Princeton’s Woodrow Search Uses Big Data Techniques, Motivational Assessments in Hiring
Photo: Bill Woodrow and Lisa Theodore spoke about Woodrow Search. Photo Credit: Courtesy Bill Woodrow and Lisa Theodore
Bill Woodrow and Lisa Theodore spoke about Woodrow Search. | Courtesy Bill Woodrow and Lisa Theodore

Back in June, Lisa Theodore and Bill Woodrow talked to NJTechWeekly.com about their startup, Woodrow Search, a Princeton-based company whose technology is highly effective at matching software engineers to jobs and company cultures.

The startup uses big data techniques and motivational assessments. “Big data has been used to match listings with skills for about 10 years,” said Woodrow. “Technologies to enable a hiring manager to determine if a candidate is a good fit with the job and with the company have also been around for about the same amount of time”

 “What is new is a combination of these two technologies in the same place for recruiting.” The company, which has been using these two technologies together for about 18 months, wants to productize this technology and scale it.

These technologies allow Woodrow Search to identify qualified candidates who are also good fits for a company — and to do it very fast. “People are hired for the long haul,” said Woodrow. The company claims that its turnover rate is virtually zero and that it guarantees its results.

The big data solution was developed by partner Alan Cooper, a software engineer and recruiter in Silicon Valley who has helped high tech companies hire software and hardware engineers. The next-generation motivational assessment technology was developed over a period of 40 years by a partner company in Brussels, Belgium.

Small companies and growing startups are especially vulnerable when mistakes are made during hiring, said Woodrow. Hiring people without the right skills just to fill slots can cause real problems, as can losing people because they aren’t the right fit. “The loss of one person can be a tremendous drag on the success and forward motion of a company,” he said.

The techniques used by Woodrow Search allow hiring managers to look at a wide selection of qualified candidates, Woodrow and Theodore noted. “We have a database of 3.2 million engineers…but, of course, skills aren’t enough,” Woodrow said. Hiring managers need to know if “they really fit in the specific job and company?” 

“Often what ends up in a recruiter’s lap is a set of requirements that can’t be filled at all,” Woodrow told us. Usually, a recruiter or HR department will list the opening on the Web and receive a thousand or many thousands of resumes.  Many of the candidates are unemployed, and thus actively looking for a position. Typically, the recruiter or HR department will then try to select resumes based on the job description through the use of word matching.

“This is like comparing a Jane Austin novel to the Bible. You are going to find a few of the same words. But does that determine that the candidate has the right skills? It is not unusual for a recruiter to list a job, receive a ton of results, and after much word matching, develop a pile of resumes with no acceptable candidates. This all could take four to six weeks,” said Woodrow.

In contrast, Woodrow Search begins the hiring process by working directly with the hiring manager to determine the specific skill-set needed for the job. Using its big data technology, Woodrow Search instantly identifies all the qualified candidates, matching the needed skills with those of candidates in its extensive database. “We then refine the job description in real time with the hiring manager,” Woodrow explained.

If too many skills are listed, there may be no qualified candidates. “So we will them ask them to narrow the required number of skills to the ‘must haves,’ eliminating the ‘like to haves.’ We repeat the process until we arrive at a sufficient number of qualified candidates for us to contact. At the same time, we’ll produce a ‘heat map’ showing the geographical location of all the candidates under consideration. So we determine at the front end of the search what is possible.”

Most engineering candidates in the Woodrow Search database are “passive candidates,” engineers who are currently employed. Companies can also use the heat maps identify qualified candidates in any geographical area to enable future staffing decisions, for example, if they are thinking of setting up a remote office where there is a concentration of qualified candidates.

Once the universe of qualified candidates is created, Woodrow Search deploys its Belgian partner’s next-generation motivational assessment technology. At the same time that Woodrow Search is refining the job description with the hiring manager, it is creating a behavioral “benchmark,” outlining the key characteristics of the job and the company, Woodrow told us.

After the hiring manager selects a number of candidates he would like to consider, these candidates spend 20 or 25 minutes responding to a survey questionnaire. Comparing the results of the survey to the behavioral benchmark helps the hiring manager assess how well each candidate will fit the job and the company culture. The results can also be used to structure interviews with the top-ranked candidates. This approach eschews the more commonly used personality tools, which Woodrow and Theodore say are not predictive of how the candidate will behave once on the job.

Woodrow Search uses linguistic technology that is relevant to how candidates will act on the job, Woodrow noted.  “This is so revealing. It has insights about how people interact with other people,” he said.

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