Typically, when a vacancy occurs in an organization, the job posting is advertised in the newspaper or job search portals where job seekers submit their virtual resumes. Keyword searches are used to sort through resumes to identify potential candidates who are then invited for in-person interviews. Sometimes this process yields a proficient employee who makes a positive impact on the organization. Also sometimes, this process yields a poor performer and the process has to be repeated once again to find the right candidate. If this all-too-familiar method is still the norm in your organization, then the HR is not only missing the opportunity to streamline and make the talent acquisition (TA) process more efficient, but also to influence and improve the outcome. The HR is beyond the capability to actually make a difference to the overall business of the company, more so at the strategic level.
HR departments are teeming with candidate data. From contact information to recruiter's notes, conventional ATS/HRIS/HRMS contain hundreds to thousands of such records. The question is: how effectively is this data being used by the TA professional?
A typical ATS/HRIS/HRMS system allows recruiters to search for suitable profiles based on keywords relevant to vacant job descriptions. The better maintained the resume database is and the more familiar a recruiter is with the details of the vacant job’s role, the better the system is expected to search. However, if a particular keyword is not used in the search or if a candidate’s skills are not properly mentioned in the resume, then qualified candidates get missed and unsuitable candidates might get chosen. This happens on a routine basis and much of the recruiter time, effort and cost is lost in this process.
The fundamental problem here is that resumes and job descriptions are unstructured by nature. i.e., they are not comprised of details which could be stored in traditional rows and columns data formats. Hence, how could machines ever understand skill proficiencies and candidate strengths correctly? All conventional systems have this major limitation.
Contextual technology brings ‘human-like intelligence’ to how talent data is searched, understood, comprehended and processed, thus making real meaning out of otherwise scattered and vague unstructured data. It is an advanced form of computing that goes beyond a mere keyword search.
Thus, a more suitable candidate who lists his/her skills and qualification using different terminology gets noticed. Results are fetched based on the ‘meaning’ of data rather than exact matches of input search terms. Gone are the days when qualified candidates would get overlooked because the resume database is not updated or the recruiter is unfamiliar with the exact job requirement.
Contextual intelligence technology saves recruiter time, effort and costs. It helps hire the right candidates and streamlines the talent acquisition process making it smarter, efficient and more accommodative to the evolving needs of organizations and the fast-paced environment.
Contextual technology is the way of the future without which the HR function will lag behind.
Two important measurable benefits emerge as a result of using contextual intelligence in recruitment.
Using contextual search intelligence in HR has proven to result in 50% time saving for recruiters, 42% savings in costs and 70% increase in selection-to-hire ratio.
Subsequently, for the organization as a whole, contextual technology can help achieve 9% increase in revenue and 7% increase in cost savings.
While the above are measurable and auditable benefits below are the intangibles.
The talent pool is better in quality. Time-to-hire is shortened, giving organizations less understaffed operational time.
A host of actionable insights could be deduced from talent data analytics. Using the candidate resume pool for effective skill deployment; identifying passive job seekers as good fits for future vacancies and engaging them; mentoring potential candidates for leadership roles; identifying skill gaps and developing appropriate L&D programs instead of running routine modules.
CHROs can contribute to company strategy by helping determine critical investments in talent vis-à-vis company goals with insights derived from contextual analytics. Contextual technology enables CHROs to help impact the overall company bottom line making HR an important part of strategic decisions.
Data is meaningful only when it can be interpreted and applied meaningfully to achieve measurable results. The question is no longer whether an organization should adopt contextual technology? But how quickly can it do so. In today’s digital age, HR is expected to be at the forefront. Contextual search & intelligence technology is the enabler.