It can't fail to work: the technology behind such dating sites is highly complex: utilising key words and phrases and automatically picking out specific options and preferences, the 'love seeker' is closely matched to a multitude of possible partners. Who needs Cupid?
Compare this technology to that which powers many recruitment systems and the story couldn't be more different. From the jobseeker's perspective, they are often matched to unsuitable vacancies: maybe it doesn't correlate to their skills and specialisms or maybe they are simply not interested in the role in the first place.
From the employer's perspective, they often spend (waste) hours trawling through thousands of profiles and applications of unsuitable candidates to develop a shortlist of 'potentials' to interview; who, once interviewed, may not even be that suitable for the role anyway. Given that this is often the experience of both employer and jobseeker in an age of online recruitment, it is a wonder that any vacancies are filled at all.
Such trial and error job-matching may work once in a while, but it is hardly a good use of time and money. Crucially, the current 'trial and error' system used in many technologies overlooks perfectly suitable candidates because jobseekers, through no fault of their own, may not have entered the 'right' text into their profiles. This is my main problem with matching technology today: it is far too generic.
CVs aren't formularised and are notoriously impossible to analyse qualitatively. Whereas one CV may include an 'achievements' section, another may call the same section 'accomplishments'. This becomes problematic when you rely on technology to search purely for specific words and phrases. For instance, one organisation's idea of a business development role may be totally different to that in another organisation. How can you possibly work with such generic terms without taking it to the next layer and understanding the skill set for that type of individual in that specific organisation?
Most technologies simply can't cope with the plethora of language used within recruitment. Yet I know from experience that it's perfectly possible to create an engine that semantically matches candidates to jobs and jobs to candidates, without relying on the right text to be inputted, on the jobseeker to search for a specific role to fit their skills or for the recruiter to search for certain skills. By creating a recruitment system that is bespoke for every organisation, there is no need to learn and re-learn the multitude of possible terms and phrases for each and every vacancy.
Instead, you work with each client to fully understand their business, so the matching is accurate and the hard work is done before you've even started the recruitment process: employers can then spend more time engaging and conversing with the candidate population, as opposed to doing work that can be time-consuming and inefficient.
It becomes a win-win situation: successful candidates are easier to locate, unsuccessful candidates enjoy a really positive experience with the company they've applied for, and those candidates who were suitable but didn't quite fit the role are retained in the system for future vacancies, therefore making it easier (and quicker) next time the company operates a recruitment drive. I have seen how well this works, so it is no longer an excuse to claim that such technology is too complicated to create.
Dating service technology has been leading the way for years: it is time for recruitment systems to catch up and deliver real value for money.
Lisa Scales (pictured) is CEO of talent management company TribePad
