Attracting top talent is vital within any company or organisation. According to a CareerBuilder survey, 75% of employers admitted to having made a poor hiring decision, resulting in a loss of nearly US$15,000 per bad hire. In today’s world, finding the right talent that will stick may seem more difficult than first imagined.
Maybe not. Why wait for candidates to come to you when you could find them before you even click on a job ad template? As a recruiter, you could be sourcing your candidates and choosing who you add to your talent pipeline, instead of candidates deciding whether to engage with you.
Before we dive in, I’m Neil Kinnaird, the Co-Founder and CCO of Zimpla, the AI sourcing platform that helps recruiters source and shortlist a candidate in seconds. I recently spoke with JobAdder to discuss AI sourcing and how it can help improve sourcing within recruitment, resulting in saved cost, time and resources.
Sourcing 101
Sourcing as such is the proactive search for potential candidates to fill a current or future role, prior to being posted in a job ad. Sourcing can be achieved through a number of ways:
- Start your search within your database. Your ATS/CRM can be a goldmine of potential candidates who have shown a past interest in your company.
- Build on networking by attending social and community events. Remember that not everyone is actively looking for a job but according to LinkedIn, 90% of professionals would be interested in an opportunity.
- Use referrals
- Boolean search: connect your search words together to either narrow or broaden your set of results. Eg. candidate and marketing. To understand how Boolean search works, here’s a beginner’s guide.
Now that we’ve established what sourcing is, it’s interesting to note that in 2018 LinkedIn released their Top Global Trends in Recruiting Report. This report shares insights from 8,800+ recruiters and hiring managers on how diversity, new interview methods, data and artificial intelligence, are impacting recruitment today.
With reference to AI, It states that artificial intelligence is helping recruiters and hiring managers to save time (67%), remove human bias (43%) and deliver the best candidate matches (31%). The report also said that AI is most helpful when sourcing candidates (58%), screening (56%) and nurturing candidates (55%).
AI sourcing is fast becoming a new and upcoming tool that is taking over recruitment. But what happens if recruiters chose not to utilise AI sourcing? Will it be challenging overwise?
The challenges
You won’t be able to compete with the competition, who can undertake sourcing quickly and at a cheaper price with consistently high quality.
I’ve noticed that the main challenge recruiters face is trying to offer your candidates the same or better value in a similar timeframe as your competitors, within a very competitive climate.
In addition, manually searching for candidates is time-consuming and gives your competitors the opportunity to source and reach out to top candidates. AI can save costs and time by sourcing candidates that are best aligned to your job description.
We’re now seeing AI within recruitment take a massive leap forward when sourcing candidates. I then discussed my points on AI in recruitment and how it has developed over time and changed the recruitment industry.
Shifting the way we recruit
Through AI, awareness of technology has come to the recruitment industry, in general. That awareness and subsequent opportunity has brought a plethora of technology solutions to the industry including a boom in AI.
However, not all solutions purporting to be AI are exactly that. So it’s important to understand, even in layman’s terms, how AI is being implemented, and that you are actually getting what you pay for.
I recommend a need for education or at least, a valued and knowledgeable partner is important before diving into the AI world.
The impact AI has brought to the industry has progressed with uptake and expanse of options. Here’s my list of how AI has made a positive impact on the industry. This can be outlined in chronological order:
- Bringing efficiency to operations and replacing costly and time-consuming tasks with smart automation
- Insights into behaviours of recruiters and their value to their business and customers
- Removing subconscious bias from the selection process with well-trained platforms basing decisions on data patterns; not human assumptions
- Evaluation of profiles and personalities to fit with organisational needs
- Data-driven decisions through all aspects of your practice:
a)Sourcing
b) Shortlisting
c) Interviewing
d) Onboarding
e) Talent Management
With the mass of technology available, it has manifested into a very complicated environment. This is why it’s important to ensure that any technology aligns strongly with your processes, or you’re ready to impart change into your practices.
