Use big data to retain your best talents

reter_talentosYour employees may be planning to leave the company this year and - worse - your best talents may be among them. We already covered CareerBuilder's research that shows this trend. In the survey, 3,008 American workers were interviewed and, of these, 21% consider leaving work. Among the reasons, they do not earn as much as they would like and do not feel valued.

For those who are satisfied and do not want to change jobs, 54% like co-workers and half the balance achieved between work and personal life. Others are pleased with the benefits and happy with what they receive. The year before, another CareerBuilder survey revealed that the title, position, or job is not important in getting it or not. Information about this research is in this article.

According to CareerBuilder VP Human Resources Rosemary Haefner, employees want to “be well compensated; they want to be challenged; want to contribute to something meaningful; and they want to have a good balance between life and work, ”he said.

The Human Resources department can manage a range of incentive programs, career paths, bonuses and can also rely on something more accurate: Big Data information.

It is with them that you can leverage employee data to improve operational performance. With Predictive Analytics, you can understand performance and retention engines by using statistics to decide who to hire, analyze whether payment correlates with performance, and so on.

According to the survey “High-Impact Talent Analytics“From Deloitte, companies using Big Data have stock market returns 30% higher than S & P500. They are twice as likely to provide high impact recruitment solutions and their leaders are 2.5 times healthier. HR professionals are four times more likely to be respected by business colleagues for making data-driven decisions. 

Research further shows that talent analysis is much more than big data and statistics tools. Companies have also been investing in relationships with the finance, operational analysis, communication and design teams, as well as business consulting's ability to focus on the right issues.

Most HR professionals who responded to the survey said statisticians are easily found, but find it difficult to find project managers who combine “data” and “business,” and those people who translate big data into one program. or solution that drives business change.

One of the biggest challenges of big data analytics in companies is changing the behavior of professionals once data is presented, as most managers have their way of working and years of experience that push them away from the scientific data shown.

Paying people to boost performance

One of the examples of the research is very interesting and can answer what we proposed in the title. One of the surveyed companies studied employee turnover and retention based on salary increases. They used to pay the best performers per grade, with the first earning more, the second a little less and so on.

But research has shown that this system is a mistake. The survey revealed that grade 2 or 3 employees would stay with the company even if they earned below 91% of the average increases of category professionals. That is, people are being overpaid. On the other hand, those at the top would leave the company unless they received 115% to 120% of the average salary increase, showing that payroll money should come here.

This may seem like a bold solution, but it is what the data revealed to the company in question. The solution for each company will vary depending on your business model, performance, etc. After all, it is your private data that should be considered. But this is the future for those who want the best performance.

Want to know more about it? Contact us.


With certified analysts and partners in various countries, our offices are located in:

São Paulo - Brazil

+55 11 96186-7935

Rua Mourato Coelho, 957

Vila Madalena

Miami - USA

+1 (305) 400-1529

777 Brickell Ave

Miami, FL 33131


Buenos Aires - Argentina

+ 54 11 6438 1196

Av. Juan Bautista Alberdi 1310



Copyright © 2021 • All rights reserved