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To quote eminent author and TED talk veteran Prof. Dan Ariely, “Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.”
This is particularly true regarding data in the recruitment sector. Or, to take it a leap further forward - everyone in recruitment thinks they are doing it, but they’re probably not doing it as well as they could.
Building a large data pool
The recruitment industry tends to rely on too small a data pool for meaningful statistical analysis. Furthermore, the data analysed is often based on a recruiter’s own data, typically input hastily by a salesperson and without reference to external industry trends.
Even if you were able to look at every single job you post, every month, you wouldn’t be able to build a statistically significant analysis. To give a more meaningful picture, look at those who are looking at the industry as a whole. Companies such as Cube19 tap into thousands of sources with more than 150 million data rows - which can give true industry insights and allow you to develop predictive modelling to understand candidate behaviour patterns.
Understanding the candidate psyche
Analysing the right data can help the recruitment industry understand the candidate mood - and can help predict what’s coming next. First, you need to build a framework to make sure that your data is specific, useable and actionable.
Organising the data you’ve already got is a good starting point, so you can decide what external data to source additionally. It’s not unusual for agencies to have tens of thousands of candidate CVs in their database - so make sure that it’s searchable and sorted into categories. This is the point where you can begin to spot trends and develop talent pools.
Consider your target audience and the sectors and regions you operate in and build your analytics accordingly. For example, if one of your focus areas is engineering, you’ll want to first of all look at your internal data, which might tell you that, say, your Sydney office is outperforming your Melbourne office. You can then bring in external data to understand the different salary points across Australia, how the competition is operating and what drivers there are in different locations. Mapping these two sources will deliver both the big picture and the granular detail that you’ll need to make informed decisions.
Empirical decision making
For the first time, data and analytics have made the boardroom agenda, rather than being dismissed as the sole province of marketing. The C suite has woken up to the fact that data is the single most effective decision-making tool available to them. Properly collected and analysed, data enables better insights, clearer decision making and more streamlined processes within a business. Taking decisions led by hard facts and measurable trend patterns rather than non-empirical bases is key to success.
For recruiters, this idea turned databases into goldmines. It’s apparent that data could be used to better source and place candidates with increased accuracy and efficiency.
Being able to challenge the norm and find a new and better way of doing things relies on solid, data driven research. It’s no longer enough to rely on quick-fix, transactional offers to solve clients’ pain points. Interrogating reliable, consistent and measurable data sources to build hard facts is the only way to understand your market, know your customers and their business inside out and create a narrative and solution that resonates with them.