Reference no: EM131643393

Discussion

Respond to the discussion post below with YOUR educated opinion in 3 sentences WITH scholarly source backing it up

One type of data that our HR department processes is "Employee Action Reports" or EARs. The EAR reports provide data as to the movement of employees throughout the company as either a hire, termination, promotion or relocation. While this data has an actionable purpose, notify IT to inactivate users, accounting to set up payroll, marketing to order new business cards and so forth, it also has strategic relevance once analyzed. As a time series (Sharpe, De Veaux, & Velleman, 2015, p. 8) this data can be combined with sales data to produce the measure, Revenue Per Employee (RPE). RPE divides total revenue at a company by the total number of employees during the same time. However, the how of this statistic is also important. While the total sales at the end of the year is obviously a sum, what about total employees. Is it the total number of employees at the end of the year? What if there was a hiring or firing frenzy in the last month. Or is it an average or median (Andale, 2013) of employees over the year which will produce an entirely different statistic.

According to Kris Dunn RPE is the only statistic that matters when evaluating the performance of an HR executive(Dunn, 2011) . However, if two companies have the same revenue per employee does that mean the HR executives are performing equally as well. What if company A has far superior products while company B has a superior sales force? Product quality is probably a greater contributor to RPE at company A than the effectiveness of the HR executive. While training, initiated by HR at company B is the reason their sales force is superior. I would argue that is a hypothesis that should be proven out through a statistical approach, Hypothesis → Data → Conclusion (QualityGurus, 2012). Where the hypothesis would be RPE measures the effectiveness of HR executives. Then determine data that would support or disprove the hypothesis. Data like the activities performed by the executive, perception of their effectiveness, number of direct reports and more. Determine how to collect the data, probably surveys but also some reports. Then attempt to draw conclusions to the hypothesis from the data. I think this might provide a different outcome the provided by Dunn.

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