We now live in a subscription economy so there is no longer the need to outlay significant capital into large enterprise platforms. Choosing the best of breed that works for you allows you to control spend and align to operational budgets to manage your cash flow.
AI potentially improves recruitment sourcing by reducing reliance on external resources, ad spend and bias.
Here I will be diving into how AI sourcing reduces recruitment bias.
Removing bias
When it comes to recruitment bias within sourcing for candidates, it depends on how the AI platform has been designed, developed, implemented and trained. It is imperative that a diverse data set has been used as a training set of data, and that feedback given on the results is by a diverse set of recruitment professionals.
Another important point is that AI removes static keyword biases when matching capability with Natural Language Programming (NLP) techniques that understand the context of language. This is important, as keywords are a static, point-in-time method of searching for a one-to-one match. If the keyword exists, you get a match, therefore, the bias in sourcing is based on keywords used.
By using AI via machine learning algorithms and Natural Language Processing, it’s possible to find patterns of similarity, intent and context. This means that you don’t need to have the exact word or phrase to find the best fit within the terms you’re searching for.
Done well, the context of language can be used to understand how skills have been applied to roles, therefore, understanding if a candidate is well-suited to a role based on their experience and not based on having the right keyword in their resume.
So, ‘why is this different approach important to finding candidates?’
Well, candidates can ‘load’ their resume with keywords. This means that they will ‘float’ to the top of a keyword search as it works on the frequency or the number of keywords found. There is no sense of context or intent. Candidates can be missed because they’re not using the right keyword or combination of keywords to be found in a keyword search.
Finding a candidate with a keyword is based on the skill of the consultant to write the right query or choose the right keyword. This is where subconscious bias starts within this type of approach.
The value of AI sourcing
When we look at AI, business owners need to understand the value it will bring to their company. AI can help sourcers, recruiters and hiring managers to find the most qualified candidate for the role without wasting time reviewing hundreds of resumes and profiles.
But the benefits go beyond this:
- Data shows you exactly why candidates have been sourced
- Reduce time spent screening candidates
- Find the best talent before your competition
- Cut your recruitment advertising spend
Through Zimpla, our technology has been designed, programmed and trained on over 50 million data points in vertical industries, and is, therefore, accurate for the industry you source for rather than a generic search.
Zimpla can assess over 300,000 resumes in 10 seconds, giving you more time to build real relationships with your clients and candidates. We strongly believe recruitment is a
humanistic industry, so giving talent professionals more time for human interaction is a significant benefit to the industry as a whole. Zimpla has continuous feedback loops so that it constantly learns what a good candidate looks like, which is imperative when sourcing top talent that will stick.
Interestingly, it is possible for businesses using AI sourcing to cut 85% and more on time and cost of screening, as seen in human to machine comparisons.
Through AI sourcing it allows you to rediscover talent in your candidate database before you advertise a role. All without advertising spend! Industry statistics show that with a good candidate database, a significant portion of people you’re advertising to already exist in your database – match before you advertise.
The benefits
We’ve established that AI sourcing can cut back on bias and 85% on time and cost of screening. With Zimpla, I’ve shared two client examples to support this statement.
- A recruitment agency was able to fast track its sourcing process. “The first shortlist took seconds and produced the same top 5 candidates as our 5-hour manual CV review process for 50 CVs.”
- A primary and secondary school amalgam projected to save over $2M in sourcing costs over a year.
With these figures alone, AI sourcing can be used to potentially take your business one step ahead of your competitors. Improve your candidate experience and quality of candidates through AI sourcing.
Remember that 90% of candidates are open to new opportunities, and with hot talent comes other recruiters pushing to the front.
Without AI sourcing, the risk of receiving candidates that don’t match your requirements and skills potentially increase.
Editors note: This blog was written in conjunction with JobAdder’s Content Writer Bianca Compagnoni.
Need help building your talent pool? Download our ultimate guide to sourcing talent.
