We live in a quickly changing business environment and innovation could be detected everywhere. The speed of the development is already high and it accelerates exponentially. There is available data everywhere and about everything, this means a huge amount that should be used and handled properly. Human Resource Management departments should be ready to use this data and be sophisticated enough in data analyzing and understanding. HR industry and departments within the organizations should put on speed.
How long did it take for the biggest online applications to reach 100 million users then and now?
Also there could be another aspect we have to take into consideration regarding the future of HR according to Tomas Chamorro-Premuzic, which is the following:
“UBER DOES NOT HAVE CARS, AIRBNB DOES NOT HAVE ROOMS, FACEBOOK DOES NOT HAVE CONTENT, FUTURE COMPANIES WILL NOT HAVE TALENT?”
Of course the above hypothesis is logical, but cannot be true, since there will always be talents in the companies, maybe the skills and competencies will be different from those needed today. HR departments need solutions leading them to such conclusions and finding such coherences – by analyzing their historical data.
How Human Resource (HR) departments can overcome the obstacle of data analysis? “They should be proactive, analytic and sophisticated in using the available data.” – according to Grant Freeland the Global Leader – People & Organization Practice of The Boston Consulting Group.
What should be then the levels of (BIG) data analysis regarding the HR departments?
The level of the reactive approach could be found in most of the organizations. Companies use this approach ad hoc, but the results could not be used in the long term. When an organization try to adapt itself to market changes and start to analyze ways for the adaptation.
The pro-active approach or analysis searching proactively the answers from more aspects and view-points, for example by the determination of the benchmarks or supporting the decision making processes.
With the help of the strategic analysis HR departments will be able to build models, ideal and excepted profiles, which could be extremely helpful during the selection process, these profiles should be the basis of the selection (Who is needed for the position?, Who will be successful in the position?, Who has been successful in similar positions in the company?)
The top of (BIG) Data analysis for HR is the forecasting. Who would not know, which employee will leave the company within months? Which leader would leave out from the planning process that most of the newcomers will be discontent if they do not receive the customized motivation? Who will be the concerned employees and how the company can intervene?
To be more specific, we would like to list some examples below, where the usage of BIG Data made the company more effective
The first example is connected to the selection criteria, most of the companies use to pick the right person for a position.
The basic hypothesis: One of the most important selection criteria was the qualification of the applicant, this means that the students of famous Universities can find a workplace easier, then their peers.
Method: Data analysis for proving the above hypothesis, or fine-tune the group of criteria with prioritizing them, for better performance.
Results: The analysis showed that there is only a slight correlation between the success of a salesperson and the University qualification the person owns. In this case the good performance originated from the knowledge of the market, the sales mindset, good time-management skills and multitasking abilities and not the level of the University qualification or the showed references.
Action: Building these factors amongst the selection criteria, the organization raised its revenues in half a year by 4 million Dollars.
We have chosen our next example from the telecommunication industry, where the telco company used the data analysis method for employee selection
Problem identification: The problem inside the organization was the high employee turnover rate (13.1%) and the financial consequences originated from that. Their employee selection process was sophisticated, but with the use of Big Data analysis they could advance their system.
Method: The first step was the identification of the successful and less successful call center employees and their competencies with the help of HR, psychometrical and business data.
Action: The company built the findings into their selection processes.
Results: The results exceeded the expectations, since the employee turnover rate decreased to 8.64% within the first year (the expected value was 10%), and in the next year the employee turnover rate dropped to 6.57%.
From the above examples it is crystal clear that the results of Big Data analysis could be easily transformed to business results, or even to specified cost savings. Although this topic could be still mentioned as a mythical tool, but the results show great evidences on the contrary. To be a winner with Big Data analysis the most important factor is not money, money and more money, BUT rather to make more and more measurements and metrics. Moreover the results of the metrics and measurements should be built into the HR processes like selection, development, strategy. HR leaders should keep pace with the development. The most important criteria are the create smart, pro-active, analyzing, flexible and ready-to-change HR strategy. This is not the future, but rather the present of HR. If companies will not identify that this should be in the focus of their fundamental interest, will they survive? Companies should be quicker and more flexible, make use of their collected data and learn, draw the consequences, or they will fall behind.