The ‚R‘ in Human [R]esources (or: a very brief introduction to the statistical package ‚R‘ for HR)
I studied psychology in Marburg (Germany). At university we exclusively used SPSS. The courses were among my classmates usually not the most popular. After over 10 years in management consulting, I have noticed that little has changed to this. It’s a shame because a lot of interesting data in consulting firms and HR departments remain unused.
In my role as managing director of kibit GmbH, I have placed the focus of the company on „R“ (instead of SPSS). We use R e.g. for the evaluation of employee surveys and 360 degree feedback. In particular, the possibilities of automation, the outstanding graphical capabilities and the reproducibility of our work have been decisive. Meanwhile, we have changed to RStudio as a graphical development environment (GUI).
Here in my blog I will publish in the future at irregular intervals interesting code examples (with links to HR). Perhaps some readers feel encouraged to give R a try. Well, if so, what should they do?
R is available for Mac, Windows and Linux. Installation is not complicated. When you first launch RStudio, you will be greeted by an interface that looks similar to this:
R is a programming language. As with other languages, also applies here: practice makes perfect. I personally think the website Quick-R, and this manual are good points to start.
Just to show, how easy it is, please open a new window (File -> New -> R script) and copy the following code into it. Then select everything (Ctrl-A) and press the run button.
assessors <- c(8, 10, 8, 5, 4, 7, 10, 6) names(assessors) <- c("Fischer", "Miller", "Mayer", "Master", "Hunter", "Smith", "Kim", "Baker") barplot(sort(assessors, decreasing = TRUE), main = "assessment center per year", col = hcl(h = seq(0, 240, by = 30)), horiz = TRUE, las=1)
In line 1 we define eight values, which we assign certain people in line 2. The third line generates the graph. If all goes well, we get the following result:
Can you plz elaborate how exactly you use R in employees survey evaluations or any hr data analysis? Can R also be used in predictive analysis on employees? Please guide on how to use R in HR.
your question is a very complex one… I’ll try:
– we use R to collect HR-data from very different Sources (SQL, JSON, XML, CSV, …)
– we mostly use the dplyr-package for reorganizing our data (merge, filter, …)
– we use latex-reports in combination with knitr and ggplot . This is a very powerful combination and it reduces the probability of errors. For presentation-formats, we use the beamer-package (with a custom template)
– we also use R for multivariate statistics on our data: cluster analysis, factor analysis, discriminant analysis…
I’m not sure, what you plan to predict. Of course you can model your predictive question. But I’m not an expert in this. Hope this helps a little bit. I also updated this articles images, because they got lost after the latest update of this site.