Analytics can keep you on top of your recruitment game – find out how
Your two brightest talents have quit, just a year into their jobs, citing dissatisfaction with their roles. It is not an unfamiliar scenario in today’s job market. Is there a smarter way to select talent that will also stay?
Enter Predictive Analytics, a data-driven approach to recruitment, where algorithms crunch information across varied metrics and recommend candidates who best “fit” your organisation – and this in far less time than it would take your recruitment team with more precise results.
That is not all. Take a closer look at what Predictive Analytics offers:
Predictive tools can develop a rich candidate pool
Maintaining a talent pool of passive candidates – workers who are not actively seeking jobs but could switch in the near future from their current positions – is a must-do for recruiters to respond quickly to hiring needs. Predictive tools crawl through vast amounts of data across diverse sources – social media activities, company newsletters, online profiles, etc. – to select candidates with the appropriate skills and attributes. Using this information, recruiters can direct their marketing strategies towards the most promising sources.
AI delivers highly accurate evaluations
An engaged and aspirational workforce is an organisation’s best asset – matching candidates to job roles however, always presents challenges. Here is how AI can help:
- Predictive tools analyse data on former and current employees to closely match candidate skills with job requirements.
- The technology provides these inputs way before a candidate is interviewed and assessed, shortlisting only well-matched individuals.
- Moreover, predictive tools can combine varied metrics to forecast a candidate’s future performance.
Altogether, for companies, the payoff is substantial in terms of saved costs, time and the resources that would have been required to conduct conventional recruitment exercises that are long drawn and less reliable.
Time-to-hire speeds up with predictive analysis
Time to hire – the period spanning initial contact with a candidate up to the time he/she accepts an offer – is an important metric in the hiring process that throws light on the efficacy of your recruitment strategies. Predictive analysis helps HR managers track the time spent in filling vacancies, spot delays and streamline the process, thereby tightening time to hire schedules.
Analytics help to boost retention rates
The time and resources spent by organisations to replace high-quality talent comes at a considerable cost. Vacant positions are also detrimental to productivity.
There is enough evidence to prove that most cases of employees quitting can be prevented. Predictive analytics can play a critical role here by closely matching a candidate’s skills and attributes to the available position. Selecting the “right” individual for the job promises greater satisfaction at work and hence, deeper engagement with the organisation.
More payoffs from using predictive tools to understand employee turnover:
-AI-generated analysis offers valuable insight into a worker’s average tenure with a company. A high turnover is a red flag indicating flaws in the company’s recruitment processes or deeper organisational fault lines such as unfair practices, poor office culture or falling company brand value.
-Predictive tools can also review employees’ attributes to (a) forecast who among them are likely to quit and (b) how their absence will affect the company’s bottom line.
Leverage the power of predictive technology
Predictive tools are only as good as the quality of your data. As you feed in more refined data as per the needs of your business on factors that make for reliable hires and take appropriate actions, the AI will “learn” to predict candidates’ attributes that make for successful recruitment.
Predictive tools can produce unexpected inputs. For instance, you may be surprised to learn that your best hires are not from the university you favour as a talent source. Such information can help you divert time and resources to other universities whose students are a better match for your organisation.
One crucial area where predictive modelling differs from older methods is that it allows for near complete objectivity in decision-making by eliminating human bias. Algorithmic processes, driven by data rather than individual hunches will consistently yield good results.
For organisations to ace the competition for high-quality talent, predictive analytics must become an integral aspect of their recruitment efforts. However, it takes experience, a deep understanding of the industry and overall recruitment landscape to successfully leverage the potential that lies locked in the enormous quantity of data that these tools provide. Tying up with an RPO vendor who meets these requirements is arguably the way forward.
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