Jobs & employment blog

We all strive to deliver the best possible experience and service to each of our customer groups. Artificial intelligence (AI) is developing as a method in increasing the efficiency of providing that experience, but in doing so it also requires data to inform machine learning.

How do we demonstrate the value of AI, so that people are comfortable to share richer data? What are the potential benefits to each stakeholder, and at what point does automation negatively impact the customer experience?

What do automation and AI bring to the hiring process?

This is largely about scale. For most talent acquisition teams – whether corporate or agency, the problems associated with moving at scale to handle large volumes of requisitions or candidates have generally been constrained by our human capacity. What automation and AI does is enable processes to be completed at a scale that is simply unachievable by humans. The need to do this is about to be ramped up significantly given the environment we face and the levels of unemployment that are predicted – the likes of which most of us will have never seen, meaning the rate of applications and candidates seeking roles will increase tenfold. It’s tempting then, to use automation more broadly to help us handle those volumes.

However, the decision to change jobs, seek career advice and understand the dynamics of the current job market are deeply personal to every individual – and this is where we believe the art – the human face of recruitment, where personal needs are understood and the nuances of roles, teams and organisations are considered – needs to blend seamlessly with the science. The science being the way we develop our capability to make our processes more efficient, more effective and seamless for our users, our customers.

We need to be thinking about the objectives in using automation from a human perspective – in our case a key outcome we’ve been looking for has been to increase the level and capacity we have for the human aspects of the work we do – everybody benefits from that – giving us more time to focus on the subtleties and relationships that are so valuable and important in the longer term..

Are there other considerations in bringing A+AI into the process?

There has been much hype and promise about AI and how it will help us rid the hiring process of bias. The reality of this however, is that most solutions in the marketplace today rely on previously gathered data, including decisions, which therefore puts bias back in the process. In our view it would therefore be wrong to assume that using AI makes the process inherently fairer. The ethics around the use of AI in the screening process is still to be bottomed out and in fact in a recent paper from the European Commission makes it clear that there is an expectation of ongoing human involvement at the key points of any hiring decision. People want transparency – so whenever we involve the application of AI we need to have the ability to clearly explain why recommendations have been made and on what basis.

What results have you seen from using AI to automate processes?

Where we have seen very exciting results from automation has been more geared towards engagement. Some of you might have read about Hays’ Find & Engage strategy which we continue to evolve, with technology playing a key role in that evolution – the use of Chatbots like Mya for example. Find & Engage to us means rather than relying on job advertising to identify and connect with the right candidates, we’ve been focused on finding the best ways to engage with the people we already know.

The best possible customer experience for a candidate is one where we contact them at the right time, with the right message – whether that is content that we’ve created to support their career development, to enhance their skills or in fact put a relevant job opportunity in front of them. Using automation here also enhances the consultant experience – making them way more efficient and effective because they’re calling the right people and having meaningful conversations with them – giving them more time to focus on building personal relationships, increasing their job satisfaction and actually having technology work for them.

We’ve all worked hard to make the application process seamless and easy in the past few years. That’s created a huge volume of candidates that many of us find difficult to process and maintain. Our challenge was – how could we use AI to help us decide who to call – and what to say? So, we started working with Mya. To be clear, Mya has two key work streams, one is screening, and one is outreach. We wanted to focus very much on outreach – engagement in the Hays vocabulary and the results were impressive.

Our first test audience was IT contractors that had registered with us but that we hadn’t spoken to for some time. In that first round, and in fact subsequently this statistic has remained constant as we have rolled this out across the globe, 41% of recipients responded with useful information. A great result and much better than other channels we’d tried, and certainly better than we anticipated. Great outcomes all round – we had a very low unsubscribe rate, we could convert the conversation into meaningful actions and the feedback we’ve had from all our customer groups has been fantastic. Consultants are calling people who want to be called, candidates get to update their information at time and in a format that is convenient for them, and hiring managers get to select from a talent pool that is bang up to date.

