Large Data Transformation online recruitment, headhunting value

Since 2012 on the line just over 2 years to get 100 million U.S. dollars financing of today's headlines, through the data analysis different user's preference to news, and then to push the mode of the model news to almost angered the whole traditional media circle; the recently successful listing of Wanda Group was announced jointly with Baidu and Tencent in September this year to establish Wanda Electric Attempts to rely on Baidu, Tencent's underlying database and membership system advantages against the electric dealers Ali ...

"Big Data" is playing an increasingly important role in the entire business world.

The big data gained by the heat is a harbinger of a commercial war that will evolve into a data war. Who gets the largest and most valuable data, who will win the entire Internet future. Just as mobile internet starts from platform-level applications to vertical, large data potential will also be released from platform-level enterprises to more vertical segments. Online recruitment, Internet healthcare, online education, O2O, these vertical areas have the most intuitive needs for "big data". Let's talk a little more about how big data changes the online recruiting field.

Online recruitment 1.0, data thick times

China's online recruiting market dates back nearly 20 years. Personal users upload resumes to the recruitment site, enterprise users in the vast number of personal resumes to search for their own talent, the labor supply and demand side for the first time through the Internet docking, online recruitment market ushered in the outbreak period.

Let's look at some of the features of the online recruitment 1.0 era:

1. Massive data

Online Recruitment 1.0 era is in the "Information network" of the huge dividend period. Players in the Zhaopin, Chinahr and other industries do not have to pay a great price to obtain a large number of user resumes, and to attract the assets, docking more recruiters, headhunters. When the Zhaopin was listed on the NYSE at $700 million a year ago, its registered users had reached 77 million and the database had approximately 60 million complete resumes. The intelligence-linked job-seekers ' data have led them to take a leading position in the online recruitment 1.0 era.

2, data structure, standardization

The recruitment site at this stage has highly structured job-seekers data, including CV presentation, career type, industry, etc., but real-life practitioners may be more sophisticated in their industry or career types. With the rise of internet technology, a growing number of emerging industries, recruitment sites even with multiple data attributes can not clearly define user capabilities and experience.

3, the data brings the resume bombing and recruiting inefficient

As more and more enterprises and job seekers are flocking to the network, their shortcomings are becoming more and more obvious. Because the cost of the job seekers to send resumes is too low to cause "resume bombing" and personal information fraud serious phenomenon, let enterprise hr face more and more wide "resume ocean", miserable.

"We wanted a sniper, but the recruiting site brought us a tank," he said. Enterprise and the candidate's information asymmetry, resulting in the recruitment site "Misfits spectrum", the traditional recruitment site short board began to reveal the clue, no longer meet the number of talents and quality needs of the growing enterprise HR or headhunting.

Social recruitment: the competition between the three-dimensional world and the two-dimensional world

With Facebook and Twitter's social storms sweeping the world, the proposition of big data mining is constantly stimulating the nerves of the public. And in China on the other side of the ocean, big data has begun to go deep into the vertical areas of film, music, networking and so on, in the vertical field of recruiting, the application of large data is also benefiting many job seekers and employers brand.

Online Recruitment 2.0 times, recruitment behavior into more social attributes, social recruitment sites gradually become the mainstream recruitment industry tools. Compared with the flat mass data of traditional recruiting websites, more and more levels of data content can be mined on social recruiting platform: User basic data, user behavior data, and interactive data of users on social platform.

Online Recruitment 2.0 times the important value of user interaction data has been excavated and mastered, through the construction of data analysis model, the integration of professional network behavior habits and social network data, can form its more accurate stereo user portrait. If the big data mining of the 1.0 era is still in the two-dimensional world, the big data in the social recruitment era will bring the whole recruiting field into a refreshing three-dimensional world. Through the excavation of user social behavior data, the enterprise in the recruitment effect of a full upgrade to a level.

