Talent acquisition and hiring are the key functions of every business, regardless of the size or industry. This is why recruiters and hiring managers need to stay ahead and improve employer branding, onboarding, and retention. Data driven recruiting offers the tools to collect, analyze, and leverage data to take your recruitment strategy to another level.
What is data driven recruiting?
Data driven recruiting is a scientific approach to collecting, analyzing, and using analytical data about candidates to make data driven decisions throughout the hiring funnel.
Here’s a comprehensive guide on why and how to use data analytics in recruiting:
How does data affect recruitment?
Recruiting is a multi-dimensional process with a number of elements affecting every stage of the recruitment funnel. Using the right metrics enables recruiters to streamline and optimize every step of the funnel to increase overall effectiveness.
The goal is to attain the best possible return on investment. Data driven recruitment empowers this journey through the proper accumulation and utilization of data.
Here are some statistics that prove how recruitment data can help identify flaws and enhance the hiring process:
- Nearly three in four employers (74%) say they’ve hired the wrong person for a position.
- Companies with a strong employer brand see 50% more qualified applicants and take 1-2x faster to hire.
- The best developer at Apple is over 9X more productive than the average software engineer at other technology companies.
- Talent acquisition teams with mature analytics are 2x more likely to improve their recruiting efforts. They are 3x more likely to realize cost reductions and efficiency gains.
- 89% of employers think employees leave for more money but in reality, only 12% do.
- Nearly 60% of candidates have had a poor interview experience. 72% of those candidates shared that experience online or with someone directly.
Undoubtedly, the bottom-line impact of top talent is real.
“The recruiting organization that figures out how to extract the value of data will define the future of talent acquisition.”
– Brendon Browne, Senior Director of Talent Acquisition at LinkedIn
What can you measure with data analytics in recruitment?
There is an abundance of data that recruiters can look at; however, every organization has different needs that determine how do you use data as part of your recruiting strategy. Let’s look at some of the key recruitment metrics related to tech roles that every hiring team needs to measure. This is a good starting point to optimize the recruiting and onboarding process using a data-driven approach.
Cost per hire
Even though recruitment is the foundation of any organization’s success, there is still a push to reduce the cost of hiring. The best way for companies to get a real insight on the spend is to analyze the cost per hire (CPH) metric. It encompasses all recruitment costs divided by the number of hires. What’s more, is that you can track this year-on-year to determine if there is any considerable change.
The formula used is: CPH = Total recruitment cost / Total number of hires = Total internal cost + Total external cost / Total number of hires
Incorporating both external and internal costs gives you a complete picture of your recruitment cost. Internal recruiting costs would be any internal expense such as employee referral incentives, recruiters’ salaries, and interviewing costs (number of hours multiplied by the hourly salary of involved employees).
External recruiting costs refer to marketing costs, recruitment software and events, and external recruiter agency fees. This metric is good to calculate as a monthly or annual cost per hire result.
Time to fill
Time to fill analyzes the amount of time required to fill a position. Count the days from advertising the job until a candidate accepts the job offer. Do not confuse this metric with Time to hire, which estimates the time from the first contact with a candidate (either through an application or sourcing) until you hire them.
Time to hire indicates the speed at which the recruiting team identifies a quality candidate and moves them through the recruitment process. Whereas time to fill supports the process of creating a recruitment strategy and can highlight if the initial advertising isn’t working. Both metrics can identify if there are any bottlenecks in the hiring process. Time matters because it affects productivity, which in turn affects revenue.
Quality of hire
Quality of hire (QoH) presents the value that a new hire adds to the organization i.e. the new hire’s performance compared to pre-hire expectations. Determining the QoH in the first year of an individual shows how recruitment practices deliver outcomes. This hiring metric ensures filling the right position with the right talent.
While there is no exact calculation for measuring QoH, there is a general formula that recruiters can adapt and customize based on what the organization perceives as performance factors.
QoH = (Indicator A% + Indicator B% + Indicator C%…) ÷ Number of Indicators
Measure these indicators with the scores you get from measuring time to productivity, onboarding, manager surveys, team productivity, and team reviews. You can also look at the speed at which the employee is promoted, as well as the end of probation reviews.
