How talent measurement will evolve
Today, the Fourth Industrial Revolution – or what some call the Exponential Age – means that society is facing unprecedented rates of technological progress. The labor market is also already experiencing monumental changes, providing an abundance of opportunities for companies and candidates. But companies are still struggling to find the right talent with traditional recruiting methods.
Traditionally, a job was not just a source of income, but where many got their sense of community and purpose. These social contracts were crucial in the employer-employee relationship. However, fully remote and hybrid work has become more popular over the past two years, and Statista estimates that, by 2027, about half of the US population will have engaged in the gig economy, driving unbundling of work. Essentially, individuals are starting to turn to other non-work related communities, both online and offline, to share with people who have common interests.
In this new normal, companies will have to change the way they employ people and distribute work. With 57% of companies currently lacking the data they need to make talent decisions, here are three trends they need to watch out for in the world of recruiting and measuring next-gen talent.
Everything is about to go faster
In 2022, the job jump will not just be a trend; he is encouraged in the midst of the Great Resignation. This means that tenures will start to get shorter and shorter. As everything from sourcing to performance measurement becomes more digitized, employers will also be able to onboard and exit talent more efficiently.
However, all of these fast turnaround times will also put pressure on hiring managers and recruiters to screen people regularly – and virtually – especially as more candidates find themselves in physical locations or different time zones.
If you look at traditional hiring management systems, they often rely on tracking and reporting on hiring processes; they create the position, source candidates through internal hires, referrals, and word-of-mouth, and fill a position over a three-week to three-month period. But due to shorter terms, there is no time for lengthy recruitment processes. Tracking and reporting over long periods of time is now less critical as companies need expert talent immediately.
Finding talent and making hiring decisions in this fast-paced environment will only be made easier with access to plenty of data points and artificial intelligence (AI). Onboarding, especially for site workers, must also take place seamlessly. There are already platforms, like Turing, that use an AI-backed Intelligent Talent Cloud to find, verify, match, onboard and manage software developers remotely.
From sourcing to interviewing to onboarding, this is where the world of recruitment is heading – and it will move faster than you can say human resources.
A focus on enhanced conversations between candidate and employer
The majority of traditional recruiting management systems focus on tracking and reporting instead of facilitating conversations between employer and candidate, especially since all of these interactions used to happen in person.
Now, with everything digitized, the need is mainly to orchestrate communication via messengers, chatbots, audio and video – all essential for data collection for recruitment campaigns and assessment specifies talent. An effective candidate-employer conversation in a digital environment will become one of the main goals of recruitment management platforms over the next few years.
There are parallels to this trend in several other areas. For example, changes are also happening within sales, which has always shared similarities with the recruiting space. It used to be that sales was all about tracking and managing the sales funnel, but now the focus is on managing customer interactions. For example, take gong.ai, which analyzes customer interactions via phone, email and web conferencing to deliver insights any sales team needs to close more deals.
No matter what industry you work in, you don’t want to have ten candidate interactions. Where clients. Lengthy processes lead to disadvantages and, in the world of recruitment, the loss of the most suitable candidates. Companies that feel pressure to speed up their recruiting processes will want to learn how to understand candidates and make quick decisions with fewer interactions or touchpoints.
This is where AI helps with interviews and assessments, improving the quality of conversations between candidate and employer, and providing additional insights. HR managers can already receive objective textual and video analysis of video interview subtext or written responses to interview questions through natural language processing (NLP) and psycholinguistic analysis capabilities based on established patterns and intrinsic values. Meanwhile, a human interviewer may have a limited understanding of soft skills, cultural fit, behavioral fit, or learnability.
Moving away from self-reported data
In the exponential age, recruiters may worry about making quick decisions from fewer candidate interviews, especially if that person will only be with the company for six months.
The problem is that today’s recruiting and talent measurement processes still rely on self-reported data or what respondents say about their experience. Therefore, HR managers and recruiters often feel the need to go through several stages and examine different aspects of the candidate’s ability and character to ensure that they are the right person for the job and that they are the right person for the job. he has the skills he claims.
But to check all this information and make decisions faster, you need a trustless environment, made possible by technologies like blockchain, which could verify everything the candidate says at face value. These mechanisms will begin to become mainstream because they allow all parts of the system to reach consensus on canonical truth without relying on a third party to authenticate a person’s LinkedIn profile.
Traditional recruitment management systems do not allow this because they are designed to receive self-reported information.
It can also be taken further. With the individual’s consent, their AI-powered interviews with specific companies could be made available on untrusted platforms. Why is it beneficial? Well, if two companies work in the same industry and are hiring for a similar position, they could share digital recordings of their reviews.
A candidate who interviewed with Company A, but did not join because the company did not make an offer or their salary expectations did not match, could store the interview as a recording verifiable without trust on the blockchain. With a profile available on the channel, that particular candidate might have records of multiple parties who have reviewed their work or have reviewed them in the past. Instead of repeat interviews, Company B could hire this candidate based on this information – which, to add, is not self-reported.
However, if company A has done an initial interview, company B should only consider its ideas valid until three to six months later, and both the employer and the candidate should be open to sharing this information in an independent environment.
Company B must also have deep confidence in Company A’s assessments, which could be made possible by standardizing what constitutes a good quality interview. To start, a checklist for moving to standardization would look like: a specific list of topics covered, open-ended questions, surveys included, and an overview of the corresponding skills.
Similar concepts already exist. For example, Braintrust is a blockchain-based system orchestrated by software companies that eliminates the middleman from online recruitment sites. The blockchain verifies everything rather than relying on a third party. In two to three years, it will be a recruiting reality.
The world of work is constantly changing, with flexible and hybrid opportunities, work unbundling and shorter employment durations. Ease of candidate discovery already exists to some extent thanks to LinkedIn and innovative job boards. However, talent measurement processes are not yet fast enough to meet changing demands. Organizations that will thrive and survive will figure out how to hire quickly and deliver a 100% digital experience. And keep in mind that those now joining the workforce, like Gen Z, expect instant gratification and are comfortable in the virtual world.