more likely to stay or leave the organisation and which employees are likely to benefit the most and add the greatest value to the business from training.
It can also identify both employees whose performance is likely to deteriorate, alerting managers so that they can take suitable remedial action at the earliest possible stage, and those with the potential to be future managers, leaders or high performers.
Predictive analytics is a powerful tool in an LMS to support HR and L&D managers whose responsibility is to spot, manage and retain talent in an organisation.