Feature |

The Path of Most Resistance

Choosing Candidates with Nonlinear Job Histories

For most of the 20th century, employees could work in the same industry throughout their entire adult life. Today, fewer people stay at the same job or even in the same field. There are a number of trends driving this: Job-hopping is a quicker path to higher pay, the “wanderlust” of Millennials (employees up to the age of 35) who embrace change and new opportunity, and the emerging “gig economy.” By 2020, 40% of American workers will be independent contractors, according to “Freelancing in America,” a report by Upwork and Freelancers Union that measured the independent workforce.

This new reality poses two difficult challenges for recruiters: how to efficiently and reliably find talent among a widening pool of people with nonlinear career paths, and once found, how to retain them, particularly as newer, shinier and better-paying opportunities continuously beckon. As these trends continue, the challenges will become ever steeper.

On traditional career paths, a recruiter could glance at a résumé and readily determine how that candidate’s experience aligned with the position. Typically, the candidate came from the same or a closely related industry (e.g., advertising and publishing or manufacturing and construction) and held a position with a clearly defined set of skills that roughly paralleled those required for the available job. Linear progression up the corporate ladder or ever-increasingly important assignments were relied upon as a sign of successful professional ability-generated growth. Today, people move in and out of jobs in completely unrelated industries, which makes it harder for the recruiter to match work experience(s), let alone performance and motivational factors, to the available position.

Take, for example, the case of a talented high school English teacher who is looking to leave the classroom for a sales or marketing position in the private sector. A recruiter inundated with résumés is likely to skip over the teacher, as will any applicant tracking system that “parses” résumés — notwithstanding that the skills honed over years of classroom instruction may very well make the applicant a highly successful salesperson or marketer with good listening and presentation skills. This is just one of many examples of highly skilled, temperamentally well-suited candidates who are routinely overlooked because their “narrative” doesn’t line up. Discovering, hiring and retaining people from nonlinear backgrounds requires a nontraditional approach.

The Shortcomings of Traditional Approaches

Conventional solutions have certainly made it easier to sort through candidates by using “filtering” technology as a screening tool. However, filters have proven to be inefficient and ineffective since many qualified candidates are “screened out” when résumé keyword searches and parsing don’t turn up any matches, or unrelated matches, to the job description. Conceptual matching and intelligent searching have taken résumé parsing to another level — however, this methodology also has some significant drawbacks and inherent problems. In short, intelligent searching matches conceptual and contextual information from a candidate’s source document (such as, a résumé or application) to another document (i.e., a requisition or job description). The result is a list indicating which candidates present the closest match by percentage.

The first drawback is that the results are based on the accuracy and content (or lack an important keyword) of the candidate’s source document — i.e., résumés, which are subjective and prone to misrepresentation. Second, a hiring manager will still need to review the results to determine whether there really are any matches. Third, when it comes to assessing work styles, character, culture fit, and dependability, hiring managers are more likely to rely on human interaction (that is, a face-to-face meeting) and intuition.

Another shortcoming inherent in most conventional assessment models is their overly narrow focus on the required skills for minimaljob performance. This may attract people who, on the surface, would appear to be good candidates and well-suited to the position. But how many hires who appear wellsuited don’t pan out owing to a variety of cultural and work-style issues — perhaps they’re temperamentally ill-equipped to handle a more entrepreneurial environment or they find a more formal corporate structure constraining?

These drawbacks are further compounded when confronted with applicants with nonlinear job histories. To elaborate on the scenario presented in the introduction, imagine the following: A position for a regional sales representative is open. Candidate A holds a marketing degree and lists several sales positions in the employment history. Candidate B holds an English degree and has spent a career in education, first as a teacher and later as an administrator. Candidate B will likely be screened out as an unqualified applicant for not meeting any overt requirements for the job. However, if Candidate B were allowed to proceed to a simulated assessment, the employer would discover that the candidate has excellent negotiation, listening, and people skills, which were honed from hands-on and managerial experience.