Alternatively, you can use the Net Hiring Score. This employs a 0-10 scale with 0 being poor and 10 being excellent. The manager can rate the employee on their performance and job fit, and the employee can rate if it’s a good job fit or not.
The percentage of great fits (scaled 9 or 10) is subtracted from the percentage of poor fits (0-6) and then multiplied by 100. If the result is <0, too many poor fits are being hired but >0 indicates more great fits are being hired. Zero being neutral.
Job Performance and Efficiency
Efficiency metrics in recruiting track an employee’s performance and productivity. These include work quality, work quantity, work efficiency, and organizational performance metrics. There are over 20 employee performance metrics. Recruiters can select the ones that are relevant to the organization and which ones can be practically implemented.
The most common method has been an appraisal between employee and manager translating the business goals into the employee’s goals. These objectives look at appraisals using points or a certain weight to measure employee’s progress.
Another method that can be combined with objective and subjective appraisals is the 360-degree feedback or multi-rater survey. This includes rating an employee on their performance by colleagues, managers, customers, and other parties that are part of the professional interaction.
Fairness
Fairness, diversity, and inclusion are becoming more important than ever in recruitment analytics. Diversity dimensions can extend beyond gender to include race, nationality, education level, age, disability, family status, employment status (full-time, part-time, flexible), immigration status, and much more.
These metrics should be pertinent to the organization’s local context and the correct diversity issues should be targeted. The legal, political, historical, and cultural environments of nations are different and determine which diversity metrics are relevant. While gender inequality is a global issue, religion and ethnicity may be predominant in certain parts of the world. Developing a multicultural organization that’s all-inclusive can be challenging but data can highlight where a company is being exclusive or biased. Identifying the voids is the first step to adapting and developing diversity in recruitment.
What are some advantages of data driven recruiting?
Strategic recruiters who take the data approach can make a significant impact in transforming the recruitment process into an innovative strategy. Data driven recruitment helps businesses make informed data driven decisions. This positively impacts revenue, offers a great experience to the current workforce, the potential candidates, and improves the overall performance of the organization.
Below are some of the additional benefits of data driven recruiting:
1. Minimized reliance on emotional decision-making
Algorithm-based recruitment decisions are efficient and objective. It reduces the pressure on recruiters to make gut-feel decisions that have no concrete basis. Emotional decision-making can be unconscious where a candidate’s status may come into play with the interviewer. Even though managers want to think they are rational, hiring decisions are often based on feelings and not on facts.
2. Decreased cost per hire
As you optimize time to fill and hire with the help of the right data analytics, the cost per hire drastically reduces. By using the right recruitment tools, you optimize each cost source, internal and external, along with the reduced time and resources in hiring.
When you analyze the recruiting data the right way, you also open doors to new initiatives. For example, looking at the days you spend manually filtering and evaluating each candidate for a job, you might want to consider using a skill assessment tool to cut your time and efforts by 80% and focus only on interviewing qualified candidates.
3. Decreased time to interview
As the old adage goes, Time is Money. Through being able to swiftly screen top candidates, the time to interview for the hiring managers reduces. This reduces the time to hire and has a knock-on effect across the entire recruitment process. A long, drawn-out recruitment process negatively impacts candidate experience as well as the productivity of the organization. It also highlights the level of efficiency of the recruiters. Taking too long to interview means taking longer to fill a position. Data fights this and gives recruiters a chance to move faster at every step of the way.
4. Increased interview to hire ratio
The interview to hire ratio determines the number of candidates selected for interviews versus the number of candidates hired over a selected period.
An obvious by-product of the data-driven approach to hiring is – better decision-making – across the recruitment funnel. An optimized recruitment funnel with reduced time and cost to hire also results in enhanced candidate experience, which in turn increases the overall interview-to-hire ratio.
5. Increased productivity
Data-driven recruitment is fundamental to improving the entire hiring process that equates to a shorter process, quality candidates, and a decrease in time and money. HR analytics goes beyond just hiring. It allows you to monitor employee performance and development throughout their life at the company. You can monitor retention rates, turnover, identify pain points using data analytics and improve processes across the board to nurture and retain your top performers.