Take the world's largest social networking site, LinkedIn, for example – on LinkedIn, individual users can create resumes, focus on company job information, build contacts, fill out personal skills, and share industry information. And the enterprise can set up the company homepage, purchase the pay product can publish the advertisement, search the file of the whole station user and contact with it.

When users build relationships and share information, they also pass on the business circles they belong to and their values. Enterprises in the creation of the home page, but also in the establishment of the employer brand image, to establish job seekers confidence. The image of both sides is more stereoscopic, figurative and emotional.

"What is the trend of the next 5-10 years to determine the most important role in the development of the hiring industry," said the recent LinkedIn 2015 China recruitment trends Report? , 55% of HR proactively chose to "use ' big data ' to predict future talent needs," which is much higher than the global 27% level, indicating that the domestic HR department is aware of the importance of big data. Asked, "How is your company doing with the data to understand the efficiency and opportunity of recruiting?" , only 18% of respondents thought their company was doing well, below the global 24% level, reflecting the fact that the country's human resources department still did not take the data to optimize recruiting efficiency.

With the recruitment field into the three-dimensional world, we can see that the 2.0 era of online recruitment industry development presents some new features:

1, recruit the most suitable, not the most powerful

In the 1.0 era, companies hired more people to search by keyword based on resumes, a way to judge the values and social attributes of job seekers from more latitude. In the 2.0 era, due to the rich and stereoscopic data types, the new data algorithm can make employers and users more accurate matching.

Jed Dominguez, a 26-year-old in California, received an unexpected email one day and a San Francisco start-up company asked him to interview programmers. Dominguez, who was living in a rented house in a Californian city and living on credit cards, is learning to program. Dominguez in high school, and did not want to go to college. A man named Luca Massa. Dominguez is selected by a new data algorithm.

The idea of this new data algorithm is to get people to move away from the traditional talent index, for example, recruiters are generally interested in the Massachusetts Institute of Technology degree, Google company experience, colleagues or friends recommended, and put more attention on some simple concepts: how is this person's performance? What can this man do? Can you quantify it?

It is understood that this new algorithm from a data analysis company in the United States in the analysis of a person to deal with 300 or so major variables: frequently visited sites, language types used to describe various technologies, positive or negative, LinkedIn skills, what you've been involved in, how long you've worked, where you learned, What is the major of this school and what is the ranking of the university in the American News and World Report? It is the rich data that outlines a more stereoscopic portrait of the job seeker, making it more accurate for employers to match users.

2, "Big Data" to enhance the efficiency of labor force

In the summer of 2011, Manchester City assistant coach David Pratt decided to use data analysis to solve the team's performance problems. Pratt found that even though the team had several big and strong players, their corner scoring was unsatisfactory. After consulting the club's in-house data analyst, the team increased its use of inward-turning corners (the direction of the ball to the goalkeeper). The tactical shift has had an astonishing effect. Throughout the season, Manchester City have scored 15 goals with a corner and become the most efficient team in the Premier League, with 2/3 of the goals using an internal-rotation corner. This practice provides a strong support for data-driven decision making.

High-quality and efficient data analysis begins to show greater value in the tactics and decisions of the enterprise and the team.

Some of the leading technology companies, such as bat, Huawei and Lenovo, have started to use LinkedIn's data to help them make more business decisions. For example, by reading job seekers ' information, they can find out which areas have more potential employees and decide where to set up new offices or factories. In other words, what LinkedIn wants to change is not just the way it hires and jobs, but the efficiency of the entire labour market.

In the ideal state of Jeff Venard, the chief executive of LinkedIn, LinkedIn can map out a grand "economic map" based on the data. In particular, if LinkedIn can track the relationship between job seekers, companies and universities and map out the matching maps of jobs, qualifications and skills with employers ' requirements, it can progressively improve the flow of information in the labour market and create large data on the labour market.

Summary

Today, data acquisition is getting easier, but most companies are still working on the huge amount of data, how to better process and use it, to turn it into business opportunities and to enhance value. Professional social networking sites with in-depth knowledge and practice of large data, or will usher in an unexpected blowout period.