Prelude

Another point of view to HR work is data gathering and data analysis. Mostly I personally believe that the most effective HR solutions always come from face-to-face discussions and interacting with the workplace community, but Martin and Kirsten Edwards demonstrate in their book, that also data gathering with different styles and analysing the data can produce a workplace, where HR issues can be cut and identified before they even come out as a real problem. This is called predictive HR analysis, and its purpose is to predict the HR issues that may lie ahead through analysing the data, which is gathered from employees at work.

Base of Predictive HR Analytics

Edwards & Edwards define predictive HR analysis as follows: “The systematic application of predictive modelling using inferential statistics to existing HR- people data in order to inform judgement about possible causal factors driving key HR-related performance indicators” Simply said, this means using data to predict things that may happen in the future. For example, in a Team Academy team predictive HR analysis could be used to define which person might cause a conflict within a team or even leave the team before the team is even formed, based on the seven cells of predictive HR analysis data gathering.

Predictive HR analytics is based on these seven things:

1. Skills and Qualifications
2. Measures of particular competencies
3. Training attended
4. Levels of employee engagement
5. Customer satisfaction data
6. Performance appraisal records
7. Pay, bonus and remuneration data

If we put this on a single person perspective this is the data which is gathered from a single person. The persons’ skills and qualifications, persons’ level on competency, and so on through the last five points. There is data gathered from all of this, which and be used to form a person profile. When this is done about every single person throughout the whole company, we have massive amount of data to analyse.

Softwares

Softwares which are used in analysing the data vary a lot, there are many different softwares to use. Edwards & Edwards mention seven different softwares in their book, which are SPSS, Minitab, Stata, SAS, R, JASP, Jamovi and Python. From these softwares SPSS, SAS and R are the most popular ones. These different softwares are used in creating statistics from gathered data. Before using, you just need to know what you want to know. Another concrete example, if you want to know from gathered data that how many percent of people in same level of competence consider quitting compared to another level of competence or same thing that how many people feel stressed on certain competence level compared to another, you put the data gathered to some analytics program and enter the variables code, so you get your answer. Obviously, this same thing applies to all the data that has been gathered or that you want to be analysed.

How can these informations be used? Mostly these are used in identifying the problem. Through the data analysis, you can see where the problem is, and mostly what it is. Predictive HR data analysis doesn’t solve problems, but it identifies them and allows you to see what’s actually going on based on pure data and not some hunches. After the problem is identified, I still believe that in order to solve the issues, interaction is required, and the problem doesn’t fix itself. But in seeing and identifying the problem, the predictive data analysis offers a great solution. And as it is predictive, sometimes you might start to see the pattern of a starting problem before it even actually starts and cut it straight to its roots. That’s why data analytics is useful and should be used when measuring the HR environment at the workplace.