Large data predicts start-up success and employee performance

"If used properly, big data will not only predict the success of startups, but also predict which employees will stay to create results," Kess Tigsen Thygesen, co-founder and product director of Rolepoint, the online social-networking platform, said in a recent article on the TheNextWeb website.

The following are the main contents of the article:

Big Data, you've heard it, you've seen it. Perhaps you are developing large data tools. Whether you use it or not, large data has the strength to help you analyze it with a higher degree of accuracy. But can big data predict the success of your start-up? More specifically, can you predict your employees and their performance in the development of your company? Of course.

Big companies such as Xerox have used big data to cut their numbers by half, while using cognitive and personal-skills tests to hire the best talent for the company. Xerox's recruiting team also looked at factors unrelated to the actual job description, looking for the relationship between employee retention and interaction. Big data helped them do it.

Well, there's no reason why your start-up, no matter what stage of development, can not emulate the success of Xerox and other companies in recruiting strategies. This is some way you can take.

Using Better filtering tools

If you can sift through the candidates before taking action, you will perform better during the foreseeable period. For example, it is hard to say that a person who used to change jobs is naturally a bad worker. In fact, http://www.aliyun.com/zixun/aggregation/13569.html "> Large data studies have found that people who frequently change jobs do not necessarily perform better or worse than those who work long hours in a fixed unit."

Instead, you should use tools to screen candidates based on the most important features of your startup. A small company called Evolv in San Francisco has developed tests that show how a potential employee can match a company based on predetermined factors.

For example, retail sales candidates need to be tested with decision making, spatial positioning and persuasion, and customer service personnel need to be tested with goodwill and relationship-building capabilities that result in better recruitment, performance evaluation and overall management.

Accept Social

As a small company, you may not have the resources to pay for expensive tests and evaluations, and you can use social networking at this time.

Apparently, today's job seekers are almost everywhere on every social networking site. Although social networking sites used to be seen as a distraction, social platforms can provide a treasure chest of big data, such as how candidates communicate online and what they like to share.

Don't think you're alone. Many small companies are using platforms such as Entelo to get data on social networking sites such as Facebook, Google +, LinkedIn and Twitter. These so-called "talent search engines" help your startup to find the right candidate based on factors that are important to you, and this has proven to work.

This is another typical example: Research shows that happy employees are more likely to interact at work. If you find candidates who publish positive emotions in social data, especially in the workplace, this sentiment can be brought to your company after hiring.

Supplement your referral plan

Although the evaluation and personality tests are good, they are still not the number one recruitment and retention channels, ranking first is the staff recommendation. In fact, the retention rate of the recommended staff reached 46% after one year, and the retention rate remained as high as 45% after two years.

However, when large data is combined with a recommendation plan, there is an infinite possibility. For example, our company found that on the LinkedIn site, a user who was considering a job change would update his or her profile, find and add new referrals, increase their contact with recruiters, and focus on more companies.

Large data show that the more active social networking sites are, the more likely users are to receive referral information.

This is another typical example: If you start a social map of your company and your employees and combine big data with employee referrals, you'll find the best channel to send targeted information and create opportunities. The average number of first-level contacts on large social networking sites is 630, so each company has a wide network of networking opportunities.

You can also track employee activity and response to information, and know which employees are more likely to participate in employee referral programs. By collecting these employee behaviors and results, you will find the most well-connected and active referrals.

These practices not only contribute to the success of the recommended projects, but also help you find out which employees will be the most powerful assets you can recommend for high quality start-up staff.

If used properly, large data will be a powerful predictor of success, both in terms of corporate success and which employees will retention and create results. Perhaps you have a start-up that is on the upswing, so don't overlook the long-term value of big data.

(Responsible editor: Meng)