A powerful weapon in the war for talent!!!
We will let you in on a ‘not so hidden secret’. If you are among one of the many teams out there not using analytics in recruitment, then you’re missing out on a virtual gold mine of valuable information. A data-driven approach to recruitment is an absolute must in today’s talent environment. Especially if you hope to consistently and efficiently hire the best candidates. These days, it seems like nearly everything is powered by data—especially when it comes to business.
The world of recruitment is no exception, and talent data is almost certainly here to stay. 84% of recruiting professionals think analysing data to drive decisions will become significantly more common over the next five years. An increasing number of recruiters are already turning to recruitment analytics to put the right people in the right roles, and to do it in the smartest way possible.
Hiring managers have started to realize they can use data to pick up on patterns and predict future success when it comes to expanding their team. They can look at everything from the responses a person gave during their video interview to their educational background and use these pieces of information to predict which candidates will be successful in the future.
Instead of guessing the type of individual who will make the best addition to the team and hoping they’re right, hiring managers have come to rely heavily on facts and figures to guide their choices as they pertain to talent acquisition.
Technological advancements have allowed the talent acquisition process to become much more streamlined and pleasant for both hiring managers and job seekers alike. An increase in available data has also enabled it to become a more accurate process as a whole.
Recruitment analytics, plays an increasingly important role for recruiters and recruitment managers. Recruitment analytics can help to make better, data-driven choices when it comes to sourcing, selection, and hiring. By embracing data-driven hiring, you can make your recruitment process more effective and more efficient.
If you’re a bit hesitant about jumping into the scary world of recruitment analytics, then you may be interested in hearing some of the companies who are actively embracing these tactics. Names like Google, Cisco, Sprint, and Deloitte all use recruitment analytics to drive their decision making and hiring processes, and do so with industry-leading success. That’s because the benefits of analytics in recruitment over traditional hiring are endless. So, let’s dive in!!
What is Recruitment analytics?
Recruitment analytics is a part of talent analytics that involves tracking, measuring, collating and analyzing candidate, and employee data to make better hiring decisions. Many of today’s recruiters utilize analytics to produce actionable insights that enable them to make data-driven choices around candidate sourcing and selection. In fact, 78% of large companies rate people analytics as both urgent and important for their business.
Let’s take look at Google. Google has become the second most valuable firm in the world because it focuses on innovators and a data-driven approach to people management decision-making.
In fact, their Chairman reports that they operate on the principle that “All people decisions are based on data and analytics.” And rather than considering HR to be too soft or difficult to measure, he states “We apply the same level of rigor, analysis and experimentation on people… as we do the tech side.”
How can recruitment analytics improve your hiring process?
Today nearly all forward-thinking organizations embrace recruitment analytics to make data-driven hiring decisions. Why do the vast majority rely on recruiting data? The benefits speak for themselves! Recruitment analytics can significantly improve your hiring efforts by:
1. Making the process more efficient
Recruiting analytics can help you identify a myriad of opportunities to improve your hiring process. By analyzing candidate and employee data, you can effectively pinpoint hiring bottlenecks to make the process better across the board. Doing so will not only streamline workflows and allow you to work more efficiently, but also decrease hiring costs and give you more room in your recruiting budget to try new things.
2. Improving your quality of hire
By using analytics to make data-driven hiring decisions, you can identify the top candidates, analyze what your best hires have in common, and repeat the process as necessary. Doing so will help you better match candidates to open roles you’re hiring for, improve your overall quality of hire, and reduce turnover .The use of candidate and employee data allows recruiters to reduce spending on channels that don’t bring in high-quality candidates. It’s not necessarily about hiring cheaper but hiring smarter. Optimizing your recruiting costs will help make your hiring process smoother, stronger, and more cost-efficient.
3. Tracking performance
Recruitment analytics can help shed light on how you’re tracking against your Key Performance Indicators (KPIs). By gaining insights into the performance of your recruiting team, you can make improvements and optimize workflows for efficiency. You can also measure your performance over time and compare them to industry benchmarks to see where you stand.This can also act as pointers for technology related interventions which can potentially transform or improve the recruitment processes.
4. Improving diversity
Diversity recruiting proves challenging for many organizations; however, with the right data, you can track your diversity initiatives over time and make changes where you need to. For example, recruitment analytics will break down demographics like gender, orientation, ethnicity or veteran status during each stage of your hiring funnel.
1. Accurate Forecasting
Part of being a recruiter is planning ahead and anticipating talent and skills gaps in advance. Predictive analytics are especially useful for preparing for the future and making realistic estimates in terms of your anticipated recruiting budget, time to hire, cost per hire, hiring frequency, and other important details.
Conclusively, recruiters need to transform to meet evolving business demands. Data analytics is the key to showing a precise picture of hiring needs, candidate attraction, and successfully predicting which campaigns and approaches will attract the right talent.
The future is clear – injecting data and analytics into recruitment processes will be your most powerful weapon in the war for talent.
Challenges with Recruitment Analytics
· Size of the data set-The primary challenge with recruitment analytics is the type and size of the dataset. Most organizations use data they collect about their own hiring. Now this makes sense when a company is hiring thousand or more candidates but for smaller organizations their own datasets are not large enough. This creates a challenge making reliable deductions by analysing the data.
· Lack of open source primary data- The other issue is with getting access to good quality primary data. In most cases, organizations end up engaging a research consulting firm who builds out these reports and dashboards basis some static and secondary data.
· Saas platforms providing Recruitment Analytics are still rare-Now this is where a big opportunity lies. Running an internal analytics team is a cost and so is hiring expensive consulting firms. Opportunity for SaaS (Software as a service) platforms is pretty significant here as this is a latent need with most organizations.
Reviewia is an effort to address these challenges for employers. We are soon launching our SaaS platform which would enable employers to do a host of things like engaging with talent on the platform, helping companies to respond to their company reviews and offer real time analytics on primary data collected on the platform pertaining to reviews posted by candidates about the particular organization. We would also be offering industry level reports and benchmarks which can be extremely useful for employers to refine their talent acquisition strategies.
All of this would be available to employers at disruptively low prices.