If your team is one of the many out there that doesn’t use data analytics in recruitment, you’re losing out on a veritable gold mine of useful information. I don’t want to sound dramatic, but in today’s talent environment, a data-driven recruitment strategy is a necessity. especially if you want to hire the best applicants effectively and consistently. We’ll also show you where to get started in this post.
If you’re not sure if you want to jump into the scary world of recruitment analytics, you might be interested in hearing about some of the companies that are already using these methods. Google, Cisco, Sprint, and Deloitte use recruitment data to make decisions and hire people, and they do so with the best results in their industries.
That’s because there are so many ways in which data analytics in recruitment are better than traditional hiring. Here are just some:
- It gives you an unbiased look at how well and how much your recruitment activities are worth.
- It helps you keep track of candidates with a lot of potential, so you can actively try to get them hired.
- It lets you make a large pool of candidates or hires, or a permanent record of all candidates and hires that you can always go back to.
- It makes proactive recruitment possible, which leads to better and faster decisions about who to hire.
What are recruitment analytics?
With the help of data and predictive analysis, recruitment analytics lets companies hire people more quickly. Analytics and the methods that go along with it are as varied as the technologies that are used in the recruitment industry.
For the purposes of this article, we’ll focus on predictive analytics in recruitment. And to get you interested in learning more, you might be intrigued to learn that forecast has been shown to focus on saving up to 23 hours per week of manual work, most of which is spent short – listing and pre-screening candidates.
How to start using data analytics in the recruitment
Now that you know what data analytics can do and what it can do for you, you can start to use it.
1.Pick your technology stack
On the market, there are a lot of HR platforms and data analytics tools to choose from. In the end, no one solution will work for everyone, so you’ll need to do some research to figure out which one is best for you.
lets you store all information about incoming candidates on the platform and use powerful analytics, tracking, and reporting to get actionable insights from data. Some of Recruiter’s most important features for this involve tracking job success, candidate conversions, and KPIs and team performance through easy-to-use dashboards.
2.The process of data analytics
The next step is to start the data analysis lifecycle once your tech infrastructure is set up and you have a plan for what to measure and why.
This process kind of looks like this:
- Getting information
- Cleaning up the data before using it
- Setting up a type of analysis
- Getting the model ready
- Trying to make predictions
- Using what you know
The most important things for you to do are to collect the data, make sure it is clean and correct, and then act on the predictions and insights that your platforms give you. This happens when you make sure that your input data only has correct and useful information for your candidates and processes and when you say which KPIs you want to improve.
It’s just a matter of keeping an eye on the data you put in and the predictions you get back so you can make changes to your recruitment decisions and processes regularly.
3.Measure and report with recruitment analytics tools
Once you’ve set up your data analytics machine, the next step is to make a recruitment KPI dashboard so you can measure how well it’s working. This dashboard should be easy to use and only show the most important information related to your key performance indicators (KPIs).
At this stage of data analytics in recruitment, you should think about how easy it is to report on your KPIs. Chances are, your manager or other executives will want to know what the metrics say and how certain changes have affected the business. In the long run, your life will be easier if you make sure your tech stack can give you clear and quick reports.
4.Keeping track of and measuring success
Seeing Key performance metrics and reporting on them doesn’t help if you don’t change who and how you recruit. It also doesn’t matter if you set it once and never change your recruitment data as well as reporting metrics or try anything new.
When it comes to hiring people, data analytics is a game of change and small improvements. It guesses what will happen based on the information it has and what will happen if you do something. To get the most out of these platforms, you must regularly act on their suggestions, make your own changes as well as measure the results, and make sure that your data pool reflects the outside world.
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