Recruit Smarter: Embracing Data Analytics
‘Big Data’ is no longer a buzzword, but an important foundation of almost all industries, with organisations across a host of different sectors realising the value of gathering, analysing and utilising data to progress business.
According to IBM, we create 2.5 quintillion bytes of data every day – so much that 90% of the data in the world today has been created in the last 20 years. However, all this information is useless if it is not extracted and utilised for business benefit – something the HR department has been guilty of.
Traditionally, the recruitment process has been heavily reliant on human judgement, but we are now in an age where the amount of recruitment and employee information we can capture is rising exponentially. The most forward-thinking HR departments are finding ways to harness this data resource, realising the true value from the information available.
The industry is showing a trend effectively using data analytics tools to monitor those already working within the organisation to ensure their development, however, the benefits of using ‘big data’ during the recruitment process is yet to be fully realised.
Predetermination of “Quality of Hire”
Currently, organisations are seeing the value of monitoring and collecting data on employees, to ensure maximum retention. From day one, as employees progress, various statistics are recorded, ranging from targets achieved to time of service. HR departments can then use this data to ensure promotions occur at applicable times and to identify skills gaps, which can then be rectified through employee training. This helps in keeping employee engagement high and also adds in an element of objectivity in employee development.
Whilst focussing on development is crucial to employee retention, often employee turnover is still high. Why? Because ‘Quality of Hire’ is too focussed on post-hire. Although it was ranked as the number one most valuable recruiting metric globally, most “Quality of Hire” metrics are still predominantly being used to assess individuals once they are already on-board.
A recent study of 20,000 new call centre employees showed that almost half (46%) left the organisation in the first 18 months. The cost of turnover – when the costs of replacing the employee and the loss of productivity are included – is on average equivalent to three- to four-months of the typical employee’s pay.
While services like LinkedIn provide the technology to find potential applicants, companies are flooded with resumes, many which have come from unqualified or unsuitable candidates. Couple that with the possible 50 interactions with candidates every single day and the “Quality of Hire” can be lost. Hiring based on human judgement alone becomes less effective than a coin toss.
Organisations need to utilise the data analytics tools available to them to identify true talent and can be confident that those they hire are the best fit for the role.
Take Google for example, which built a hiring algorithm to predict a candidate’s probability for success if hired. They also developed a separate algorithm designed to support its initial screening of candidate resumes.
Google’s investment in this analytical approach is also carried into their application process. After much research, Google determined four interviews provided the maximum amount of insight into the prospective employee. As a result, Google has seen a low employee turnover while filling available roles quickly and effectively.
Assess for success
Through carrying out the right assessments of the employee during the recruitment stage, organisations can identify quality, best-fit applicants and recruit faster – whilst slashing employee turnover. Additionally, businesses and candidates can be truly confident they have both made the right decision.
These assessments will sort and benchmark potential candidates against top performers already doing the role within the organisation. For example, measuring a prospective employee’s competencies, including decision making qualities and business insight, alongside their past experiences, will give the businesses an overview the candidate’s core skills.
Whilst measuring the traits and drivers of a prospect, such as their natural aptitudes like confidence and assertiveness, as well as what motivates them, provides a company insight into the personality of the employee.
Often, organisations that screen hundreds of job applicants start with little or no indication as to the fit between applicant and the job position. By customising RPO assessments to the role in question, screeners can identify the fit score of each applicant and identify a shortlist of top candidates – filling openings more quickly and with confidence.
Additionally, if such screening assessments were fully integrated with not just applicant tracking software and internal employee performance data, the assessment would adjust its fit score over time to more closely resemble those applicants who were eventually hired, stayed in the job and got high marks for job performance, offering even more direction for recruiters when wanting to identify future top talent.
A successful example of this approach was when Xerox collected and analysed performance data on early hires. The company discovered that some assumptions it had been making about job recruits were incorrect. The assessments found candidates with experience in call centres or other relevant positions cost more, but they didn’t perform any better than those without previous experience. Additionally, workers who were active on up to four social networks were more likely to stay in their jobs.
It is important to note, that while companies might invest in new, innovative data analytics tools, they are not going to be completely effective if the data gathered is not digested and understood correctly.
Organisations will only realize the true benefits of data analytics if they consider the following:
- A clear understanding of how HR aligns with business objectives is essential – so decisions can be made in-line with the relevant metrics.
- A systematic approach must be taken, regardless of what metrics are employed – clients must ask why measure it, what value it provides and how much emphasis should be placed on the results.
- Creating a single integrated information system is key – data should exist within an online dashboard, presented in a way that is meaningful for decision making.
By utilizing the data available at the recruitment stage, HR departments that invest in the right tools with partners who can tap into this wealth of data can benefit from a highly streamlined talent management process, expecting a reduced employee turnover and higher retention rates.
Big data makes businesses smarter, whilst in the long run saving precious resources. It is time that recruiters embraced the capabilities of big data to ensure a 21st century approach to recruitment, only then can companies feel confident that they are truly finding the right people for the right jobs.
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