To find out how to improve candidate experience using Recruitment Automation, we have a great eBook on candidate experience.

Hiring with heart is good for business: candidate experience in C-19 times. Sapia launches its Candidate Experience eBook. This book provides an insight into the changing face of the candidate experience. 

If there was ever a time for our profession to show humanity for the job searchers, that time is now. Unemployment in Australia has passed a two-decade high. The trend is similar for other countries. That means there are a lot more candidates in the market looking for work.

With so many more candidates, the experience of a recruiting process matters more. What are candidates experiencing? Are they respected, regardless of whether they got the job or not? Is their application appreciated. Are they acknowledged for that?

This may be the time to rethink your candidate experience strategy.

Here are two big reasons to prioritise improving candidates’ experience:

1. There is a much higher value attached to it – both for candidates and your organisation. 

This story won’t be unfamiliar to you:  An Australian based consulting firm advertised for a Management Consultant and decided to withdraw the advert after 298 candidates had applied. That was in their first week of advertising.

When candidate supply outstrips demand, that is bound to happen. Inundation of your Talent Acquisition team becomes an every-day thing. Employers are feeling swamped with job applications.

Being effective is much harder when there are more candidates to get through every day.

High-volume recruiting issues become further aggravated when two additional dynamics come into play:

>> When the role for which you are hiring requires a relatively low skill level.

In the example provided above, the Management Consultant role had several essential requirements which should have limited applications.  Included in the applicant list were hoteliers, baristas, waiting-staff and cabin crew (it’s heartbreaking). So when it comes to roles with a much lower barrier to entry, the application numbers can quadruple.

The traditional ‘high-volume low-skill role’ has now become excruciatingly high-volume. This trend is being seen across recruitment for roles like customer service staff, retail assistants and contact centre staff.

>>When your organisation is a (well-loved) consumer brand. 

Frequently, candidates will apply to work for brands that they love. Fans of Apple products, work for Apple. They also apply to work and get rejected in their millions. So, how do you keep people as fans of your brand when around 98% of them will be rejected in the recruiting process? That’s not only a recruiting issue – it’s a marketing issue too.

Thousands of organisations and their Talent Acquisition teams are grappling with both dynamics right now.

The combination of unemployment and being in Covid-19 lockdown means that consumer buying is being impacted. Their confidence is down. Buying is also down. With people applying for more jobs and spending less as consumers, the hat has somewhat switched. For many who were consumers, they have now become candidates. That may be how they are currently experiencing your brand. As candidates first, customers second.

If customers are candidates and candidates are customers, is there a reason for their experience to be fundamentally different? 

Candidate experience is defined as the perception of a job seeker about an organisation and their brand based on their interactions during the recruiting process. Customer experience is the impression your customers have of your brand as a whole throughout all aspects of the buyer’s journey.

Is there a difference? It’s all about how the human feels when interacting with your brand. A person is a person, regardless of the hat they are wearing at the time!

All about the human experience.

Millions, even billions, of dollars are spent each year by organisations crafting a positive brand presence and customer experience. Organisations have flipped 180 degrees to become passionately customer-centric. It makes sense to do so. Put your customers first, and that goes straight to the bottom line.

What is perhaps less recognised is the loss of revenue and customer loyalty which is directly attributed to negative candidate experiences.

How about those loyal customers who want to work for your brand? They eagerly apply for a job only to get rejected.

2. Candidate Experience improvements have become super easy to implement.  

For those who have tried in the past, you may well know that it can take an extraordinarily long time to ‘define’ a Candidate Experience strategy, create its metrics, find a budget and then execute on it.

Have a look inside the ‘too hard’ basket and there you may well find many thousands of well-meaning ‘candidate experience’ initiatives, that are still lying dormant! So many want to focus on candidate experience, but may shy away from doing so. This is because it’s perceived as time-consuming and expensive.

Plus, right now there is so much on which CHROs need to focus. From ensuring workers’ wellbeing to enabling remote working. Who has the time to also worry about the experiences of candidates?

However, that has changed. Boosting candidate experience is no longer too hard, too expensive, nor too time-consuming. Technology becomes more manageable, quicker and cheaper over time. Also (borrowing from Moore’s law), its value to users grows exponentially.

Candidate Experience Playbook: Hire with Heart

The good news is that for those organisations who genuinely want to improve candidate experience, it has become much easier to do so. Finally, it is possible to give great experiences at scale while also driving down costs and improving efficiencies.

Win-win is easily attainable. In the Sapia Candidate Experience Playbook, read how organisations are hiring with heart. All by creating positive experiences for candidates while also decreasing the workload for the hiring team.

