Continuing our series on recruitment, this week we are looking at Big Data. Big Data is revolutionising HR practices and recruitment methods. As online data analysis is becoming more and more widespread, Big Data makes it easier to recruit the right candidates, predict staff turnover and employ the most appropriate selection criteria. But Big Data also raises questions about automation of recruitment processes and about how candidates can invest in their personal branding.
Here is an example from the United States. Twenty-six year old Jade Dominguez, from South Pasadena in California, never went to university and taught himself how to program computers. Yet he was offered a programming job in a start-up based in San Francisco and has since been hired.
Someone, somewhere, up in the “cloud”, thought he was a bright lad. That person was Luca Bonmassar, the co-founder of the start-up Gild. He discovered Jade Dominguez thanks to technology that focuses less on traditional recruitment criteria (university degrees, recent experience etc.) and more on simple questions such as: is this person efficient? What can this person do? Can we assess this person’s work?
Gild’s algorithm, which uses information available on the internet, rated Jade Dominguez right at the top of its list of programmers. By using Big Data, a computer can collect all sorts of information to use in many different ways, particularly for recruitment purposes.
Big Data defined
So what is Big Data? The term is used a lot in the marketing business and refers to the capacity of very powerful algorithms to handle huge amounts of data and, more specifically, find correlations between them.
The human resources sector can use this sort of data in many different ways. One is for sourcing purposes, whereby suitable profiles are found online and ensure a targeted recruitment process. This method, which is slowly making inroads in United Kingdom, consists in a computer analysing resumes for keywords and skills and evaluating a candidate’s profile on social media. The aim is to determine whether a candidate fits the company’s requirements and business culture. It enables saving a precious time during the candidate’s recruitment process.
Thanks to Big Data, an American insurance company realised that certain criteria, such as the candidate’s school, were not at all pertinent when hiring sales staff. Instead they filtered candidates according to factors such as a previous experience in the property sector or within an organisation. This helped the insurance company turn its flagging sales revenue around.
By using cross analysis of certain criteria (salary, position in hierarchy, seniority etc.), Big Data can also help predict which employees are more likely to resign. Statistical analysis can help us determine what factors cause employees to leave a company. The printer manufacturer Xerox reduced its call centre staff turnover by 20% using such analysis.
Questions on Big Data
Although HR consultants are not particularly keen on using an arithmetic approach to human resources, and so remain reticent when it comes to using Big Data, increasing amounts of data available online and constantly improving technology are giving it a better image. Yet Big Data does raise some questions.
For example, as this type of recruitment becomes more popular, there may be a certain standardisation in the type of candidates selected because algorithms can search for profiles according to specific criteria. So what happens to diversity and the wide variety of human qualities required to make a winning team?
There is also a risk of discrimination. For example, a candidate who was not chosen for a position could claim that the selection was based on considerations which are not directly connected to the skills and qualities required for the job in question. In “The employment practices code” published by the Information Commissioner’s Office (ICO) in November 2011, the article 1.4.2 mentions the need to “Inform applicants if an automated short-listing system will be used as the sole basis of making a decision. Make provisions to consider representations from applicants about this and to take these into account before making the final decision.”
Access to digital files and their interpretation therefore require HR personnel and recruitment agencies to comply with the ICO’s code of ethics and rules of transparency.
Nor should Big Data replace meetings and interviews which remain compulsory, especially for highly specialised positions.
How can you adjust your personal branding in line with Big Data ?
In a world where any traces left on social media are taken into account and analysed, candidates must be particularly vigilant. So the standard rules of personal branding are more important than ever before – leave behind positive digital footprints, publish clear and precise contents, avoid what a recruiter would see as inconsistencies and be careful of what you post. These are all key recommendations. Who knows? You may be lucky enough to be singled out and offered a job thanks to your online data, just like Jade Dominguez.
Cautious online behaviour is even more important now that LinkedIn has bought Bright, an American start-up specialised in data management which matches candidates with companies, even when the job-seeker has not actively applied for a position and the recruiter has not even considered that type of candidate. The potential is huge – 80% of the 270 million LinkedIn users worldwide are passive. So we are looking at over 200 million candidates who are not registered on job search websites!