To take advantage of all the new technological innovation coming into the recruiting world, businesses need to view their recruitment technology as a constantly-evolving picture.
Far from removing the recruitment manager and HR team altogether, it actually has the potential to quicken up the recruitment process, enhance the candidate experience, and effectively add to the time that recruiters can spend with potential hires.
So, why is it that automation is considered to be such an effective way forward? How do clever algorithms and code really help to alleviate the administrative burdens of recruiters and simultaneously enable better personalisation for more frequent engagement?
The answers have certainly been evolving over the last twenty years since WCN first established itself on the market. But perhaps the one thing that hasn’t changed is the need for a formalised approach to workforce development – i.e. one that will help a business to build foresight models to plan hiring around whilst realising business goals in intuitive, easy to use, focussed and efficient ways.
The golden ticket appears to be automated processes that crunch high volumes instantly, cutting admin and costs; driving transparency for candidates and recruiters; expanding reach & diversity, and massively reducing the time-to-hire.
The right tool for the job
With that in mind, the build of software must become more logical in order to facilitate the successful delivery of a model that is fit for purpose, and that recruiters/decision-makers can have confidence in.
This results in the build of tools that enable integration with complex datasets – the outputs of which are critical when it comes to enabling robust evidence-based decisions to be justified, particularly around areas such as shortlisting and assessment scoring.
Developing such models is not easy and requires careful planning and specialist technical knowledge. The process synthesises the views of multiple stakeholder groups, uses large datasets and links together different applications. Contrary to some opinion, it’s not just about relentless cost-cutting and technology taking over.
Nor is it just about the notion that applicant tracking software serves just to provide a simple first cut of applicants based on pre-defined basic attributes that a job requires so that all but a few candidates make it to the interview stage.
It’s almost impossible to do that with any precision, and clients do not want to be perceived as having an overreliance on credentials or experience that are not all that relevant to a post.
What they do want though is for technology to help them to hire the best before the rest. Ever since the recession first hit and the job market became even more competitive, it has been essential for recruiters to be able to find ways of expediting processes and breaking through the difficulty of distinguishing between different applications.
Pinpointing the perfect candidates
The human review process is always revolved around finding it much easier to say ‘yes’ or ‘maybe’ than to say, ‘no.’ The risk then becomes that at this stage, everyone has excellent academic credentials and seems to have packed an awful lot into their professional lives – no matter which stage they are.
Characteristics of candidates can become equally distracting. Through the answers they give, they are perceived as interesting, sometimes witty and suddenly the ‘yes’ pile grows at an unsustainable rate. There’s this temptation that emerges where you want to meet them all. New technology is evolving this with features such as smart processing of big data, psychometrics, video, assessments and social content to pinpoint great talent.
Intelligent solutions automatically process and drive insight and improvement. But is the automated approach a good thing? In some ways, it can help a recruiter to digitally analyse if a candidate would fit the organisational values you are seeking to fill.
Recruiters must craft job descriptions to match sophisticated algorithms embedded in technology
Applications aren’t wasted though and an intrigued recruiter will check those ‘eliminated’ to see why this candidate appeared not to fit the mould and might even be persuaded to give them a chance.
In order to determine this well, recruiters must craft job descriptions to match sophisticated algorithms embedded in technology – the selection process requires knowledge of what keywords are likely to be used, and which uncertain parameters will need to be quantified.
For this reason, WCN advocates the importance of working backwards from the policy decisions that may need to be made, and think about what outputs are required from each of the stages to enable these decisions to be modelled and analysed.
Inevitably, there may be some parameters that cannot be modelled, or limitations to the available data, which may lead to decisions being needed as to what is practically possible. As a general rule, it is better to use the simplest approach and only add complexity once the findings have been thoroughly analysed, and only then if there is solid evidence that it will improve accuracy.
Complex models are often less accurate than simpler ones, especially when dealing with uncertainty. Simple models are easier to understand, and are consequently less prone to mistakes. Done well, this brings rigour to the hiring process and will help to create added human capital value with it.
Staff can be onboarded on the e-recruitment systems they applied to
Technology is not standing still either. Automation will continue to evolve and employers need to be keeping up with changes. Staff can be onboarded on the e-recruitment systems they applied to, for example, undertaking any procedures that can be completed pre-joining or simply providing information to ensure they have equipment and/or uniform ready for their first day. The same systems can be used to securely host contracts and other HR forms that the employee must sign up to as part of company terms and conditions.
Over time, the brains behind the technical excellence offered by e-recruitment specialists such as WCN will continue to evolve the algorithms that make up the sophisticated filtering and shortlisting capabilities provided through automation. The process will be enhanced to help truly eradicate potential for bias and help streamline HR delivery in effective and efficient ways.