When large data meets HR

On the topic of big data we see a lot of--no matter is massive data scale, uses the big data to do "solves" the sharp weapon. But today the topic is real people to feel and realize the impact of large data: large data recruitment.

The more correct argument should be "Labor science" (workforce), which uses a huge amount of data for human resource management. Plainly, is "Big Data meet HR". Enterprises are certainly very welcome to this change, because they can improve the efficiency and accuracy of their recruitment (to know, many enterprises recruitment criteria, originally rely on "feeling").

Real Example: Global customer Service call center Transcom, because the company's turnover rate is too high, in the second half of 2012 using large data for employee behavior analysis. When analyzing the quality of honesty, employees are asked if they can perform simple shortcuts, such as copying and pasting. If the answer is yes, they will be asked to do the actual operation on the keyboard.

As a result, Evolv, which collects and analyzes data, found that employees who scored high on "honesty" were 20% to 30% more stable than other employees. As a result, transcom changed the hiring strategy, giving priority to hiring employees with the same type of "trait", which reduced the number of employees they employed by 20%, because the team was more stable and saved the cost of training new staff (the cost of the new hire was about 1500 dollars/person).

Large companies do not want to let big data recruit this piece of cake. Last year, IBM also bought Kenexa, an online recruiting and training service, with 1.3 billion dollars to cover 40 million of job applicants and managers each year. The New York Times shared one of the details, and IBM found that the trait of a successful salesman is not in his extrovert personality, but in the strength of his self encouragement, which is the quality he insists on after being rejected. and other companies, such as Oracle, SAP are also following up on big data-recruiting services.

In addition to large enterprises, many entrepreneurial teams are also engaged in this area of service. As mentioned above, Evolv, as well as the Silicon Valley entrepreneurial team Knack, are all for the enterprise to provide recruitment, training and talent data analysis of large data services.

As for the employees themselves, they are in fact disadvantaged in "large data recruitment". Because after all, such data collection is very analysis is "one-way" communication, enterprises to determine whether to hire individuals, the information collected does not necessarily give the individual feedback. As a result, you don't know exactly what kind of information the company collects or what the data is used after the recruitment process. The boundaries between analysis and monitoring are also very vague.

(Responsible editor: Fumingli)