AMC used workforce analytics and employee profiling to determine the traits of excelling customer service representatives
AMC Theaters
AMC used workforce analytics and employee profiling to determine the traits of excelling customer service representatives. They used this data to determine who to hire to fit the ideal profile for customer service representatives. The result was reduced turnover, increased employee engagement, and better customer satisfaction (White, 2019).
AMC knew that to find and hire those that would be successful customer service representatives, they would need to find the key performance indicators for influential representatives. They used workforce analytics and employee profiling to determine what traits correlate to customer satisfaction, isolate those traits, and determine if candidates have those traits (Fitz-Enz & Mattox, 2014, p. 98). AMC could save costs and time by reducing their talent pool to fit the criteria and increase their efficiency once those quality candidates were brought on (Aggarwal & Minds, 2015, p. 2). By granting the best customer service representatives, AMC managers can provide consumers the best customer service and increase the number of customers attending its theaters.
E.ON
E.ON utilized predictive analytics to help determine why they were incurring a high number of employee absenteeism. They determined 55 hypotheses as to why the absenteeism occurred and determined that out of 21 tested, 11 reasons were verified. They concluded that the majority reason was the lack of a long holiday time off. The organization informed its managers to improve the employees’ PTO to decrease absenteeism (White, 2019).
In the case of E.ON, the lack of vacation time-off benefits given to the employees caused their increased absenteeism. The employees were dissatisfied, so they took time off of their own accord. E.ON realized the importance of employee value proposition, which determines the value of employees and ensures to provide them with their needs to be satisfied within the organization (Fitz-Enz, 2010, p. 57). They did this in the form of ensuring they had proper time off benefits. Managers can determine employees’ satisfaction levels, which can be significantly attributed to proper work life balance, to decrease the employee attrition rate and increase the demand for candidates desiring to work for them (Aggarwal & Minds, 2015, p. 2). By doing this, they can develop a competitive edge over competitors trying to obtain the same candidates.
References
Aggarwal, V., CTO, & Minds, A. (2015). Data science and predictive analytics enabling better hiring mechanisms for enterprises. Dataquest, Retrieved from https://search-proquest-com.proxy-library.ashford.edu/docview/1751474203?accountid=32521 (Links to an external site.)
Fitz-Enz, J. (2010). The New HR Analytics : Predicting the economic value of your company’s human capital investments. ProQuest Ebook Central https://ebookcentral-proquest-com.proxy-library.ashford.edu (Links to an external site.)
Fitz-Enz, J., & Mattox, J. (2014). Predictive analytics for human resources. Wiley.
White, D. (2019, June 05). Top 3 Examples of Predictive Analytics in HR: HR Technology. Retrieved November 12, 2020, from https://www.techfunnel.com/hr-tech/top-3-examples-of-predictive-analytics-in-hr/
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