People analytics is based on applying data science techniques to
human resources with the aim of getting to know the people of our
organization better and increasing their degree of satisfaction and
productivity.
Large organizations are so complex, and their operations so remote
from each other that it is virtually impossible for management to
see some of the vital connections and influences. Current people
analytics techniques include developing algorithms to analyze, and
statistically balance the connections between internal and external
factors, while optimizing processes, delivering services, and measuring
performance.
A typical example of how people analytics can intervene is in
analyzing and improving turnover rate. A predictive model can
identify which employees are at risk of leaving the organization,
and even when they will leave, and the reasons why.
Unlike other assets in the company, the value of human capital
grows over time. As each employee gains experience, their talent
and experience increase. The more experience they have in the
company, the greater the loss when they leave.
On average, every employee who leaves an organization costs the
company one or two times their annual salary. Turnover analyses
reveal some unforeseen key differences between employees who
stay and those who leave:
1. Whether they have had a track record of not staying long
with any job or position
2. Their demographic, their job position, or even their commute
distance
3. Whether they are within or near a period that typically has
high turnover (e.g. their first four months or their second or
third year in the company)
What Is People Analytics about?
There are also some signs that can help anticipate employee discouragement
and risk of leaving the company, such as absences,
coming in late, or declining performance ratings.
From this and other data, you can apply an algorithm that classifies all people according to how likely they are to leave the company.
Those who rank higher in the model and are more valuable to the
organization will be the first to receive special attention.
Ref: People Analytics - Data and Text Analytics for Human Resources - Eduardo Valencia. Data Analytics Manager - Analytics to Grow.
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