Would people analytics make people short term oriented and cold?


The World Economic Forum have said they have identified three strategies that organizations should focus to increase people’s analytics capabilities to maximize their firm’s potential, that are

1. Investing in data analytics capabilities/tools to increase the accuracy of performance management,
2. Personalizing experience throughout the process by gathering private data, and
3. De-bias the decision making process of hiring & recruiting by minimizing people’s intervention.

But if all three factors several are met, would really organizations start to make accurate decisions to hire and promote people efficiently and accurately? I believe not. I think there are other additional critical factors that needs to be solved that the WEF is missing in order to make people’s analytics impactful for organizations.

The first question is, to what time-line are we having to judge whether an employee is capable or not ? According to the Bureau of Labor Statistics in the United States, the median number of years that workers work for their current employer is less than 4.6 years. For workers age 25-34, 3.2 years–much shorter. If we are going to be judging running models based on the performance data we gathered only for 3-4 years, is the data set gathered in that length of time sufficient to make a accurate decision?

For example, when I was working in Japan (where people work for average of 13.6 yrs in the same company), I identified significant amount of people who were star players in their 40’s, but they weren’t in their 30’s. Many people talked about how they didn’t do well for the first five+ years, but gradually or linearly improved over about ten years of experience. They thanked people who took care of them regardless of them struggling, and have great appreciation to the organization.

If an company ran an study of 1,000 new employees with average of 3-4 years of retention rate, that means they have identified the characteristics of the successful candidates “within the 3-4 years of time in their company”. That does not mean the data-set is sufficient to predict an star player in the long run (i.e. 10 years). But if they wanted to identify those “future star players”, they just wouldn’t have enough individual data to gather in a society where only an employer sticks for less than 4.6 years. So the question is, can they justify to exclude the people who might be bad performers in the first 3-4years, but might be stars in the long run? If so, how would that affect the loyalty of employee and the culture of the organization?

Even if the first question can be solved, the second question arises. How could you differentiate those who are truly incompetent, from the people who are competent but underperforming because of being influenced by external factors? Are the external factors identifiable ? Wouldn’t the overuse of people’s analytics increase bias rather than reducing it, by masking other uncontrollable factors that influence performance?

There should be careful consideration when deciding one’s performance besides just looking at the A~D grades made by their boss. How can you deny that the person who had an “D” was due to the bad chemistry with his/her boss? How would you identify the “D” person from the data set who was unluckily in charge of an downside industry? Currently, an “human” are taking all these situation into consideration. And this “human evaluation” would take time.

All in all, if the two questions above couldn’t be solved, my concern is that, organizations would be much more transactional, short-term oriented, and cold.


A world with deep people analytics capabilities allow us to experiment with radical ideas like the “Talent to Value” method

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