It’s time to start using data analytics to drive your recruitment process.
Everyone is talking about Quality of Hire and data-driven hiring and the latest recruitment tools designed to take your organization to the next level. Improving Quality of Hire helps you build a more cohesive, efficient, and productive workforce, while closing skills gaps and futureproofing your organizations against lack of critical personnel.
Quality of Hire is the value an employee brings to your organization and its success over time. The basic formula for calculating Quality of Hire is:
The inputs for calculating Quality of Hire can range from a candidate’s apparent cultural fit, their past performance at other companies, feedback from their former managers and colleagues, and more.
A complete Quality of Hire solution also draws n data from your existing employee pool, including current performance ratings, team fit, and hiring manager satisfaction. The more data you integrate, the more factors you can include when calculating Quality of Hire.
However, integrating all of your data and processes at once can seem like a big ask. The most important thing when it comes to starting your journey up the hiring intelligence maturity curve is to take a first step.
Crosschq has built the most effective, integrative Quality of Hire Analytics solution. We help you collect, filter, and analyze all employee and candidate data to drive intelligent recruiting processes. However, we know that signing up for a major recruitment data integration can feel like a huge commitment to make if you’re just now starting to seriously think about Quality of Hire as a corporate KPI.
That’s why we made getting started with Quality of Hire easier. Now, if you aren’t quite ready or able to do a full integration that includes your HRIS and post-hire data, you can still get Quality of Hire data.
Just like it’s easier to crawl before you walk and walk before you run, Crosschq’s latest Quality of Hire solution lets you get started with hiring intelligence without getting overwhelmed. Compared with other off-the-shelf solutions, Quality of Hire Analytics lets you do more with less, reducing your time and effort investment by giving you a simple product that basically runs itself.
While our complete Quality of Hire Analytics solution will give you the most robust and actionable insights, you can still get solid, actionable results. So, if you have limited resources, don’t have access to HRIS and post-hire data, or need to get up and running fast, this is for you.
Now, you don’t have to worry about grabbing every single scrap of data from everywhere. Instead, all data required to get started with a QoH model is collected from your ATS (for employee metadata) or via our Voice survey campaigns (for tenure/retention data). Enjoy codeless implementation: our out-of-the-box ATS connectors install in just a few clicks.
Simple surveys give you more data without tying up key staff; 60-second surveys automatically collect performance and tenure information from hiring managers. Additionally, campaign surveys are automatically triggered via hire events in your ATS – you’re fully automated, with no manual uploads or interventions required.
Do you (and your higher-ups) love charts and reports? While you’ll be getting fewer of these from this lighter version than you would with Full QoH Analytics, this can still get you 90%+ of the way there, with user-friendly charts and reporting options.
The Full version of our QoH solution does provide you with more reporting, thanks to additional data from post-hire data, HR operations, and your HRIS. You’d be able to see multiple post-hire QoH outcomes (quota attainment, patient satisfaction, code quality, etc). Again, this fully integrated version is more resource and time-intensive but will give you more insights.
You’d also be able to implement custom QoH modeling, whereas the previously mentioned lighter version doesn’t include the ability to weight QoH outcomes based on the importance of outcomes to your organization.
Full QoH Analytics provides advanced processes, like predictive modeling, and machine learning capabilities such as correlations, regressions, and advanced analytics.
If you decide to stop at the first step and aren’t able to do a fully QoH Analytics implementation, you won’t have the ability to complete segmentation and filtering based on candidate/requisition descriptive data vs employee/post-hire descriptive data (department, hiring manager, etc).
There are four simple steps to calculating Quality of Hire. If you’re using the Full version, you’ll be able to integrate HRIS data (performance data), but if you’re not, you’ll substitute survey results.
Step 1:
Use ATS data as well as employee engagement surveys, employee self-assessments, and satisfaction surveys from peers and managers to gather consistent scores that can be used in QoH calculations.
Step 2:
Transform all input scores into an equivalent scale (preferably a percentage or a whole number on a scale of 1-10 or 1-100).
Step 3:
Calculate by adding all of the scores together in a decimal format (80% would be .8), and divide by the number of inputs. Then multiply by 100 to arrive at the official QoH score.
Step 4:
Compare QoH scores to your own internal previous benchmarks as well as external benchmarks. Our recent Crosschq Q Report showed that average Quality of Hire measures at 73.0, with top tier companies ranking in at an average of 81.4 and lower performing companies at an average of 58.9.
Again, with the full QoH solution, you’d be adding in post-hire performance and HRIS data, but the lighter version still gives you plenty to work with when tracking Quality of Hire KPIs.
While traditional recruiting KPIs focus on cost, efficiency, and hiring process satisfaction, Crosschq pulls out the data that really matters when it comes to your recruiting teams’ impact on your business:
These two metrics are similar, with time-to-hire being a subset of time-to-fill. TTF starts when the job requisition is approved, while TTH starts when the ultimately chosen candidate enters the recruitment pipeline. Both metrics end at offer acceptance.
Benchmark: The average time-to-fill is 44 days.
Cost per hire is how much expense your organization incurs filling a role, and it can be an enlightening QuoH metric. This doesn’t just include recruiter costs or hiring salaries and bonuses, but the costs of lost productivity while a role remains unfilled.
Benchmark: The average cost per hire is nearly $4,700.
The offer acceptance rate is the number of offers extended divided by the number accepted and is one of the classic QoH metrics. A poor acceptance rate indicates problems with the hiring funnels. A common issue is delays between interview and offer, leading the candidate to accept a competitor’s offer.
Benchmark: The average is 70%, but strive for an offer acceptance rate of 90%.
NPS stands for “Net Promoter Score” and is a way to measure how survey respondents score their experience across a scale of one to ten during the hiring process. The responses should then be divided into three categories:
The general formula for calculating candidate Net Promoter Score is:
cNPS = % of Promoters – % of Detractors
Hiring managers are asked to score their experience with the recruiter team. Candidates are asked to score their experience with the recruitment process. NPS is used across industry as a QoH metric.
Benchmark: Scores between 30 and 70 are considered good, while scores above 70 are considered excellent.
Love data and visual graphs? Check out our Ultimate List of Recruiting Benchmarks.
If you’re not ready to run with a full analytics integration for Quality of Hire, it’s OK to take baby steps.
Crosschq’s QoH gives you tons of valuable candidate data delivered in highly visual, easy to act upon reports, even if you are not doing a full systems integration. You’ll still be able to:
Learn more about Crosschq Quality of Hire Analytics, and how we can help you get started with QoH today. One of our representatives will be happy to schedule your free demo.