Employee training is an inevitable part of organizational growth. Most companies invest a great amount of money and time in training their employees. The justification behind such huge investment is improving staff competencies and productivity, which ultimately spills to garnering higher profits. However, measuring the effectiveness of such employee training programs remains a big puzzle.

Many companies are failing when it comes to measuring the impact of their training programs. A recent study found that 96% of learning and development leaders are searching for ways to improve data gathering and analysis on training, yet only 17% currently even measure impact. But how does one measure impact?

The most popular model of measuring the effectiveness training is the Kirkpatrick model. This model developed by Donald Kirkpatrick in 1959 essentially has five levels that claim to measure the effectiveness of any kind of training. Let’s look at each of them in detail.

Level 1 – Satisfaction

This focuses on how the trainees have reacted to the training they undertook. This is crucial for L&D professionals to understand because it helps them pinpoint what was preferred by the learners and what wasn’t. Through employee feedback, companies can learn about what they liked and what parts of the training they couldn’t agree to. Questions could be related to the quality of the content, the style of the trainer, the venue, the format, etc.

Level 2 – Learning

Every training program begins with a series of well-defined objectives, be it increasing theoretical knowledge of participants on a particular topic or improved soft skills. This level measures how much of the knowledge in the training program was actually acquired by the learners. This is usually done through pre and post training assessments of the participant’s skill level.

Level 3 – Impact

This level looks at behavioral changes that occur as a result of the training. It aims at seeing whether or not the concept delivered during the training is being applied on the job or not. This level measures how far the behavior of participants has changed on the basis of the training they received.

Level 4 – Results

This is the final step where the results of the training program are measured. This level is considered the most difficult as it involves identifying whether the outcomes and objectives of the training program were achieved or not. These tangible results could be decreased costs, improved productivity, higher sales, lower employee attrition, higher employee morale and others.

Level 5 – ROI

Since implementation of training involves huge investment, the last step involves calculating the return on it. This is the stage where data analytics comes into play that can help L&D professionals understand exactly how much gain or loss has been made. Meaningful insights in the form of data at regular intervals can help suggest appropriate action to help maximize ROI in the long run.

This is why organizations have increasingly come to depend on analytics to make strategic business decisions when it comes to learning. Using the right kind of technology to collect and analyze large data sets at low prices can prove to be very advantageous. Learning and training are after all the fundamental tools required to improve employee productivity and engagement levels.

What is the solution?

1. Predictive analytics

For efficient learning, companies need to redesign the way they conduct training programs. This needs to be done in a way that learning caters to the needs, preferences and styles of employees. The modern learner has a tremendous passion for consuming knowledge in their respective fields. They want to be able to learn and also share and collaborate about their knowledge with those around. Learning needs to enable them solve real problems, become more confident and also align with their lifestyle.

Companies need to redesign their training programs to cater to the learning needs, preferences and styles of their employees.  The modern learner at the workplace expects continuous learning opportunities in a way that suits their lifestyle. They demand content that is available 24*7 on mobile devices, and that is highly relevant to their daily problems and challenges.

Measuring the result of any training program requires measuring how much the participants have actually learned in the process. One way of achieving this could be through predictive analytics where the behaviour of learners is tracked on the basis of their performance throughout the training. On the basis of this data, learning programs are adjusted and reshaped in order to accommodate the needs of the learners.

Predictive analytics can also be used to predict key events in the future for employees, such as whether or not an employee will pass a course, or whether or not they will retain knowledge. Such data helps identifying key behavioural traits and patterns correlated to success or failure in undertaking a particular training. Such brilliant insights can help top tier management to chart out better future learning strategies to improve performance.

2. Personalized experiences

Personalization in learning is the biggest feature that can enable competitive advantage for organizations. Today learning is about “flow” not “instruction,” that helps bring learning to people throughout their digital experience. Only if LMS’s consider all these parameters and are reinvented will they see the future. Otherwise, this $4 billion industry will probably not be a thing in the future.

Each learner is unique and so is their learning style. This is why one size fits all approach does not work in training. Each individual learner’s personal style needs to be assessed and relevant content needs to be pushed out to him/her accordingly. Such personalized experiences not only increase engagement, but also help align the training program with the preferences of the learner.

The way to do this is through adaptive learning, a technology that collects data about employee choices, performance and preferences as he progresses in a training. This data is then used to personalize goals and learning content so that the learning is most suited to the needs of the employee.

Before delivering the training, it is imperative for organizations to do a thorough research on the background and skill set of their learners. Without knowing them thoroughly, learning cannot possibly be created in a way that they would want to consume. The goals should be to allow the learner to successfully attain the learning objective set by the trainers. In other words, the learning should follow an individual’s own preferred learning path.

Data can be analysed through such powerful tools that relies on principles of predictive analytics and adaptive learning. However, the number of organizations actually implementing these tools are not many. Perceived barriers include not knowing where to begin or general confusion on how to implement a step by step process at reasonable costs. But the solution lies in identifying the right technology and platform in helping organizations collect and analyze their critical data. Because measurement of data is a prerequisite for implementing successful training programs.

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