Training ROI

Part
01
of one
Part
01

Training ROI

Two best practices for calculating the return on investment (ROI) for employee training include the use of data mining and evaluating employee turnover rates.

Data Mining

Description

  • One best practice for calculating the ROI for employee training is data mining. Data mining involves a procedure in which businesses convert raw data into insights that are beneficial. They utilize software to locate significant patterns within massive data volumes.
  • Learning management systems are often utilized by some businesses to obtain metrics and produce reports that offer insights into a training practice's effectiveness, using various variables.
  • Furthermore, data mining can utilized to analyze a company's high performers' data to recognize any trends, patterns, or correlations within their training.
  • According to HR Technologist, these metrics are dropout rates and time spent finishing each individual activity, as well as the duration of time used for each activity or course. An additional metric is completion rates.
  • Companies can also employ pre- as well as post-training surveys to use for data mining, which are capable of providing them with immediate insights. As stated by HR Dive, some forms of data take time to gather, such as indications of the training sessions generating any behavioral shifts that the company may be seeking.

How/Why it is a Best Practice

  • It is considered a best practice because it is capable of producing far-reaching insights. For instance, with the use of data mining, a company can determine if its training session was too complex/complicated for trainees to comprehend, which can be indicated by noticeably high dropout rates, according to HR Technologist.

Evaluate Employee Turnover Rates

Description

  • Another best practice for calculating the ROI for employee training is by observing employee turnover rates, which is a widely assessed HR metric. As listed by TalentLyft, employee or staff turnover is an evaluation of the volume of workers that are choosing to leave a business (voluntary and involuntary).
  • Turnover rates can serve as an indication of whether employees are getting the appropriate training and opportunities for development.
  • Companies can develop mobile training programs containing various courses, which can consist of skill development sessions, that cover several domains for their workers. After they finish any course module, workers can then search for other courses and improve their abilities, as well as adapt brand-new ones. According to Kitaboo, this action enables employees to advance their expertise and skills, resulting in opportunities for growth within the company and decreasing the volume of worker turnovers.
  • This action also strengthens the return on training investments.
  • The metric used to measure employee turnover is the share/percentage of workers that decided to leave a business in a specified time period, and it is primarily computed either monthly or annually. According to TalentLyft, it is measured "by dividing the number of employees who left the company by the average number of employees in a certain period in time." Finally, to obtain a percentage, this figure is multiplied by 100.
  • In the United States, the average employee turnover rate is between 12% to 15%, but it varies depending on the industry.

How/Why it is a Best Practice

  • As stated earlier, employee turnover rates can help to determine the effectiveness or suitability of a training course/program. A high employee turnover rate can expose dissatisfaction amongst a company's workers, much of which can stem from the lack of proper training.

Research Strategy

During our research, we were able to find two best practices (data mining and employee turnover rate) for calculating the ROI for employee training and most of the requested details. However, we were unable to find examples of companies that employ those practices for the purpose of measuring the ROI for employee training specifically. Below is the research strategy we employed for the missing information.

We first searched through credible human resources-related sources discussing these best practices to see if they mentioned any companies that adapted them. We believed that since such sources focus on the human resources department, which is usually involved in employee training, and served as the primary sources for our research, they would offer a list of companies that employ the practices. These sources included HR Technologist, HR Dive, EmployeeCycle, among others. However, this research strategy failed to yield the information we were seeking as they never mentioned any businesses that use the procedures included in their reports.

Next, we explored for reports and articles discussing the use of data mining and employee retention rates to measure ROI for employee training. We consulted reputable blogs, news, and media sources, hoping that they mentioned the businesses that adapted those specific best practices. These sources included Forbes, Business Insider, Chron, etc. Though we found reports on data mining being used by companies, this action mostly concerned the use of data mining on customers/clients. There were no reports available in the public domain on companies using data mining or employee turnover rates to measure the ROI for employee training.

Finally, we searched for recent case studies centered on the implementation of data mining and employee turnover rates to calculate the ROI for employee training. For these case studies, we searched through prominent research resources such as Researchgate, hoping they offered details on any companies that adapted the best practices. Nonetheless, most of the case studies we came across only discussed the use of data mining and employee turnover rates as a general topic, as opposed to metrics being used by specific companies to measure the ROI for employee training.
Sources
Sources