Let’s face it, the world is different now than it was a decade ago. People are becoming more and more dependent on technology, and companies can collect viable insights from the data they collect, regardless of industry. For example, through predictive analytics, you can get a wide range of marketing insights, predict customers’ next purchases based on machine learning, and position ads to encourage them to make purchases. In this fast-changing business environment, companies can’t keep up with the pace of competition without using these technologies to improve their models.
With so many newly listed technologies bringing impressive customer and employee data to companies, why are there so many companies still using the static training techniques of the past? Most companies don’t value employee training – it’s a fact. Now it’s time to change, especially as one in three employees say unwelcome training is a barrier to their learning and may affect them from looking for new opportunities to leave the company. What’s more, sticking to the old training method is expensive. One study even found that ineffective training techniques could cost the company up to $13.5 million per thousand employees annually.
Corporate training departments also need to consider how much guidance employees need and how to address their individual learning styles. A recent work study at Middlesex university found that 74 per cent of employees felt less than full potential due to lack of development opportunities. From a management perspective, according to the 2015 talent development association study, 62% of hr managers thought they were not in line with everyone’s learning needs. These figures are very telling about the current state of enterprise learning and development.
How can corporate training departments address these issues and provide more effective training and development opportunities in the workplace? Enterprises must adapt to the requirements of 21, and ST new technology is incorporated into its own enterprise training scheme century staff.
Today, enterprises can gain insights and intelligence about learners from the analysis of labor and human resources, and promote enterprise learning plans. There are technologies in the market that can take advantage of automation, real-time personalization to tailor learning content to each user’s unique learning style, speed up the entry process and maximize work efficiency. These technologies not only make users feel that the training content caters to their needs, but also that human resources and training managers can expect to improve the training effect.
Personalized learning techniques address past problems due to outdated training techniques, because employees can teach information in ways that maximize their potential. You may have heard that some of us are visual learners, some are auditory learners, while others are doing it. By implementing cost-effective tools based on machine learning algorithms, two employees in the same training project there will be a completely different experience: they will be according to the learner’s behavior, cognitive preferences and participation.
The meaning of social learning
With new technologies, you can also use employee behavior data to determine how he or she best responds to information by learning about the history of social networks on the management system. You can focus your analysis on how people interact with each other on chat or discussion boards to determine who is the knowledgeable communicator, who is the intellectual seeker, and how to change from subject to topic. Not every employee is a corporate training program in each topic put forward by the experts, but by interpreting network data and the use of machine learning, you can determine the content of employee is known, professor need and how to teach the content of the employees get the most understanding.
After high school or college, learning and development won’t stop, it’s a process that runs through every employee’s life. To best prepare for successful careers, and maximize enterprise training investment, enterprises need to start using the correct data and the right analysis to personalized training, in order to transfer knowledge and improve the results.