Are you committed to a data-driven talent acquisition process yet? If not, it’s time to take a closer look at how analytics can help improve your hiring record. Data-driven talent acquisition leverages analytics on past hires to improve future hiring decisions and improve quality of hire across your organization.
With all of the data now available on each and every candidate in the talent pool (including active, passive, and internal candidates), there’s no excuse to not be using analytics to improve hiring decision-making.
Without data in play as part of the recruitment process, quality of hire can be all over the place. Using the wrong data to inform hiring decisions can cause unconscious bias, a lack of diversity, and an unhealthy company culture.
The cost of a bad hire in both new recruitment costs and lost productivity can mean anywhere from $17,000 to $240,000 down the drain if the employee quits before they become productive enough to “earn out” the cost of hiring them.
The Three Out Of Four Phenomenon
When it comes to the numbers surrounding new hires and employee attrition, three out of four seem to be the champion - and the odds aren’t in your favor.
Three out of four open seats in the average organization require filling because of employee attrition. A revolving door when it comes to new hires could mean your company is literally bleeding money just to keep seats filled.
Three out of four hiring managers say they have definitely hired the wrong person for an open position before. That’s what happens when pressure is on to fill a role, but no one is bothering to look at the data.
New hire quits
Three out of four employees leave their employer or position for reasons that could have been prevented by the hiring manager. Most of these reasons have to do with lack of or poor communication, resulting in low employee engagement.
You can leverage talent intelligence to flip the three out of four numbers and make those stats apply to retention, good hires, and engaged employees instead. To achieve this goal, you need to adopt data-driven talent acquisition practices based on analytics in order to more accurately target the best people for each job.
What is Talent Intelligence?
Talent intelligence hinges on knowing what data is important to talent acquisition, management, and equity, and using analytics to spot patterns and create models that can be used to predict performance and quality of hire. Nearly one out of four global organizations say that they have made a bad hire due to a lack of talent intelligence.
The average job posting can attract an average of 250 resumes. Even with ATS filters set to shave this number down, and rigorous automated screening processes to decrease the number of finalists who make it to the interview stage, that’s a lot of interviews.
It can be tempting for recruiters to cut corners, tighten ATS parameters to the maximum, and risk cutting out candidates that could be ideal matches but don’t hit the necessary keywords in their resumes. They may also send the first five candidates who make it through screening to the interview phase, instead of choosing the top five out of ten, or twenty.
Data analytics can help show which recruiters are actually sending candidates that get hired and last longer than 90 days (statistics show that 30% of new hires don’t even last that long.) This can help hiring managers refine their relationships with recruiters and depend on those who have proven superior screening processes.
On the recruiter side, analytics can help show the top source of hire when it comes to accepted offers, and improve their job description word choices as they A/B test descriptions. Recruiters can also benefit from analysis of where candidates self-select out of the process, and whether that number is too low or too high.
Once a new hire is secured, there’s that pesky concern about potential attrition before they manage to reach full productivity. Companies with high turnover need to take a two-pronged approach: figure out what is causing churn and take steps to stop it, while having a backup plan to refill seats as they open up again.
Data analytics can help highlight runners-up for job positions, allowing an offer to be extended quickly to a silver medalist if the first pick turns it down. With one of the most common reasons for rejecting an offer being that the candidate accepted another (better?) offer, this is a very real possibility.
Also worth keeping tabs on are applicants that weren’t quite the right fit or didn’t have quite enough experience, but otherwise seemed perfect for culture add. Just 3-6 months of additional experience might mean they would be ideally matched to a future role in the company.
Identifying attributes of high-quality candidates
Managing your talent pool can reduce cost of hire and time to hire significantly; instead of going back to the drawing board for each new round of hiring, you can revisit high-value candidates already identified, and also look for others that match their same general profiles.
The ability to benchmark and predict future performance can transform your recruitment funnel. When you are able to recognize the kind of candidates who tend to hire on, stay, and make a positive impact on a team, you can hire more of them, faster than ever before.
Analytics can also help identify candidates already in your organization who are ready for a promotion or lateral move. This can be a good way to shift someone who is ready into a role with more responsibility, and change the fillable role from a high-stakes one to a lower-stake process.
Additionally, promoting from within is a great way to keep your employees 41% longer than companies that don’t. So is offering L&D opportunities. When word gets out that you care enough to invest in your existing staff and their careers, you create loyalty that can’t be otherwise built.
Finally, diversity, equity, inclusion and belonging (DEIB) are key to today’s workforce. Three out of four job hunters (there’s that ratio again!) say that a commitment to diversity is something they look for in company policy, and can tip the scales in favor of accepting a job offer or turn them off applying completely if they feel a business is lacking in this area.
Analytics can also be useful for showing how many diverse candidates are in the pipeline, where they tend to drop out of the hiring funnel. This can cast light on what might be causing unconscious bias during the filtering, screening, or interviewing steps that could harm diversity and prevent culture add.
Reducing bias in the hiring process can improve not only diversity, but quality of hire, productivity, innovation, engagement, and retention. It can also enhance candidate experience, and boost your company’s positive profile as an employer.
Crosschq TalentWall is a powerful tool you can use to help set data-driven hiring into motion. With a dashboard that sits on top of your chosen ATS and pulls relevant information into easily digestible hiring flows, it’s the best way to get recruiters and hiring managers on the same page.
All individual pieces of data are available, for a surface scan, making it easy to see “where we’re at with hiring” by role, department, or recruiter. Bidirectional, real-time updates mean every view is correct no matter who is looking at the data and when.
Crosschq Analytics lets you check the pulse of new hires constantly using surveys, and helps break down the vast wealth of data into segments that make sense. As patterns emerge, you can use the data to drive recruitment based on the twin goals of longer retention cycles and better quality of hire.
Ready to harness the power of data-driven talent acquisition and analysis for improved quality of hire? Contact us and ask for a demonstration today.
From pre-hire to post-hire, Crosschq helps you source, screen, onboard, and measure the best talent. Fast.
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