Free luxury lunches, excessive bonuses, free laundry service, energy pods, 20% of your time may be spend on your own side-projects, longer parental leaves, it seems that it takes much effort to thrive employees performance nowadays. However, looking more closely into Google’s HR strategy, or as they call it: people operations, one finds that Google is deeply engaged in the well being of their employees and is not afraid to take onorthodox actions to improve both employee performance and satisfaction. And how do they know the effect of these actions?
They analyze the data!
What might work for Google, doesn’t necessarily work for other organizations, so what does work for your organization? To help organizations answering this question Google decided to share their best practices by launching the platform “re:Work”.
This platform includes best practices, case studies, and blogs on various HR topics such as Hiring and People analytics. Besides Google, other organizations also decided to lay their cards on the table and shared HR practices on the platform, including Jetblue and Wegmans. The common divisor of these practices? Measure the effect of your HR policy and act on it!
One of the hazards of not measuring the effects is that we fall into our own judgmental bias: we think we make the right decisions while in reality we do not. This for example often happens during unstructured job interviews: during an interview the interviewer tries to answer the question: “Is this candidate suited for the job”, which is a difficult question to answer. Hence, as professor Daniel Kaufmann describes in his book “Thinking fast and slow”, we tend to answer an easier question instead: “Do I like this person?”, or “Does this person fit the stereotype of the employee I have in mind?”. This replacement happens in the unconscious mind without the interviewer realizing it, resulting in the interviewer being convinced that he/she answered the original question. That answering this simpeler question has little predictive value has been shown by various studies including internal analysis at Google.
Hence having intuitive thoughts on how to optimize your HR operations is definitely important, but just by analyzing the data you know for sure that the policy works and you are not fooled by your own judgmental bias. So how can you use analytics to reduce judgmental bias? There are many options here, a great introduction into applying HR analytics to your business is given by Tracey Smith: “HR analytics, the what, why and how”, in which she introduces the HR analytics maturity curve (figure below) and shows how to increase your HR analytics maturity level. Personally I would advise to “think big, start small”: start with analyzing small datasets with only a few parameters, initially use simple visual analytics such as bar charts, pie charts, histograms, boxplots etc., and if you want to apply a new HR policy: use a/b testing to test if it actually works. This way you are able to get an initial feeling of the possibilities of analytics in your organization and you can identify where problems may arise when increasing the complexity of the methods used or when increasing the size of your dataset.