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Dean Sadler



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Recruitment technology: hiring for impact using machine learning and data analysis

How better data analytics can help address critical skills gaps.

Data is everywhere. It’s powering some of the most exciting businesses, providing insights that supercharge products and enrich the customer experience. HR departments are sitting on a data goldmine, with all sorts of information on career history, skill progression, personality traits, training or reviews. Until now, however, this data has largely remained untapped or siloed within separate platforms.  

Data-driven approaches mean hiring managers can hire for genuine impact, not just to fill empty chairs.

Solutions are slowly emerging to bring all of this data together, and HR technology is being built that talks and integrates with each other. When combined, the data can be used to revolutionise the HR and recruitment processes we use today. Using integrated APIs, combined with machine learning (ML) and data analytics, we can analyse thousands of data points to create a bigger picture of who organisations really need to hire, and how organisations can hire better.  

This approach can be used to address problems and issues, such as improving a team’s blend of personalities, by using analytics of previous productive teams and their personalities. It can even be used to help tackle skills gaps or talent shortages, for example, by finding talent that may fit the persona required, but that can be skilled up quickly to match the technical requirements too.

This means you can hire people based on impact, not within the first day or month, but what that candidate will be capable of in the next six months, a year, or beyond.  

Hiring for impact  

This approach is vital in the current market, where applicants are turned away for not being qualified enough, but then businesses struggle to find the talented staff they’re looking for. That’s because sourcing the right talent with the right skills, personality and experience, and then retaining them, is a real challenge. Data-driven approaches mean hiring managers can hire for genuine impact, not just to fill empty chairs.

New data solutions and cutting edge technology are making it a ‘fairer’ game when head hunting. 

For example, while a candidate might not be 100% right at initial application, using ML algorithms, businesses can access data of similar candidates and see how, with the right training, they could be moulded in a year or two. That candidate you may have rejected in the past could in fact be perfect for the role, and help drive long-term company growth. Further, thanks to the abundance of insight into how candidates really work, managers can ‘test the waters’ to see if their personalities match with the wider team before offering a role. Hiring based on their ability to fit in with the team is just as vital as the skills they hold.

Employee retention is equally as important. Current employees must be able to develop skills and progress in their roles or they will look to move companies. ML powered performance management tools can be used to form the basis of an employee’s development programme and help shape their career goals. Understanding how to use data to attract the best talent means you are also making the effort to retain the best talent already employed at the company.  

For example, employees will feel valued more if they have clear progression plans. Using data, you can show how a similar employee advanced in their careers by not only performing well, but by taking different training courses and developing new skills. This also helps to make development processes more efficient and effective.  

The skills gap  

This is important because UK businesses are facing critical skills gaps. Not combating this could lead to a loss of around £120 billion by 2030, which would have a detrimental impact on productivity and talent acquisition as well as the economy.  

ML and data analysis could help tackle this. Imagine if businesses could track a person’s employment journey from the outset, and then use that to replicate and train similar candidates at the start of their own career path? Candidates could also access data that reveals which skills they would need to develop in order to unlock further value on their career journey. Harnessing data in this way could help reduce the ever-growing skills gap, by opening up career avenues candidates may not have previously considered and matching hiring managers with the best undiscovered talent in the market.  

The age of data and HR

Data is changing the world of HR and recruitment for all parties involved. Not only are employers sitting on a goldmine of data about candidates, but candidates have access to lots of technologies that improve their chances of finding the dream job.  

New data solutions and cutting edge technology are making it a ‘fairer’ game when head hunting. Data insights coupled with chat bots, video interviews, language translation etc. can further bring a candidates experience and ability to life and remove bias in the hiring process, helping both recruiters and candidates focus on showcasing transferable skills and their personalities over experience – all of which could be overlooked if solely relying on a CV.  

Don’t be afraid to test the waters with data analytics and ML software. The mountain of data available will only continue to grow in the hiring process and the only way to ensure the best hiring impact is to make the most of this valuable resource.  

Interested in this topic? Read People analytics – how candidate assessment tools can refine your recruitment process.

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