Tech Den is the HR Tech Summit’s flagship program – celebrating excellence in HR start-ups and entrepreneurship across Australia.

Vying for the ultimate prize, a $20k marketing campaign in HRD Australia publications, hundreds of HR Tech start-ups will be whittled down to just a few finalists.

Five lucky finalists pitched their solutions to a panel of judges and investors with Sapia coming out on top.

The competition was fierce as we went head-to-head with Crewmojo, Gradsift, Voop.Global and Referoo.

We were delighted to come out on top!

Thank you HR Tech for the opportunity and the wonderful prize. We look forward to using it!

AI is the fastest growing trend of any technology – EVER

It used to be all about Mobile First, now it’s about AI-first. Google now calls itself an ‘AI first’ company.

“How do you decipher the truth from puffery? Are there any shortcuts to really understand where AI is best applied in your business?”

I’m not a data scientist, but I spend my days talking to users and buyers of AI technology who are befuddled and increasingly cynical about the hype. Here is my 3-step guide to cutting through the noise.

1. Understand that AI is not the same as Machine Learning

Most products are using standard statistical techniques like regression. Without any machine learning baked into the technology, they are just matching tools. There are efficiency gains, but no ‘smarts’ and no learning in technology.

For example, in recruitment a stock-standard AI product would merely find you people with the same profile as those you have already hired, matching applicant profiles to hired profiles. CV parsers do this kind of thing. Now, that can be helpful to you if all you want to do is a short-cut to the same profile fast, and it can definitely save your recruitment team time.

But unless you know that these characteristics also match performance, you will not make a difference to your organisational outcomes.

If your Sales Director tells you that every new hire over the last year is hitting or exceeding budget, then absolutely keep using that tool. If she tells you that a third or more are underperforming or leaving the business, your AI tool is merely amplifying that bias and doing quantifiable damage to your company’s bottom line.

If you want both efficiency and business bottom-line impact – your AI needs to have machine learning baked in.

Takeaway: If the organisation selling you an AI tool has no Data Scientists, there is no machine learning in the product.

2. No data means no AI

If I imagine a Maslow’s hierarchy of AI it would look like the below:

First up you need to have the data.

About 50% of companies don’t pass this threshold, but assuming you have it the next step is understanding the data context: What is the business problem you are trying to solve?

Next is the housekeeping. This means consolidating, cleaning, categorising and cataloguing the data. And then finally the optimisation is at the top – this is where the magic happens. Optimisation is the last mile and is what gets you to the big savings, but you need everything underneath it in order first.

In recruitment a genuinely smart AI tool with machine learning baked-in works best in these conditions:

1. High volume recruitment where you can gather applicant data fast. Which is also why no one is selling AI tools for exec level recruitment yet.
2. Hiring for roles where you have a way of measuring performance AND that performance needs to be a whole lot better. For example, almost all retail businesses track turnover and usually also whether it’s regrettable or not. If that number is above your industry average, then AI works for you. If you have no way of measuring performance for that role, AI will not give you much return on your investment.
3. Recruitment for low skilled roles or roles where success is not about a specific qualification or vocational skill. It’s about soft skills – communication, learning agility, customer awareness and empathy and so on.

Takeaway: It’s critical to have a solid understanding of what you’re trying to fix, and the means to measure the changes you’re making. Ask yourself why you are considering AI if you can’t quantify the problem, to begin with.

3. Once you know the problem you want to solve expect a long term commitment to fix it

AI is about optimisation. For credit card companies it’s detecting fraud quickly. For online retailers better product recommendations. In recruitment, it’s finding the best new hires in a massive group of rookie players.

In each case, you are optimising for efficiency and accuracy, as the cost of getting it wrong is huge.

It means trusting the technology to find the patterns. You have to suspend theory, and your assumptions, a lot. You feed in a large amount of relevant and unbiased data and the machine learns on its own, finding the patterns. It is looking for the ‘signal in the noise’. Humans are unpredictable and more often than not unreliable.

The current hiring processing by humans is extremely resource-consuming and the result is not always satisfying. Using AI will free up your time if you allow it to, improving efficiency or outcomes, often both. But AI built just off CV data only adds bias and we’ve all see how badly that ends.

Takeaway: Predicting human decision making is not easy and not quick. The only way to get to the ‘answer’ is to start now and expect this to be a journey.

You can try out Sapia’s Chat Interview experience right now, or leave us your details to book a call

If you liked this article, suggested reading: 
A CV tells you nothing
To AI or not to AI