More often than not, professionals choose Talent Acquisition as their field because they love working with people—not data. It can be very hard to manage once it’s not monitored and analyzed. However, due to the advancement of technology, data has become much easier to manipulate your own advantage.
Organizations and their teams are already basing most business decisions on data. They use data to drive increased outputs from lead generations, reports, and customer feedback- this is called a data-driven strategy and considered one of the best practices companies are now utilizing.
With re-occurring bottlenecks on traditional methods such as inaccurate hiring decisions that can be based on gut decisions or multiple job channels that are hard to track down in one sitting, recruiters know by heart how difficult it is to solve these. These steps might cost exponentially when not managed carefully-unless you have a super team of recruiters that still might cost a lot and that is why recruiters are now also learning to practice data-driven recruitment.
What is Data-Driven Recruitment?
Data-driven recruitment is the key to attracting and keeping the right talent needed to meet business objectives — and hiring them at the right price. But what is data-driven recruitment? Data-driven recruiting is an approach to recruitment by using several software tools and equipment to produce data based on your current channels. By using a large talent pool as the data available, you can narrow down the best candidate for the position, in each process, by letting software and data decide.
As the recruitment process goes, you will have more access to analytics and new metrics such as time, quality, and speed of the hiring process that you can use to your advantage.
Technologies like an Applicant Tracking System (ATS), HRIS, or performance management platforms, for example, are some of the proponents of this new trend and approach to recruitment. They contribute a huge part in the daily cycle of work of recruiters, gathering huge amounts of data while organizing it, making it a staple practice in the field.
What do the benefits of Data-Driven Recruitment look like?
Like any other work initiative or idea, practicing the data-driven approach will have its own benefits, depending on the level of skill and effort your use.
When you have already mastered the art of using data for your own recruitment process and let objectivity be the focus of your decisions, then will be some major benefits that you may receive. Still, results vary but here are some that you will be receiving:
Decision Making from actual numbers-not “from the gut feeling”
Most of the time, recruiters experience the feeling of getting torn between two great candidates. At the end of the day, only one candidate will be chosen. Most of the time, it leads to recruiters mixing their personal emotions and biases towards the candidates, creating “a gut feeling” final decision.
In these situations, using a data-driven recruitment strategy will immensely help by showing all of the available variables. You get to find the hidden pieces of information from his resume that might result in the applicant being pushed in the far back or front of the line. You can easily separate the qualified candidates from the unqualified candidates making your decisions become more logical and objective-based for your hiring needs.
Improve the Quality of Hire
More often than not, it takes a good amount of time and effort to find good talent in the market. But by making decisions more accurate and objectively, based on data and analytics, you will be able to hire more efficiently and accurately on quality hires; important benefits that can also change the quality of your work and improve the hiring process.
To really bring the best out of a data-driven approach in the recruitment process, always find the patience to analyze your data so as to gain a grasp of all of the variables available. Who are they? Where did they come from? Traits and personalities they share.
Analyze these data that are consistent with your top hire, and focus on those going forward.
Decreasing Hiring Costs
If your main goal is only on the variables that lead to the top candidates and eliminating as much waste or churn as possible, then you should also start to consider the cost of hire
Whenever you take a candidate into the hiring process, you are using the money of the company. From the platforms that you use and advertise on and as well as the software tool for organizing your database. With data, you can easily pinpoint and remove the necessary churn and bottlenecks. Churns such as platforms that are not really profitable in terms of the quality of hires you get from them.
This could save you lots of money in the hiring process, which in turn, can be used for more successful recruitment programs and ensuring that you are hiring with the right spending as well.
Improve the candidate experience
Analyzing and experimenting with your current recruitment process might be a good way to find great ways to improve the overall candidate experience.
By playing around with your current database and tools, you get to see the bigger picture and find pain points that affect candidates in your application process. For example, one process takes a longer time to be finished before the next step, causing candidates to be impatient and will be converted into withdrawals.
By identifying these kinds of data points, you can remove such tedious processes for your best candidates in your application process, thus, you pave a new and innovative way to make the best candidate experience for your incoming new hires
Improve vacancy and hiring forecasts
The more time and effort you invest in analyzing your databases, metrics, and analytics means that eventually, you will have a clear sight of the pattern of your recruiting process.
Being able to understand how the recruitment team and HR processes of your organization is a major impact. It will help you also understand what’s missing, what should be done, and make major improvements in the recruiting process. One particular aspect is forecasting future openings and job positions along with the associated labor costs. You will eventually know when to track and pinpoint the exact moments within the year your employees will leave, leading to lesser turn-over rates and better output.
These pieces of data will prove invaluable for your team and the hiring managers in the long run
Speed up the hiring process
Another great benefit from what data can give is speeding up your application process. Imagine having already a predicted timeline to tell your hiring managers before even starting. Likewise, this data-driven recruiting strategy can reveal the bottlenecks slowing down hiring and inform you of the right actions to take to fix them.
Deliver On Recruiting Capacity
Recruiting is a fine balance: over-hiring can create unnecessary burdens in prioritizing candidates while under-hiring can reduce productivity and slow the progress of the company output.
In order to stay on track, recruiters need fact-based hiring plans that are continuously updated to reflect the most current state of the company. Through constant collaboration and communication of teams such as Talent Acquisition and Finance, it determines and creates forecasts and accurate hiring plans in the long term process, based on historical data of employees such as employee turnover, interdepartmental movement, and respective hiring successes.
In addition, this type of planning, which incorporates data from workforce metrics & analytics, provides a full picture of spend. Instantaneously, information about your current budget will be available, leading to the proper allocation of your company’s budget as you will be able to allocate more on important matters and activities.
What type of recruitment data should I measure?
Data can vary from one variable to another, depending on the field it is used. In the recruitment field, it can vary from your job channels to your internal databases. Knowing these data fields in recruitment and which aspect should be prioritized and focused on will lead you into making a new data-driven hiring process.
There are multiple metrics that are available in recruitment but to summarize it, here are the three areas:
- Time-to-hire recruitment metrics like time to acceptance, time to hire, approval rate, and time per stage.
- Quality-per-hire recruitment metrics like submission to acceptance rate, source of hire, applications per job, candidates per hire, and retention rates.
- Cost-per-hire recruitment metrics like hiring costs, applications per channel, talent pool growth, and advertisement performance.
It’s important to not get bogged down with the volume of KPIs and data that is available to you in your HR systems. Sit down with management and your team to talk about what KPIs and metrics should be the current focus of your hiring processes
If what your current need is reducing costs, focus on cost-based recruitment metrics and optimize your hiring strategy around improving efficiencies on that aspect. If you want to improve the overall quality of your hires, you may want to do a deep dive and analyze metrics surrounding the hiring funnel, employee engagement, and retention aspects. Focusing a metric on a given schedule could prove useful to your company as you are able to bring your hiring process to the next step by eliminating any pain-points in a fast-paced manner.
Which tools should I use for a data-driven recruiting strategy?
There is an abundance of tools that can be utilized for a this type of recruiting strategy, it just so depends on the size of the organization and the actual hiring need. ATS’, CRMs,
Large, enterprise-scale companies, for example, may opt for multiple HR systems to process the sheer scale of data being created by sourcing and analyzing candidates from numerous job channels. However, This could result in recruitment data silos and a lack of coherence into how to use the information stored in multiple locations. Recruiters can, therefore, lack the holistic view of their processes needed to truly optimize and innovate their techniques.