Who’s Seeking a Job Change: Using Artificial Intelligence to Predict What Workers Feel in Their Gut
The workforce is a finicky bunch. They bring talent and passion to their work; but studies show that many workers are constantly on the lookout for their next opportunity — even days after starting a new job. Still, whether they know it or not, these workers have vast differences in their actual readiness to make a move away from their current position.
Those differences are a big challenge for recruiters. An important competency for finding talent fast is understanding the pulse of their target workforce. What recruiter hasn’t wished to know which candidates in the talent pool are ready to jump ship? Unfortunately, that essential bit of information has been so elusive for recruiters.
A Common Scenario
Several studies show (including here, here, here) that roughly 3 out of 4 in the current workforce are actively looking for a new job or are open to new opportunities. That’s a significant number. So with all the job seekers, shouldn’t a recruiter’s task of finding good, talented people be an easy one?
Well, consider the example of one sourcing company looking to fill a marketer role. In their attempt to recruit with an outbound communication campaign to targeted candidates, they received only 1 positive response from the 60 sent. That’s frighteningly low. Many recruiters report similarly perplexing response rates. That begs the question of whether the high percentage of active job seekers is an accurate depiction of who is actually ready to change jobs.
With this seemingly conflicting data, how do recruiters sort through their prospects with confidence?
Entering Hearts and Minds
Fortunately, Brilent has introduced a tool to help recruiters with this problem. We do it with a unique feature that lets recruiters into the hearts and minds of some of the best talent available in the market. Here’s how it works.
In talent acquisition, it’s crucial to know whether a candidate is ready to leave a current job and look for new opportunities elsewhere. There are many factors that could impact someone’s decision, including:
- Relationship with manager(s)
- Growth of their career
- Growth of the company
- Salary and benefits
- Commute
- Local economy
- Growth of the industry
- Family issues
- Others
While it’s impossible to know candidates’ exact reason(s) without surveying them directly, there are clear patterns when looking at a large group in the same industry, region, or even the same company, with the same or similar titles. Brilent designed a simple and effective method to predict a candidate’s likelihood of changing jobs when compared to their peers in a similar role and same location.
Using a sophisticated methodology based on big data and artificial intelligence (AI) techniques, Brilent leverages millions of data points about specific jobs and relevant worker behaviors in those jobs. The resulting computations allow for making fairly accurate predictions about when a worker gains an itch to look for something new.
Brilent created five levels of availability in our analysis. The levels describe a candidate’s likelihood to change jobs in the next 90 days, and include: very likely; more likely; equal likely; less likely; and not likely.
In the table below, we see actual data representation of two different job functions from two widely different regions. Software engineers in the San Francisco area reach their peak of likelihood to seek a new job at the four-year mark; whereas account managers reach that peak much sooner after only two years.
Other factors are considered in the analysis, including a candidate’s job changing pattern and significant changes at their current job, such as major shifts in product strategies or stock option vesting schedules.
Brilent’s methodology provides significant analysis that includes data from more than 100 million resumes and job profiles. Therefore, recruiters searching for talent with a specific requirement — such as location — can have confidence that Brilent’s recommendations bring a high level of accuracy.
Real People, Real Impact
Predicting the likelihood of changing jobs is just part of what Brilent’s intelligent recommendation does. Imagine how these types of recommendations could have reshaped the candidate landscape for the sourcing company from our sample scenario. From the outset, the recruiters would choose from marketer candidates who met the job function-specific predictive requirements. They would then work with 60 candidates with a much higher likelihood of getting 20 or more positive responses. Now that’s smart recruiting. This type of result would signal immediate ROI recognized through greater recruiter efficiency.
The recruiting industry itself has a certain telltale attribute that makes this product feature particularly valuable. There is lots of turnover. In fact, somewhere between 60–70% of recruiters can be classified as junior level. That means that very few recruiters bring years of experience and the luxury of deep knowledge of an industry and the many job functions working in it. The Brilent product offers a unique snapshot into the rich and deep-seated idiosyncrasies of talent they are looking to find at breakneck speed — all at the click of a button.