We have also had great success using Automation Anywhere to streamline various repetitive processes both in the front and back office. For example, gathering and processing compliance data can be a tedious and complex task for candidates and consultants alike. Having that automated has made the journey faster, needing less input from all parties and resulting in increased efficiency on our part and a much less onerous journey for candidates – a win-win for everybody.

What we’ve learned from our experiences in these transformation projects is to start with basic first principles – rather than automate a bad process, map out how it should ideally work, redesign the process with your customer needs at the fore, then bring in the technical solutions to support it.

So how does the use of AI and automation deliver an enhanced customer experience?

A few key points here:

1. There’s often a trade off. For example, by collecting more data, you’re able to personalise each customer’s overall experience. That might be understanding more about candidates as individuals, more about the hiring manager’s expectations or about an organisation’s culture. But asking for the wrong data at the wrong time can completely negate the benefits of those potential outcomes. What you don’t want to do is bombard someone with questions at the first encounter – so what is it that might prompt them to be open to sharing more? Is it as a result of receiving something that is useful to them in terms of advice, be it one to one or via content? This is where understanding the customer view is so critical, and of course when you DO ask for that data, being clear about how it will be used, stored and managed is critical to establishing trust with your organisation.
2. You need to put the customer at the centre. I did a piece of work with Google recently and their approach to customer centric design was quite an eye opener. They have a lot more patience than me. But it taught me that understanding the perspective, the joys and the frustrations of being a user in any digital environment can only really be achieved by sitting with them as they experience each part of the process, taking time to understand where things could be better and where they are working well. Doing that is time consuming but so incredibly useful and gives a totally different perspective on the way people are interacting with your environment. Taking those insights and building them in to the design of a product is paramount to its adoption and success, which is what any product designer wants to see.
3. Map out each customer journey. All of us have a range of customers – and a multitude of touchpoints and interactions with each of those customer groups. Often across a huge range of separately built products and processes – think careers website, email responses, application & compliance processes, engagement marketing and in person contact to name a few. Understanding how each of these fit together, from the customer’s perspective, is important to give you a baseline for any future changes as well as the benchmark from which to measure improvements. It’s a complex project to undertake but once you have done it, the review and adjustment is much easier to do and with clearer outcomes and results.
4. Use tools to help you continually evaluate the customer journey. AB testing is an oldie but a goodie – seeing how people actually use your website for example, testing out new designs and seeing what response you get can be incredibly useful. Especially when supplemented by tools like Hotjar which can give you an instant reading on the zeitgeist of how people feel about what you’re offering or asking them to do. We’ve dumped many “fabulous” new designs and schemas for various aspects of our websites when the evidence was clear that even though we thought it was fantastic our customers didn’t!

Want to bring AI and automation into your technology stack? Here are a few things to consider

So, the key takeaways for when you are thinking about bringing automation and AI into your technology stack:

• First, work out what the problem is you’re trying to solve. Focusing on the outcomes you want will help you enormously throughout this process and help you keep a clear vision on what good will look like
• Secondly, look at the process through a customer’s eyes. If you haven’t mapped their journey with you and all the associated touchpoints along the way, that’s a great place to start. Experience all the touchpoints and put yourself in the customer’s chair – if you can, do some research directly with customers to truly understand their point of view
• Once you know which part of the process you want to improve, look at redesigning it – could it be better? Could it be easier? What are the implications of making changes on each of the stakeholders?
• Once you start to look at technology, think about how easily you can explain it to customers – will it be transparent? Does it align with your organisations’ commitments and values? Are you comfortable it doesn’t add bias into the process?
• Have a customer advocate in every project – make it their job to be the voice of the customer and think about how it feels to use that product amongst the other tools and technology you use.

To conclude, if done properly, automation should never negatively impact the customer experience – every customer – it should only enhance it.

I also firmly believe that people, not machines, will continue to play the dominant role in hiring and staff engagement. We will need to set the criteria, we’ll need to bring that magic of human nuance to the table, and we need to build the person-to-person relationship which is all that ultimately matters when our customers make career and hiring decisions.

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