Data at each step of the recruitment funnel
Recruitment can be a fun process when you have the right tools to be successful. Analyzing your recruitment funnel with data can bring up hidden opportunities and uncover flaws that have existed for years. Data driven recruiting can be a part of every stage in the recruitment funnel, allowing you to modernize and develop the best recruiting strategy.
1. Finding
Being able to figure your source of hire lets recruiters invest in effective channels and not waste time on marketing in areas that achieve minimal results. Data driven recruiting and hr analytics can direct you to places where the top tech candidates are and it can help you improve your employer brand to become attractive to job seekers.
2. Assessing
A data driven skill assessment tool can evaluate applicants based on a number of variables, which a recruiter can’t do manually. This helps recruiters to be selective in shortlisting quality candidates for interviews. A company can substantially reduce time to fill, increase candidate conversion rates and improve the quality of hire through better assessments. Getting early insight into candidates who have the right skills has an overall impact on the rest of the recruitment funnel.
3. Interviewing
Several tools can help expedite and improve the quality of interviews as this part of the recruitment process can be the most time-consuming. Using online test platforms together with structured interviews can provide an accurate assessment of a candidate along with analytic reporting. Accurate reporting on testing and interviewing the candidates not only reduces the time at the interviewing stage but data can provide better insight into the best-suited candidates rather than relying on emotional decision making.
4. Retaining
Retention is critical. Replacing top performers and starting from scratch with the recruitment funnel is expensive and disruptive. The right analytics can help you identify why employees leave, how likely they are to resign, evaluate current employee satisfaction, and more. All of this helps the organization improve in areas that are lacking so the best performers can stay, and turnover remains intact. Losing a good employee can be detrimental to a company.
Steps you need to take towards data driven recruiting
Now that you’ve decided to use the data driven recruitment approach, you can take actionable steps to get the process started. By using tangible facts, you will be able to make informed hiring decisions with an effective recruitment strategy in place.
1. Setting expectations right with the hiring manager
Managing the recruiter – hiring manager relationship right is the most crucial step towards a successful recruitment process. A recruiter’s understanding of the hiring manager’s expectations helps in creating accurate job descriptions and in deciding the right evaluation approach. It is essential to define the talent needed for the position. This determines the skills, personality, and attitude required, as well as the career growth opportunities available. Also, get real with the timeline in which the roles need to be filled.
2. Deciding quality evaluation metrics
Data-driven recruitment gives you the right insight on what metrics to evaluate for a specific job role or a position. Companies focus on different KPIs, projects, and organization-specific goals. A knowhow of what parameters you need as well as what parameters you can assess during an evaluation or interview process is important to understand what analytics to use and how to use data to maximize the efficiency of your recruitment process.
3. Conducting pre-employment assessments
Technology enables the use of pre-employment assessment tools to minimize the time to hire while assessing the most qualified and competent candidates. These can include tests to evaluate specific skills, problem-solving abilities, analytical thinking, technical and organizational skills, and collaborative attitudes before making a job offer. A bad hire without proper assessment is an expensive one.
4. Acting upon the data
We live in an era of big data. We have the opportunity to embrace the possibilities that come with collecting and analyzing data in a meaningful way. Recruiters need to adopt data driven recruiting approach using a hybrid of quantitative and qualitative information. There may be challenges in the operational use of analytics in recruitment but if recruiters get the proper training and the right tools, they will be able to derive meaning out of the relevant data.
Winding up
An effective recruitment process leads to higher productivity and decreased turnover that has a positive impact on the bottom line. The recruitment industry is ever-evolving and making use of intelligent tools and metrics that have become an imperative shift for businesses to adopt.
It is more important than ever for companies to take the initiative to collect recruiting data that can be used to draw inferences to build successful businesses and recruiting processes.
Thanks to data, recruiters and hiring managers no longer need to rely on gut-feel or luck or engage in a time-consuming and perpetual cycle of amassing and analyzing resumes. Data driven recruiting offers a wealth of insights to unlock the potential that was never tapped before.
WeCP offers a range of analytics to assess each of your recruiting metrics and helps you make better hiring decisions.
