Today’s guest blogger is Jason Starr, CEO of Dillistone Group PLC, a leading global provider of software and services that enable recruitment firms and in-house recruiters to better manage their selection process and address the training needs of individuals. Their new platform, Talentis, takes advantage of big data and AI to help recruiters find candidates with the relevant experience for their searches.
“I need a candidate with experience in fintech. She’ll ideally have a background in banking and will have worked in payments.”
Candidate specifications come in all shapes and sizes, but it’s increasingly common for a hiring manager to require specific industry experience. Historically, this is where specialist recruiters come into their own – being able to mine a database with extensive data about professionals in a niche sector can certainly help find candidates with relevant experience.
Of course, the “Great Resignation” that is driving demand for your services is also devaluing your databases. Those 10,000 candidate profiles you’ve built over the last decade? Well, 40% of the candidates they represent are considering a career change that will make your database out of date “overnight!”
So, recruiters increasingly turn to LinkedIn as the “source of truth.”
There is no doubt, the 700 million profiles it boasts are typically more up-to-date than the information stored within any recruiter CRM. But…LinkedIn’s recruiter tools are not designed for identifying candidates based on specific niches. It has no “fintech” industry filter – choose from computer software, internet, financial services or banking. You’ll find plenty of potential candidates, but most will have no exposure to fintech – most will be irrelevant.
So, recruiters use keywords. Be it on Google – via the “X-Ray search” or using LinkedIn’s own search tools, users try to identify candidates with relevant experience based on words that appear in personal profiles.
And this works well. To an extent.
Take PayPal. PayPal is unquestionably a fintech company.
The CEO of PayPal is Dan Shulman – but guess what? The word “fintech” does appear on Dan’s LinkedIn profile. So, a keyword search on Google or LinkedIn for “fintech” will not find him.
Which is crazy. Every recruiter who has any interest in the fintech sector would consider PayPal as a fintech company. They would realize that anyone who works for PayPal has exposure to fintech. But profile-based keyword searching doesn’t deliver.
The problem is that many candidates will not explicitly talk about the industries they are in on their profile. Look at yours. Do you explicitly say you work in “fintech executive search” or whatever keywords you might expect to be found by?
I’ve been working with executive recruiters for the best part of 30 years. Back in the day, there was no LinkedIn. There was no internet. Headhunters would work differently – they would draw up a list of “target companies” and would then identify candidates based on sourcing appropriate employees at each firm. It worked well – but it was laborious. Potentially, days of work, often involving dozens of phone calls.
LinkedIn provides a middle ground for this approach. If recruiters can identify the right companies, LinkedIn Recruiter allows users to search by current (or previous) employer. Searching by individual company names is somewhat laborious, but far better that the traditional approach.
Any company specific search though is limited to the companies that the recruiter initially identifies. It’s unlikely to be exhaustive in a time scarce reality. It’s also one dimensional – how can a “target company” based search find candidates that have worked in fintech AND banking?
What if recruiters could search based on company description?
Interestingly, while it’s not possible on LinkedIn Recruiter or Recruiter Lite, it can sort of be done using LinkedIn’s Sales Navigator product. Sales Navigator has separate search screens for People and Companies (so-called ‘leads’ and ‘accounts’), and the company search feature incorporates a company keyword search. It’s not great, though – recruiters need to be able to combine candidate-specific and company-specific filters, all in one place.
That’s why we developed our Talentis candidate search functionality. We’ve sourced people and company data from a variety of sources (in addition to LinkedIn, our company data, for example, comes from sources such as FT.Com and Bloomberg) and built a search screen that allows recruiters to search across both people and company data simultaneously. We’ve also enabled users to differentiate between keywords associated with current employment and previous roles – hugely speeding up the candidate review process.
It’s a new product, but it’s taking the recruitment world by storm. Learn more about candidate sourcing with Talentis on our site.