Variations on this scenario are repeated time and time again — the lawyer who spent time at the firm training clients and colleagues and now wants to become a corporate trainer, or the bank teller looking for a support position in a software company; there are countless examples of seemingly diverse candidates who may possess the skills, behaviors, and culture fit to succeed in the job and, equally important, within the organization, who are automatically disqualified. Of course, candidates coming from other fields would stand little chance of making it to the next stage if they came through a conventional screening system.

The Solution

Simply matching a candidate’s self-reported skills to those listed in the job description is clearly not going to cut it when many of the best people have backgrounds, skills and passions that are not visible on the surface.

What if, instead, you could whisk any person interested in employment with your company through a complete, unattended interview with job-specific direct questioning, assessments and real-time simulations? What if this vetting process looked at the whole person, not just their education and prior work history, and you could screen in candidates by looking at multiple data points that addressed/ interpreted an applicant’s experience, skill set and behavioral characteristics — all matched against objectively determined indicators of top performance within your organization? This would surely give organizations a far better ability to find better hires among the rising tide of applicants with nonlinear job histories.

Simply matching a candidate’s self-reported skills to those listed in the job description is clearly not going to cut it when many of the best people have backgrounds, skills and passions that are not visible on the surface.

Engaging candidates in revealing, real-time interactions that address attitudes, competencies and skills enables hiring managers to objectively find the employees who are most likely to perform best within their business culture. Each candidate is rigorously assessed and rank-ordered as an individual. The objective is to facilitate more in-depth, meaningful and revealing candidate interactions while at the same time reducing staff workload — systemically delivering top candidates at the point where the hiring manager’s expertise is most valuable: when it’s time to make the final hiring decision.

Considering the increasing number of candidates with nonlinear career narratives, a top performer can fall between the cracks using conventional screening methodologies.

The increasing sophistication and more widespread application of artificial intelligence promises to make these processes and interactions more refined. The “questioning engine” that has long powered our candidate assessment platform has evolved from using “branching logic” for more realistic candidate interactions, to using AI for more revealing candidate interactions and more responsive intelligent process automation. An AI-driven real-time assessment can find patterns in anyone’s work history, no matter how nonlinear: core skills (teaching skills = presentation skills), dedication (learning new skills) and adaptability (looking to go into another field). It also can submit candidates to real-time assessments on character and ethics. All of this provides employers with a robust, fully automated assessment and hiring platform that is both predictive of job success and longevity.

Rewarding Candidates with Nonlinear Career Narratives

Some have started referring to “discovery-driven candidates” — people with backgrounds that don’t follow more traditional career trajectories. According to management consultant Whitney Johnson in a recent TLNT article, “These are dedicated individuals who pursue passion instead of a title, adapt quickly when things don’t go as planned and make the most out of opportunities. Instead, look for signs that candidates have made the most of the responsibilities they’ve had, and used them as opportunities to learn and grow — it’s a marker of a devoted and determined hard worker.” (“Your Next Best Hire Could Be a Discovery-Driven Candidate.”)

The work of staffing specialists has traditionally centered on a process of screening out applicants by focusing on what they ostensibly can’t do or what skills they don’t possess (or rather didn’t enumerate in their résumé) in order to get the pile of résumés down to a manageable number for manual decisioning and processing. As previously discussed, these determinations are inherently “skewed.” Moreover, such a system has minimal ability to flag false negatives, where someone who would otherwise have been a success on the job is summarily rejected. The weeding-out process results in a candidate pool of those who “might” be successful. On the other hand, a system based on screening in and identifying candidates who can demonstrate relevant skills and the right temperament in a real-time engagement has proven to be more predictive of job performance and success in a particular work environment.

Considering the increasing number of candidates with nonlinear career narratives, a top performer can fall between the cracks using conventional screening methodologies. Conventional approaches too often reward the candidates who look better “on paper.” Providing candidates with an interactive, realistic experience gives them the ability to demonstrate their readiness and potential to succeed, and gives employers a complete, 360-degree candidate snapshot that provides solid indicators of potential performance and the likelihood of longer-term success within the organization.

Ron Selewach Ron Selewach is the CEO of HRMC Inc.

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