In this jobs market, the secret to success is not necessarily a huge job ad budget or a top-range salary and perks package. You don’t even need to be the biggest, or the best known – many are the top-notch candidates that have been ghosted by the world’s most sought-after companies.
You do, however, have to invest in employer brand. Most of us know this, of course, but few companies have made the appropriate investment in long-term brand building. It’s a marketing play, fundamentally, and it’s difficult to do right, but the benefits can be huge for your business.
It’s your best long-term approach to recruiting. If you give every candidate a caring, consistent, and memorable experience, you will dramatically increase your fill rate AND your talent network. People talk about good experiences – in fact, according to our own data, a single good experience while applying for a job makes candidates 77% more likely to recommend you as an employer of choice.
The good news is, too, that the impact of an employer brand can be easily measured, according to Dr John Sullivan: By the number of job applications you receive each year. Now, don’t confuse this point with the opening sentence of this post – there’s a difference between a company’s brand and its employer brand. You might be a Fortune 100 company with a household name, but if your job application process is terrible, people will know you and remember you for that.
(And, if you’re not careful, a poor employer brand will end up affecting your wider brand.)
Your employer brand touches everything. You have seconds to introduce yourself to candidates, show off your best features, and get them to apply. That doesn’t mean, however, that you need to throw everything out and start again. Start with some easy wins, and then take a wider focus to include things like your technology and feedback processes.
Stodgy artwork, pixelated logos, spelling errors, outdated information, broken links… these will break your recruitment strategy before it has had the chance to work. So start here.
|Website||Is our ‘About us’ section up to date?|
|Do we have a ‘careers’ or hiring information page?|
|Do both sections, along with the rest of our website, adequately reflect our values?|
|Social media platforms||Is our ‘About us’ section up to date?|
|Do we include correct contact information, including to our website?|
|Does our imagery and content reflect our brand values?|
|Are our job postings attractive and adequately promoted on the page?|
|Recruiting portals (Seek, Indeed)||Is all of our information up to date?|
|Are our visual branding touchpoints (logo, header/banner images) of sufficient quality?|
|Is all of our information up to date?|
|Third-party recommendation apps (e.g. Glassdoor, Productreview.com)||What is the average star/quality rating of our reviews (mostly negative, positive, mostly positive)?|
|Have we made an effort to visibly address customer/employee feedback on the platform?|
It’s important to note that the branding and visual appeal of your organization is not primarily your responsibility – maintaining it is a team effort. But portals and third-party apps are often overlooked over time, as a brand develops and organization information changes. It’s never a bad idea to champion the task of regular housekeeping, and get your best marketing minds to help.
With our Ai Smart Interviewer on your team, you’ll give every single candidate an engaging, empowering experience with your brand, boosting its value from the moment they click ‘apply’.
You can have offers out to the best candidates in just 24 hours. This is an incredible value proposition for candidates who are applying for 5, 10, maybe even 20 jobs at a time and usually don’t expect to hear anything back.
Here’s how it works:
Our customers have cracked the candidate experience code, enjoying application completion rates in excess of 80%, and candidate satisfaction scores of more than 90%. Everyone gets an interview, and no one is ghosted.
Remember: There’s no space in this market to be slow.
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The job seeker is a human being who at some point in the process wants to talk to another human being.
B.C (before COVID-19), organisations would create those moments of connection with prospective hires through campus events, case study workshops, group assessment days and invitations to office events.
COVID-19 and forced incubation make some of this impossible and even illegal.
Organisations who have been forced to bench thousands of employees face the same challenge. Staying connected to, caring for and protecting this ‘people asset’ they have built and invested so much in.
The only experience organisations have with protecting an asset on extended leave is when new parents take parental leave and for most organisations that comes down to letting them keep their computer equipment and inviting them to the Xmas party.
Countries in the southern hemisphere are bang in the middle of graduate onboarding, and graduate recruitment and those in the northern hemisphere are about to kick off their programs.
They bring new ideas and new skills, and above all, ambition to make a difference. They are also often the most cost-effective cohort as far as output vs salary and related costs.
Have you been following the HR practices of tech companies over the last decade? If you have, you will notice that expectations of employees and candidates have shifted big time. The Netflix culture deck personifies much of it with concepts such as ‘Trust people, not policy’ or ‘Trust + transparency = accountability’.
Trust at work means your team will work all night to meet a deadline. They will be generous sponsors and ambassadors for your organisation and your products, they will refer their friends to work with you. Additionally, they will accept change in your business more readily. Your team will admit and bounce back from mistakes and failures more readily, and overall their discretionary effort will be substantial.
Trust in the workplace is a massive accelerator, and most organisations are trying to find ways to accelerate – to build product faster, ship faster, change business models faster.
Woebegone companies that believe they can keep attracting talent especially young talent with a purpose of ‘improving Shareholder returns’. Today, we look for aspirational purposes that connect us to something bigger and with which we want to identify. Check out the motto mission statements of the tech giants here and to be the 11th million (or thereabouts) person to download the Netflix deck click here!
