Talent and HR analytics are changing the talent experience due to applications of big data and intelligent machine learning systems in almost every aspect of talent management. To stay ahead of the tech-curve, HR and talent management leaders are beginning to adopt HR and talent analytics without really understanding what they are. This can be very dangerous, so in an attempt to stay clear from this trend, below are some of the common misbeliefs with respect to HR analytics:
Some HR leaders believe having large volumes of data is a good thing. However, Nanduri argues that any data expert would testify that rather than large amounts, it is the right type, form, and quality of data that gives the best insights. This makes having a clear data talent strategy extremely important, rather than jumping straight into the “data deluge.” Map out the talent analytics objective, research the right analytics tools to implement to help meet the objective, and outline the desired results.
Human vs. Machine
People tend to trust their gut feelings. It’s silly to believe in the results of a robot while ignoring the years of experience of a human HR professional, right? According to Nanduri, this “algorithm aversion” leads to a trend of going by one’s gut feeling even when the machine suggests otherwise. The unfamiliarity of working with machines is one of the main reasons for this, and it is something that HR leaders must refrain from if they want to leverage the best of talent analytics.
HR Analytics: Yes or No
Many businesses lose confidence because they feel they are not yet ready to take the analytics plunge. Doing research is important and will help, but ultimately, until you immerse yourself and learn by getting your hands dirty, you will never understand the real challenges. The key is to translate the talent analytics value-add to business value.
Need for Analytics Professionals
This relates to point #3, while talent analytics will require lots of research and statistical insight, this does not mean you have to go out and hire analytics professionals. In fact, many data analytics skills are available from third-party service providers.
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