The talent acquisition challenges we saw at the beginning of the pandemic persist today, such as:
The hiring challenges above are only a few of many, and if you boil it down, everything comes down to Talent Quality. Do you know that the contingent workforce has significantly expanded since the post-pandemic crisis? As per the study by Coupa, leading organizations have increased their investment in the contingent workforce by 22.8%.
When recruiters face competitive job offers, picky candidates, high volumes of job openings to fill, and demanding clients, the notion of Talent Quality takes a back seat. Instead, quality and candidates should go hand in hand. Everybody knows the cost of a bad hire.
On this point contingent staffing experts and leaders, Praneeth Patlola, Lindsay Freedman, Satish Kumar, and Vik Karla share their thoughts and ideas on addressing today’s talent acquisition challenges.
Satish Kumar:Talent quality is the ability of the candidate to do the job with satisfactory output. This baseline has two components: Hard skills or job role and human traits or cultural fit. Both of them deal with different dynamics or success criteria.
While hard skills are more prone to automation, human traits are not so explicit. That’s why we can find only a few high-performing individuals or teams in a company. Also, the benchmark for talent quality varies across organizations.
Vik Kalra: Tactically, talent quality refers to the accuracy of talent match against the job description our client has provided. Also, it depends on the hiring manager to decide the level of alignment or the objective positioning of the candidate.
Lindsey Freedman: Talent quality is subjective. It depends on different departments and how they define and measure it.
Satish Kumar: Any talent measuring metric has to be scientific, objective, standardized, and repeatable. Only then does the yardstick for measuring talent quality become meaningful. The typical measurement mechanisms for talent quality are screening bots, automated assessments, and live interviews. Also, the hiring funnel covers the entire engagement module from bot conversation to live human interaction (for remote hiring). In some cases, we can also derive talent quality through certifications.
So, assessments data helps us create a benchmark and define the stack ranking. Conversely, measurement dynamics are entirely different for soft skills as they differ across organizations.
Vik Kalra: From a vendor’s viewpoint, we measure talent and skills through the lens of speed, quality, price, compliances, and coverage and data points like external summits, shortlisted interviews, offers, stats, premature termination, and successful project completion when it comes to contingency talent quality. However, quantifying all checkpoints is not always preferable as output and interpretation could be wrong. So, from an assessment perspective, we consider ‘interview-to-offer’ ratio, as a benchmark.
Glider’s products like objective assessments have helped us increase our interview-to-hire ratio by 80%
Lindsey Freedman: We can measure only what we can see. So, technology gives great visibility to your workforce in terms of both pre-qualification and post-hire metrics. For example, historical data about your past employees helps you decide about future hiring decisions because it tells you a lot about talent quality.
Vik Kalra: Perception of talent quality differs everywhere. Undisputedly, a hiring manager always has the authority to take talent quality decisions, followed by what a recruiter does. So, it’s always a good idea to consider what a hiring manager wants and use it as a baseline for workflow design. Also, individual bias influences shortlisting decisions. Inefficiencies like these can be addressed if recruiters and hiring managers interact over talent market and quality parameters.
Satish Kumar: There are multiple touchpoints (challenges) between a recruiter and hiring managers. So, we need data-driven technologies like design-thinking which can fulfill the hiring manager’s expectations about talent quality. Systems like Glider AI consider opinions from MSPs, suppliers, and other participants to articulate their expectations. It enables transparency, a sense of ownership, and responsibility towards ensuring candidate quality.
Lindsey Freedman: Talent quality also extends to the external workforce who are tied to projects, assignments, and their statement of work. Holistically, it’s also about the quality of work received. Unfortunately, many companies lack data here.
Lindsey Freedman: Most companies look at a match between a candidate’s resume and the job description. Credentials help you get interviews, but resumes do matter. Also, we need to look at the ‘cultural fitment’, the human element. So, we need to balance technological and human assessments.
Vik Kalra: In the contingent labor industry, we should do a sprint that is time-boxed to one week. Let the hiring manager interview the candidates, limiting only one candidate submission per supplier. Reiterate this sprint, if the first candidate fails to perform, then we must recalibrate the requirement and reeducate the various actors in the supply chain and go for the second sprint. Through this, we can minimize the wasted efforts in the talent pipeline.
Satish Kumar: Many large organizations have dropped even the college degree requirements today. The current digital world is full of people who are driven to perform and upskill almost every day. So, the notion of providing an opportunity for competent talent needs to be inculcated in every type of industry. But hiring must be fair and accessible at both ends considering the great resignation trend. This way we can reduce the interview tax.
Vik Kalra: Recruiters need to be transactional in nature, only then can they influence the candidate to take the test. For example, we need to come up with micro assessments that are portable and mobile-friendly for candidates in senior management.
Satish Kumar: Yes, there are constraints like old assessment processes, but we ask our MSP partners to uphold the ‘human element’ in the assessment processes. We should add it as a part of the communication channel and assist the candidates in upskilling and reskilling, etc., irrespective of the community the candidate is coming from.
Lindsey Freedman: No amount of technology can ever eliminate unconscious bias when hiring. But organizations that have clear DE&I goals, contingency programs, and KPIs combat hiring bias efficiently. It helps find the best talent.
Vik Kalra: DE&I is still in the infancy stage. There’s a lot of work that needs to be done. But objective and data-driven assessments will come to the rescue.
Satish Kumar: Data helps in talent optimization. We have to be mindful of the candidate elimination criteria at the top of the funnel. Data also helps to look at the diversity aspect in the talent pipeline. Therefore, at Glider AI, we present only the competency data to the hiring manager barring the candidate’s details.