You're Hired! (Because I like you)

It is often said that a company's employees are its most valued asset.

It is therefore hardly surprising that companies (and law firms are no exception) spend vast sums of money in an attempt to recruit the "right people", whether this is for graduates or more experienced hires, right up to partner level. With graduate recruitment season currently in full flow, and prospective recruits being thrown all sorts of freebies at law fairs up and down the country, it may be worth asking: is there a better way to recruit?

Clifford Chance and one or two other big law firms certainly think so and have attempted to differentiate themselves by introducing a "CV blind" policy for final interviews. The aim here is to increase diversity amongst recruits, in order to prevent any perceived bias towards the "old school tie". It is without doubt fairer than the mythical company recruiter who threw half of the CVs that landed on his desk in the bin without looking at them on the grounds that "I don't want unlucky people working for me".

Laszlo Bock of Google thinks he has an even more radical solution to the problem (see here). He describes CVs (or "résumés") as "a simply awful way of marketing yourself for a job". He argues that the job descriptions people give themselves and generic sound bites from candidates can be misleading. Similarly, job descriptions can be inaccurate and the interview process flawed (because, Bock says, "we are biased, ask bad interview questions, rarely go back and check if our predictions were correct, and so on"). Ultimately, this can lead to inappropriate candidates getting hired.

Perhaps unsurprisingly, given that Mr Bock works at Google, he believes the answer to these problems lies in data. Programmes and information can match up skills that prospective employees have with gaps in a company's skills profile. He concludes by stating that "the most efficient way [to recruit] is by looking at large sets of data and inferring relationships, similarities, and predictors of success and failure".

Given that so many people (both recruiters and prospective employees) use tools like LinkedIn to seek out staff/job opportunities, the market is already using data to try and match people to jobs. Mr Bock envisages this principle going a step further, where data and programming would be able to match up an individual's skill set to the best job for them regardless of what degree they have or where they went to school (items which can take up significant space on a CV). As he puts it, "slowly we'd become able to not just match people today, but also to tell people where to invest to be ready for tomorrow's jobs".

Clearly the legal industry is not going to dive head first into an entirely mathematical approach to recruiting; however in recent years almost every law firm has bulked up its social media presence, a platform where prospective employees (particularly at a junior level) are heavily invested. Given that companies are always seeking to employ the "right people," any tool which could match up prospective employees with employers using traditional criteria, such as interests and skill set, but also taking into account other factors, such as the kind of workplace people thrive in and what sort of boss they want to have, is likely to be sought after by employers. And in Google's world, data and algorithms are part of the solution.