First up, how can data help recruiters find developers?Everything! Analysing your own data, incorporating insights from external data and using predictive analytics tools can save you time and money. And it can result in more successful hiring decisions and happier employees.
Analytics enables you to confidently double down on your strengths and eliminate the areas where you’re weakest so you can meet every talent need of your organization.
- Analyse trends in potential candidate demographics and candidate profiles
- Analayse and forecast trends in programming technologies and skills
- Understand how groups of potential candidates behave online
- Identify which candidates are actively looking for a new role
- Offer competitive salary, bonus and benefits packages
- Analyse time-to-hire and identify bumps in the recruitment process
- Forecast future hiring needs
What’s the difference between data and big data?“Big data” is defined as data sets so large they must be analysed computationally. To pull your own big data sets, you’d probably need a data scientist or big data engineer. They’d need to understand at least one programming language (likely to be Java or Python), computational frameworks, statistics and a bunch of other things we can’t wrap our heads around. What we’re talking about is recruiter-friendly, not-so-big-but-just-as-useful “normal” data. The kind of data you can start collecting and analysing right now with no data-related experience.
Armed with predictive analytic insights, recruiters can not only anticipate what will happen but be able to act on it as well.
It’s not only data that’s changing the tech recruitment landscape.
Tech trends are drastically changing the way we recruit, and not only because we now all want office robot dogs. Here are three more trends you need to keep an eye on.
How to use data to create talent mapsTo give you an example of how you can use data to hire developers, we’re going to focus on “talent maps”. It’s one of the easiest trends to spot and incorporate, so it’s a great place to start if you’re a data newbie or have limited resources to hand.
In other words, literally creating a global map of where your tech talent has come from. It’s as simple as it sounds!
Hiring plans should also include “talent maps”, so companies know where to look for talent based on data from previous hires and where an organisation’s best performers are from.
Insights we pulled from our dataWe’re lucky enough to have some amazing data to hand, so it didn’t take long to create our own “talent map”. Over the last few years, we’ve placed hundreds of candidates from all four corners of the world. We also have a database of over 50,000. This includes shortlists of candidates with particularly strong backgrounds and skill sets who are actively looking to relocate and start a new challenge. So we set about pulling lists from our CRM of where each placement or shortlisted candidate was from and what their key skills were. It took us about 5 minutes to realise that in 2016 most of the UX designers we placed came from Brazil. In 2017, there was a sudden influx of strong backend developers from Turkey. And the trends kept coming! It seems simple (and it is!). But a surprising number of recruitment teams don’t spend any time looking at trends from previous hires before they dive head first into sourcing.
How have these data insights changed our sourcing strategy?After pulling the data for the first time, and realising what a big impact it could have, we decided to formally incorporate the process into our sourcing strategy. Now, before we set a sourcing plan for a new role, we look at where our previous hires with similar backgrounds and skillsets were from, and start our search in those countries. Some other trends you could look at:
- Data trends between skill sets (for example, what other programming languages or skills Java developers have)
- How long the hiring process takes
- What day of the week and time of day job ads get the most applications