The roundtable was informed by the findings of a study, conducted by Aptitude Research and Oleeo ‘Improving Quality of Hire through Recruiting Enablement’, which revealed 63% of businesses believe that identifying and attracting quality hires is the greatest challenge they face. It also demonstrated that the use of quality data to inform recruiting decisions made businesses twice as likely to hire strong candidates.
In fact, 72% of businesses are prioritising automated recruiting decisions for the year ahead in order to meet the needs of the business and the changing expectations of candidates, recruiters, and hiring managers. Talent acquisition and HR leaders can no longer afford to rely on reactive or traditional approaches to recruitment processes. Participants agreed – here are some of their thoughts:
How important is data to your quest to find quality talent?
- Data is key – without it, we can’t make decisions or justify them to managers and therefore we can’t prove that we are doing a good job.Core to moving to a direct sourcing model and relying less on agencies.
- Measurement can be subjective- it is not only down to the Talent Acquisition team, but also the line managers or hiring managers and broader HR colleagues.Once the candidate starts, even small things affect quality from a weak onboarding process to a lack of adequate training as well as simple things live living up to expectations, team bonding and overall culture fit.
- Quality of hire is not something that the Talent Acquisition function alone can evaluate – it is a whole company measurement. Feedback from wider HR teams is the only way to prove if the quality of hire has been good and could inspire future hires
- For the recruitment team, it is key to demonstrate that they are doing all the right things to keep candidates in the hiring funnel – i.e. have the right EVP, the right job descriptions, good nurturing processes. This is because the quality of the pre-hiring process impacts on the quality of hires we make.
- Some technology ranks the quality of hires by the correlation between different variables that are measurable – such as time spent in the recruitment process, hiring manager feedback, employee performance reviews, satisfaction surveys etc. This is useful as it helps to identify what needs to be improved but can be a double-edged sword.
- In some organisations, they are not yet looking at data to inform recruitment processes trends, instead focusing on attrition rates or verbal hiring manager feedback. This makes it difficult to pin down the factors used to judge quality of hire, especially for roles without a direct measurable goal to businesses (typically sales related). Referrals are also relied on by these companies without audit trails to avoid nepotism risks.
- For others, they are more driven by organisational targets especially for high volume roles. Here, there is less focus on quality and more on the numbers of vacancies left unfilled over 30. 60 and 90 days respectively. With stretched resources, it is considered too difficult to retrospectively measure the past, so the focus is always on the immediate future.
Are there better ways of harnessing data for recruiting efficiencies?
- Machine learning can help to unbias the process and reduce the workload as well as enhancing diversity monitoring so talent acquisition can be more proactive and less reactive. This is key to improving overall candidate experiences and journeys which in turn smooths the hiring manager experience and satisfaction rates.
- Unconscious bias can easily creep in on manual selection such as reputation of university instead of historical success metrics like characteristics for employees with high retention rates or recently promoted. Increasingly recruiters are at risk of being trapped in a cycle of only hiring the same people from the same backgrounds and forgetting the importance of diversity and inclusion in their approaches.
- It is not harmful to have ideal candidate profiles in mind but equally it is crucial to prioritise diversity in talent pools. Ideally this will come from Talent Acquisition and HR colleagues working together well – shifting focuses from just obsessing around large volumes and thinking more about improving D&I.
- Talent Acquisition should always do their best to make sure they hire the best talent throughout the funnel – it is important to mix human with virtual, consider when and how you rely on algorithms. Agencies and thus candidates are too focused on laying out CVs or answering application questions to emphasise details known to be captured by AI. New danger is that bias is creeping into systems just as much as human sifting.
- Historical data can help build better criteria for shortlisting – knowing what made successful hires stand out and be guiding lights for the next employee to join that role.
- A barrier to this is recruiters are not analytics experts and do not have dedicated data and insights departments to help. Outputs have to be as simple as possible to make reporting easy – once management can see the benefits of being data-driven, they are more likely to commit resources and provide budget.
- The models used by assessment providers have proven useful in rapid sifting built with recruiters to identify competencies, drivers and traits. This speeds up identification of candidates who appear to demonstrate the most potential in vacant roles and is sufficiently scientific to be mainly unquestioned..
- But, these tools are equally only as good as the people who use them. Data should be credible because it is easy to manipulate and to make it show whatever you want it to show in some instances.
- One idea is to work with an occupational therapist to help ensure a widespread understanding of what your own idea of good is – especially as candidates are more casual now and apply for many-jobs at once. You can also benchmark against competitors in your industry where national data is available.
- Saving administrative time is vital for recruiters looking to stop the majority of tasks being done manually. This will help them in regards to attracting, engaging with and selecting the best suited candidates for each role. Recruiters enjoy more time on nurturing relationships with promising candidates than reporting and data analysis. This can be utilised regardless of pipeline capacity and can make progress on areas like D&I, Time to Hire and onboarding more automated and seamless.
It has never been more important for companies to get their recruitment right. In a COVID world, many are operating with reduced personnel levels, roles are being redefined and to survive, let alone thrive, companies are having to innovate and cope with unprecedented levels of change. Every person hired needs to be the right person.
The roundtable helped to validate our research report and clearly shows that the use of data is critical if businesses want to find, engage and attract this very best talent. Worryingly, decision makers are either not confident in the data they have, or they are being supplied with inaccurate information which jeopardises their ability to meet the fundamental recruitment challenge their business faces.
Through a greater understanding of the data, more control over what touch points are measured, knowing what attributes a ‘top applicant’ has, and the use of Recruiting Enablement, businesses can still fight for the highest quality candidates. A huge thank you to all who participated in this roundtable discussion.