There are many alternative approaches to common evaluation models like Kirkpatrick's Four Levels, the Phillips' ROI Model, and the Success Case Method. Identify ways to improve your evaluation process by applying new techniques, such as the use of predictive analytics.
- In this video, we're going to explore some alternative approaches to traditional evaluation models. In many cases, we don't need to conduct a comprehensive evaluation study. We just need to know some specific pieces of information to tell us whether the training is working, find ways to improve it and demonstrate its value to sponsors. One option is to focus solely on employee performance. In some programs, the training isn't complete until a participant can demonstrate specific skills on the job.
A technician might need to fix something to finish their training. A customer service rep might need to pass a product knowledge quiz before helping customers. Some companies have created a 90-day version of their annual performance review to evaluate new hires. The advantage of focusing on performance, is you blend evaluation with good training. If a person can't demonstrate the required skill, a manager or a trainer can work with that person to diagnose the reason why. Another evaluation approach is to apply for industry best practice awards.
This provides external recognition of your training program's value. Some companies use awards in their marketing to showcase their well trained employees as an advantage to perspective clients. In other cases, winning an award can give a program instant credibility and increase its support from senior executives. The association for talent development or ATD, hosts annual best practice awards. You can get more information at the website shown on the screen. Local ADT chapters and other professional organizations often have their own best practice awards too.
One trend on the horizon is applying predictive analytics to training programs. Most evaluation approaches look backward at what's already happened. The goal is to gain insight that can be used to improve the program in the future. With predictive analytics, you capture data that can help you influence results before they happen. For example, let's say you want to increase the success rate for people attending a training class. You'd start by analyzing both successful and unsuccessful participants to see what they do differently.
Perhaps you discover it, that when participants do better, their manager meets with them before the training to discuss how the training is linked to their job. Armed with that insight, you could survey participants attending your class to learn who had that conversation and who didn't. If a participant indicated they met with their manager to discuss the training, you could predict that they'll apply their new skills back on the job. But if a participant said they did not have that conversation, you could provide extra support to help them implement what they learned in training.
There are a lot of great developments in the use of predictive analytics. I've included a link in the Additional Resources File to some of the pioneering work on this topic being done by Ken Phillips and Trish Uhl. Okay, these are just a few examples of alternative approaches to evaluation. Keep in mind, there's no one way to evaluate training. Whatever approach you take, it's a good one if you're generating useful insight to help you achieve your evaluation goal.
Check the exercise files for sample evaluation plans, reports, checklists, and worksheets that you can use to evaluate your own employee development program.
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- Common learning assessment models: Kirkpatrick, Phillips, Brinkerhoff, and alternatives
- Identifying expectations
- Collecting data
- Analyzing data
- Making recommendations