Copy Xerox’s data analysis model for hiring success

By Chris Hebert, TechnologyAdvice

Hiring people is about people, right? That may be true, but, in a sense, when you are hiring many people in a relatively short span of time, each of those people starts to look a lot like a data point.

Admit it, you already collect data on all your hires and applicants, such as their education level, past experience, and maybe even personality types. If you were to compare this data to each person’s success in your workplace, you’d be able to better understand what factors help determine whether or not someone is a good fit for the position you’re filling. Some of those factors are bound to correlate, and the first step to acting on that information is to identify it.

This type of analysis may seem possible only for large corporations with huge hiring budgets, but small businesses can tap into the same power as well. With the rise in SaaS business intelligence programs, pricing is far less of an obstacle than ever before, and there are often no up-front costs to starting a small to medium data analysis project.

If you’re a small business, recruiting analysis is primarily for the purpose of improving your hiring process.

This is done by implementing (or perhaps creating) a model for acquiring and selecting applicants, then statistically measuring the success of each step of the model. For starters, if the conversion rate from applicant to job offer is so low it fails to produce enough new hires, or places too much work on HR, then you’ll want to adjust how you market the position to capture more qualified applicants and fewer duds. Are the best applicants seeing your job posting on LinkedIn or through an industry-specific job-board?

Once the right people are dropping into your funnel, you can continue to analyze conversion data from each of the stages (application to phone interview, phone to in-person, etc.) to increase the quality of your methods. Try keeping track of who performed the interviews, which questions were asked, and even collecting feedback about the interview process. This data on people you hire as well as people you reject can all be used to key in on the aspects of your interviews that were most efficient at identifying qualified applicants (as well as ensuring the process is a comfortable experience for everyone involved).

Large businesses have far more to explore in the realm of HR data analytics. Collecting data about sales performance, employee retention, leadership development, and accident claims allows a company to find correlations between ideal employees and certain metrics on personality tests and questionnaires.

Xerox Corp. implemented data analysis in the hiring process in hopes of saving money on training, which cost them $5,000 per employee. With the help of sophisticated sophisticated business intelligence software, premature attrition rates fell by a fifth among 2,000 employees during a six month trial, and Xerox has since applied the techniques to all of its 50,000 call-centre positions.

The centrepiece Xerox’s effort identified correlations between efficient, long-term employees and their scores on personality tests. When Xerox found a score or personality trait indicative of a good employee, they focused their hiring efforts on applicants with similar scores. Their results indicated that individuals with reliable transportation, moderate participation in social networks, and creative rather than inquisitive personalities are more likely to keep their job long enough to make up for the cost of training. Xerox was particularly surprised to find that applicants with previous experience in call centres performed no better than those without.

Although this may sound robotic, the process is remarkably similar to current HR practices. Just as an interviewer seeks to verify if someone will fit the company culture, such hiring software helps determine the likelihood of success, based on a person’s answers. You may observe naturally that few of the individuals applying meet your requirements, but crunching the numbers would tell you exactly how few and whether or not your method changes have been effective.

We’re a long way away from taking the H out of HR. However, increasing the R at the H’s disposal is enough to improve the hiring process.

Michael Cayley
Michael Cayley
Having attracted over US$50-million in investment and closed over $21-million in pre-launch sales for startups in China, the USA and domestically, Michael is living the struggle of the self-funded, pre-revenue Founder in Canada. He understands the pace of global innovation. He founded & funded the Ontario Cross-border Technology Innovation Ecosystem (OCTIE) study and he designed and taught the first, post graduate level, social media course in a full time program in Canada: crowdsourcing over 100 global experts as mentors. Cayley is the Founder of Cdling Capital Services Inc. (pronounced "seedling") a ratings agency that measures risk and builds trust between Founders, Investors and Experts in the era of low cost, globally funded startups and he is the Founder & Director of Startup Grind Toronto.

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