Finally, the HR world has discovered how to utilize Big Data. HR managers agree that \u201cdata are the oil of 21st century\u201d. There are big expectations placed on these bits and bytes that sleep softly in numerous databases. Could it be that the expectations are too high?<\/p>\n
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As the term implies, Big Data refers to a collection of data sets that are too large and complex to analyze with standard statistical applications and data base systems. Unfortunately, there is no BMI to tell data when they are getting big or when they become obese. Suppliers of standard applications have already started to enhance their products with new features so they are capable of handling larger data sets. This just makes the definition more vague. It has been reliably estimated that the amount of data doubles every second year. HR departments contribute to this since IT\u2013systems have replaced paper personnel files with a wide range of tools from application tracking systems to computer-generated letters of resignation.<\/p>\n
Talent analytics, talent management, feedback, e-learning and many other systems\u2019 databases accumulate enormous sets of usable data, offering great potential to data driven HR processes. In many organizations, relevant data about the company\u2019s workforce is stored over the entire HR life cycle. Data analyses can be used for a variety of tasks, such as determining the efficiency of a recruiting system. Nevertheless, data collection is a long way from producing beneficial information:<\/p>\n
Even if the brave new data world offers a lot of potential; data are not a substitute for using our brains. Furthermore, the \u201cend of theory\u201d suggested by some big data enthusiast will have to wait. Relationships in the HR field and in organizational research are often quite complex (mediation- and moderations effects rather than linear relationships). Nevertheless, many ad-hoc analyses reveal nonsense or trivial relationships and therefore result in wrong conclusions. HR KPIs like job performance or turnover rate are driven by multiple factors (for people with deeper interest read the Journal of Applied Psychology)<\/em>.<\/p>\n Organizations and their contextual factors vary. Even within an organization factors such as personal characteristics (demographic as well as psychological ones), leadership- and organizational climate vary between departments. One of the main weaknesses of the big data approach is that it ignores micro organizational processes. Other analyses fail because of a simple lack of basic statistical knowledge: probabilistic relationships are used for deterministic predictions, cause-effect relationships are derived out of correlations, third variables are included and predictions made on past data (regression) might be useless when bordering conditions are changing. It is just a question of time, before the next statistical super brain will get to the conclusion that the hiring of employees is one of the main risk factors for fluctuation (a mean comparison revealed that rejected candidates showed a significant lower turnover rate, 0.0%, to be exact). Another emerging topic due to big data in HR is data security and privacy concern. Data related to employees are legally more protected that other ones.<\/p>\nFurther reading:<\/h5>\n