Can HR data analysis be the link?
Successful enterprises seek to improve their operations through innovation. For many years, HR could focus only on precise or the most optimized processes. But by doing so a company could fall into the trap of becoming too rigid and could miss new opportunities or approaches. From which direction is the wind blowing now? Asking the right questions and answering them accurately with the help of HR data analysis could be one way for IT specialists and social scientists to work together. While it may be challenging at first to make these different specialists collaborate, once they understand that they have common goals the results can be very beneficial (e.g. IT specialist in data security, data analyst in the content of data, social scientist the implication for behavior).
Collaboration project between HR and Science
There are very interesting projects on the market. Google is noted for striving for innovation through their PiLab (People Innovation Lab). Among many interesting questions they focus on what makes managers effective. Under project Oxygen they gather all possible data (performance reviews, feedback surveys etc.) and their analysts provide the meaning.
Google statisticians gathered more than 10,000 observations about managers — across more than 100 variables.
What was the result?
The final list has eight recommendations, among them: “Have a clear vision and strategy for the team.”, “Help your employees with career development.”, “Don’t be a sissy: Be productive and results-oriented.”, but hmm, not pretty new things huh?
So they needed to make the question better and so rephrased it in a way that makes the thing much more interesting. How are the final eight recommendations connected to the success of the manager? In Google “deep technical expertise” was one of the eight recommendations, the least important. Of greater importance, is making that connection and being accessible. Based on these findings, Google developed training programs for their managers and began to support them with coaching for performance review sessions with individual employees. They reached statistically significant improvement in manager quality for 75% of their managers who had previously produced low levels of performance.
Data helps managers to understand what is important
The traps with biased decisions are within all HR processes. Any decision about people e.g., selection, promotion, development, and retention, should be based on data so as to avoid bias based on intuitive decisions. For instance managers often want to decide about whom to hire. They often prefer those they like and assess those criteria they think are important. So the lesson again is making decisions based on criteria that are really important and reduce the power of managers by giving more people possibility to decide who will be hired.
Simply discovering the effective approaches does not get the thing done. The next step is how these approaches can change behavior and that’s the field of social scientists who work with motivating people. That means training topics and coaching based on organized, concrete data.