The Computing AI & Machine Learning Awards recognise the best companies, individuals, and projects in the AI space today. The awards cover every corner of the industry: security, ethics, data analysis, innovation and more. They also showcase the movers and shakers. “The technology heroes and projects that deserve industry-wide praise”!
From data entry to chatbots, artificial intelligence has applications in every industry, sector, and role. Even the most basic implementations can free a workforce from time-consuming manual tasks, with more recent developments providing real insight into customer data.
Artificial Intelligence as a concept has existed for decades, but only in recent years have businesses begun large-scale adoption. AI technologies have the potential to reshape the world that we live in and change the way that we work.
This is a combination of Conversational AI and Explainable AI described by Computing as follows:
The consumer world is rapidly adopting speech-based AI – but these systems, which can engage with users like a human to capture context and accomplish tasks, also offer a step-change in how we utilise enterprise IT. They can accomplish data entry, but also book meetings, answer questions, manipulate data and much more. Our judges want to know where you implemented conversational AI in your business, why you chose to do so and what quantitative effect it has had, as well as the challenges you overcame along the way.
With the rise of legislation like the General Data Protection Regulation, AI can no longer be a simple black box. Companies must be able to provide the reasoning behind AI decision-making. Thus, this award will go to the company that has made the most progress in adding transparency to their AI processes.
Conversational AI is how the technology works and Explainable AI is a key-value guiding the way the service is delivered.
Using Sapia, people apply for jobs by texting their answers in response to specific questions that are then analysed by AI for personality and work attributes. Given that it is AI facilitating the interviews, it means that every applicant can be interviewed. All in all, this makes it much fairer for all candidates and much quicker for recruiters and operational leaders.
The award will be presented on Tuesday 22nd October in London.Judges include Christina Scott, Chief Technology Officer of News UK, David Ivell CIO of Enginuity and also Natalia Konstantinova, Architecture Lead in AI for BP.
Additionally, to keep up to date on all things “Hiring with Ai” subscribe to our blog!
Lastly, have you seen the 2020 Candidate Experience Playbook? Download it here.
One of the questions we get asked a lot is “what’s the difference between psych testing and predictive analytics”. So today we’re going to unpack this a little bit and look at how the two differ, and where they are similar
Psych testing has been around for decades. It’s an old-school form of predictive analytics. You look at a big group of people who are in the same role and figure out what’s common with their profiles, define a set of questions to test for the common attributes for that role and then apply that as a broad-based test for anyone who is applying for that same role.
It’s been around for a while, so people are familiar with the practice.
Read more: The Changing Role of the Organisational Psychologist
It’s generally expensive, cumbersome to interpret, and based on a very big assumption that if you fit the profile you will be successful in the role.
Psychological assessments have long been used to identify ‘hidden talent’ or ‘potential’ in people with limited work experience. Whilst these traditional assessments have reduced the hiring and promotional error rates, they take time to analyse, are costly, and are built off competencies inherently imbued with bias. It gives a suggestion that you are a fit, but we know that this rarely correlates to actually being successful in the role.
Psych tests are testing your ability to do a test. That’s it. Traditional psychological assessments do not link to actual performance in the role, nor do they have any self-learning functionality. There is no performance data that feeds into psychological assessments and therefore they have limited predictive power.
In the context of Sapia, we use actual performance data to predict a candidate’s likelihood of success in the role they have applied for. The applicant completes an online questionnaire, but in-between the questions asked and the applicant’s responses is a data model. This statistical model draws on many different objective data points to predicts a candidate’s success in the role.
This also enables an efficient and immediate feedback loop about the actual performance of the hired candidate, improving the accuracy of the predictive model over time. Very quickly the predictive model that you use to select high performers becomes completely customised for your business. You build your own bespoke Intellectual Property, which becomes even more valuable with use.
We all try to find patterns to help us make decisions, whether it’s ‘this restaurant looks busy so it must be good’, to ‘this person went to the same university as me, so they must know what they’re talking about’. We are often blinded by our innate cognitive biases, such as our tendency to overweight the relevance of our own experience. We end up in a tourist trap eating overcooked steak because that’s what everyone else was doing.
Our predictions are based on analysing objective data – someone’s responses to a set of questions, compared to the objective performance metrics for that same person in the role. This is a much more reliable and fairer way to make the decision. The democracy of numbers can help organisations eliminate unconscious preferences and biases, which can surface even when those responsible have the best of intentions.
We work closely with the recruiter or hiring manager to drill down into the qualities of a high performer, and then structure a bespoke application process to search for this. This could be a high level of empathy for customer service or the drive and resilience needed in sales.
Like all AI, our system improves with data. It learns what kind of hires drive results for your business, and then automatically begins to look for this with future applications. Ultimately, the more applicants that apply, the better it gets in identifying which people best match your requirements. And the longer you leverage our system, the more effective it gets.
Hopefully, that’s given you a good overview of where we differ, and what some of the advantages of implementing this into your recruitment process. Still, looking for more?
You can try out Sapia’s Chat Interview right now, or leave us your details to book a demo