Employees need to be taught at work in order to do their jobs in the best way they can. But as it stands now though, many workers receive little to no training at all and the training they do receive is often bloated with useless information and wastes time. Nearly 60% of workers are entirely self taught and this lack of learning leaves many unsatisfied. The majority of workers feel that they could be doing more work more efficiently if they had more opportunities to learn and 70% would consider leaving for a job that gives them that opportunity. Most workers report they don’t have the skills they need to do their jobs and only 12% are able to use what they learned in training in their actual work.
Traditional ways of training are ineffective and costly and create a poor experience for everyone involved. On average, it takes 7 clicks through a learning management system to access specific information. But after only 3 clicks, learners perceive a massive spike in difficulty, making reaching information near impossible for many. Creating a course or a small event can take up a huge amount of time and money while not teaching workers anything. A one hour course can take hours to set up and a small, one-time, in-person event can cost upwards of $40,000. These standalone training events, in addition to being costly, also don’t create lasting learning with up to 80% of information being lost within just a week. With the average adult having a maximum of a 20 minute attention span, these events quickly become boring and exhausting to sit through.
Learning small amounts at a time instead of cramming information into one larger event makes lasting learning by creating mental pathways. This helps employees apply new knowledge into their actual work while not wasting time with unneeded and extra information. Bite sized content for learning over messaging tools is easily accessible to anyone, without the huge cost of setting up a training event.
Learn more about how microlearning works and how it teaches what employees actually need to know here: