Recruitment Costs: Recruit Like Google Without Spending Big Bucks!
US based Laszlo Bock, ex Mckinsey and Google SVP of People Operations (or the man behind Googles’ unique work culture) is a firm believer in the power of recruitment to transform work whilst not increasing recruitment costs for businesses.
His mission is twofold: “To make work suck less” as he puts it and to utilise recruitment as a means of accelerating culture change and behaviour.
High calibre people such as smart price teams don’t just appear when you want them to, he explains. Top talent are highly influenced by the quality of job posts and campaigns. If they don’t like your job descriptions they don’t apply. It takes more than an algorithm to source and select great people and often there are unexpected recruitment costs.
What can we learn from Google about recruitment costs
What’s more, high quality people are more likely to abandon poorly run recruitment processes or online applications that fail at seeking talent. They dislike automated recruitment processes and much prefer a high touch recruitment process with real human recruiters that know what they are talking about.
Attracting quality people can be a problem and can entail high recruitment costs, Laslo explains, when you don’t have talent pools, communities or carefully curated talent networks to draw upon. It is important to use a multi sourcing and selection strategy. Don’t just rely on hiring algorithms.
Google, for example, has publicly discussed its goal to change the demographic makeup of its workforce, which is overwhelmingly male and white or Asian. Yet the 2017 edition of Google’s diversity report shows that Google is finding this a challenging task: only 2 percent of its staff are black, 3 percent Hispanic, 75% of leaders are men, and 20% of tech staff are women, but 48% of no tech staff are women – pointing to the challenges of changing workforce demographics and recruiting by numbers.
Recruitment costs and times have increased by 26 days per recruit compared to 10 years ago according to the Corporate Executive Board.
Businesses that do not have quality talent pools wait two or three times longer than businesses with qualified talent pools to find high quality people for pricing roles. The average time to fill a role for organisations using their internal recruitment function or agency to fill is 63 days.
Without a candidate pool to source more specialised talent (or buy-in from the executive team), most businesses time to fill price leadership roles increases to 200 days or more, which is 28 – 30+ weeks or over 6 months to fill leadership or technical pricing positions.
Algorithms cannot always ensure diversity or even faster recruitment processes, Bock explains, businesses relying solely on algorithms can be left facing serious diversity and resource issues even if the organisation has broad buy-in for diverse hiring. There are many recruitment factors that algorithms alone cannot compensate for – such as a homogeneous pool of applicants.
Bock explains, businesses have to work much hard than ever to attract the attention of talented people. More often than not, high calibre people are not looking to change roles, they are happy in their current positions, or they haven’t even considered working for another business – it’s just not on their radar or they’re not that fussed.
Google takes candidate engagement very seriously; constantly testing and trialling multiple people and sourcing strategies to find the best matches for them.
They take a 2-3 year view of candidate engagement and actively build high quality talent pools using thought leadership, marketing, prompts and reminders.
They run and monitor multiple campaigns and engagement strategies to see what strategies work to draw people to them.
They systematically weed out poor matches and inauthentic social media avatars with puzzles, challenges and problem solving exercises.
“A bad hire can be toxic.” Laszlo explains. “Use recruitment to set the bar high, never compromise on quality, and find someone who is better than you in some meaningful way. Then you’ll end up with a much stronger team.”
A bad hire may be a toxic employee who poisons the morale of the whole team; a bad boss who micro-manages the team or a yes man or women that keeps perpetuating bad habits because it’s safe and easier to acquiesce to the lowest common denominator.
Bad hires negatively affect stakeholder relations and are one of the main reasons high performers leave businesses.
For Lazslo Bock, eliminating bad hires is key to his role at Google as VP of People operations. Bock sees initial search and screening phases as the best place to vet and qualify applications for suitability and fit.
Bock says “We try hard not to not look for people who look like us. Rather, we try to find someone different, offbeat, who can push and challenge the status quo.”
We are all inherently biased to hire people like us. Unfortunately, most companies hire to type, creating serious diversity and inclusion issues further down the line.
Bock says, “Before you start recruiting, decide what attributes you want and define as a group what great looks like.”
He adds. “A good rule of thumb is to hire only people who are better than you.”
Developing a clear hiring criterion underpinned by a proven framework is basis for an objective search and selection process. Seeking management alignment on the framework across the hiring committee and clearly defining underlying traits and capabilities helps businesses like Google avoid biased hiring decisions and costly hiring mistakes.
To avoid bad hires and overlooking talent, Bock says, he’s actually built a sophisticated search and selection infrastructure for Google that results in every application sourced by AI driven search algorithms, campaigns or referrals to go through to a secondary screening process led by a human recruitment team.
“Google only hires several thousand of the 2 million applicants they receive. This makes “Google 25 times more selective than Harvard, Yale, or Princeton.”
Google have invested in a recruitment team devoted to reviewing all applicants that have been sourced and screened by AI driven recruitment systems.
They have also invested in an additional recruitment team to review applicants who’ve been rejected from the regular process to show the importance of making unbiased selection decisions.
Google reviews all rejected applications just in case someone potentially valuable has been missed during the search process (and hence high recruitment costs that a small business can not take).
So, contrary to what many people assume about Google and how it recruits; Google recruitment sourcing and screening process still remains purposely manual and heavily reliant on skilled human recruiters.
For Google, the cost of making the wrong hire far out ways the cost of carefully assessing applications.
Carefully screening candidates is the value add service to finding the right match for the business. Automating broken recruitment processes and unreliable data only helps AI to learn bad habits and biases.
AI is a tool; not the definitive answer on candidate sourcing or selection.
Google purposely does not fully automate the application screening part to AI for 1 very important reason: AI match making, like human recruitment can propagate algorithmic discrimination.
Designers and engineers developing algorithms are humans with biases. The input data they select will inevitably bias someone somewhere.
How a developer selects data and constructs variables for algorithms can overlook and even omit the importance of skills and attributes that a human recruiter may think are important to the business.
Conclusion on recruitment costs
How designers select data to develop their algorithm will naturally alter how they craft the underlying algorithms.
Human recruitment teams are vital to recruitment processes. Finding a practical synergy between AI and human recruiters is a work in progress, but a worthwhile pursuit when you get the balance right.
AI search algorithms are tools; not the complete solution. It is a mistake to let AI control all match making without putting in place expertise, checks and review processes.
Real human recruitment expertise and AI are required to improve quality of hire, cost per hire, candidate fit, candidate experience and hiring manager partnerships. See our blog on why diversity is vital to price intelligently.
See our blog on team burnout here.