How to be successful with recruitment analytics

How to be successful with recruitment analytics

The role of the recruitment professional has changed. The role is still about the identification, screening and hiring of the best available talent, but the role has expanded. Today's successful recruitment professional now needs to have a strong grasp of digital marketing, have the mind-set of a salesperson and be adept at collecting and interpreting recruitment data. Data analytics is now not just something that ‘might be worth looking into’ for an organisation - the ability to understand and use the data is becoming a core function of HR.

The body of evidence to support this view is becoming overwhelming. Predictions suggest that recruitment success will improve by over 300% in the next five years due to the use of analytics. Recent LinkedIn studies have found that where talent acquisition teams have used data, they are twice as likely to see improvements and three times more likely to reduce costs and make efficiency savings. 

A Gallup study looking at the impact of using data to identify top talent found that organisations that select from the top 20% of the most-talented candidates will see significant increases in productivity and sales, alongside a 30% rise in profitability and a drop, by a quarter, of unscheduled employee absences.

However, despite the growing weight of supporting evidence and a clear recognition of the importance of recruitment data, its actual use has been fairly slow to catch on. Something appears to be holding companies back, so it's time to take a look at what the do's and don'ts of data-driven recruiting are.

It's important that organisations take a holistic view of the recruitment data they hold in their hands. Data needs to be accurate, consistent and easy-to-access. If it isn't, it becomes very difficult to measure success. Data is required for all parts of the recruitment process. From marketing, to screening and onboarding, data needs to be collected from all aspects and be connected and accessible from a central location. Taking a more holistic view enables organisations to be better placed to identify trends and make informed future decisions.

Unfortunately, for many organisations the use of data really stops with its collection. Data should be being used to drive decisions. Predictive analytics, where data is used to make recruitment decisions, is empowering to organisations as strengths and weaknesses can be addressed, rather than merely being identified.

Reporting of data needs to highly flexible and configurable. Many variables need to be able to be inputted and reports formatted in a variety of ways to gain the most thorough and effective analysis from it. If reports can be configured to individual and specific needs, the particular metrics that are most useful and important to that individual can be highlighted and interrogated more effectively. It's also important to remember that data-driven recruitment doesn't require data analytics technology that is separate. Data is best leveraged when its collection and analysis is tied closely to HR. This is because HR teams are best-placed to ask the types of questions that will generate the most useful reports.

Broadening the scope of analysis can be very useful. What is known as 'surface-level' analysis, such as time to hire, is a good starting point, but so much more information could be gleaned, such as the devices job seekers use or the percentage of candidates who start - but don't complete - an application, and at what stage they leave the process.  It could well be these little nuggets of information that will inform improvements to the recruitment process and give an organisation a competitive edge. Asking 'why?' questions rather than just collecting the evidence of 'what' has happened is the best way to improve the breadth of analysis.

Data-driven recruitment requires the development of a formal analytics strategy. Establishing overarching goals and breaking these down into annual, quarterly or monthly targets will help to shape a strategy. This will also help to organise how data is used, resources managed and information reported.

Such a strategy should make it clear how recruitment is driving business results. Involving teams within the organisation who already have experience of using data to drive decisions will enable successful elements of this to be incorporated into the data-driven recruitment strategy.

It seems likely that the future of recruiting will be data-driven. After all, data already drives most other business functions. Therefore, there's no reason to say that data analytics cannot be embraced by HR teams. In simple terms, recruitment technology generates massive amounts of data; technology providers continue to make data more accessible and, when used effectively, HR teams benefit greatly from data analytics.

Embracing technology is not about replacing professionals. It is about enabling HR professionals to maximise the resources that are available to them.

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