How do you analyze recruiting data?

The sentence in the above that is spot on is "you should choose metrics that align with your specific objectives, challenges, and industry standards.". For example: 1. Company A hires the same type of roles 2 x's a year and does it on a class hiring basis 2. Company B hires different roles that require a specific skill set and hire based on revenue generated by the sales team If you use the same metric objectives for both you are not setting the recruiting team up for success. I would look at a pipeline conversion model for Company A and focus on top of funnel (how many reachouts convert to interviews) and Company B focus on market insights of what's available to what you are attracting to your organization.

To analyze recruiting data, start by collecting information from applicant tracking systems, job boards, and internal records. Clean and normalize this data to ensure accuracy. Identify key metrics like time-to-hire, cost-per-hire, and employee retention rates. Use statistical analysis and data visualization to uncover patterns and insights. Summarize your findings in clear reports and share them with stakeholders. Finally, continuously review and update your analysis process to adapt to changing business needs. This approach helps optimize hiring and improve decision-making.

Metrics that I believe all recruitment teams should track are, Time to Fill, Requisitions coming in each month and how many filled each month, Source of where we got the applicant, Requisitions sorted by department or field, Requisitions by location, Requisition amount assigned to each recruiter, and Requisition number of days open.

To define your metrics, you first need to define your recruiting processes. For hourly roles, there's probably a different process than professional vs executive, vs contract roles. Then, you need to break down every major step; Create a job req, post job req on job boards, engage with candidates for pre-screening calls, schedule interviews, get feedback, provide offers, etc. Then, you need to be able to track each step in the process. One of the biggest issues with hourly recruiting today is the Applicant to Pre-screened candidate ratio. Most companies I talk with have no way to track this, and the results show. Often only 10-20% of qualified applicants are ever pre-screened. That means 80-90% of qualified candidates are being ignored!

The numbers don't tell the full story. Some of the most important data comes from people (recruiters and candidates). Anecdotal information, which can be more time consuming to process, can be the most accurate way to determine root cause where your numbers don't seem good. Fix the right problem. Metrics drive behaviors and results, so choose wisely. Efficiency, cost, quality. You can pick 2 (hint: don't pick efficiency and cost).

Accuracy and consistency is a pain point for most TA departments. I'm seeing some AI tools come online that will help with this, but until they are perfected, I'd have an audit team in place to check accuracy and consistency. I've done this before and it's pretty cool to see how everyone's accuracy goes up with an audit. Most orgs that follow OFFCP require this.

In my experience when it comes to recruitment data specifically candidate details, it is challenging since the level of data validation you can do is limited unlike employee data. Thus a good amount of time will be spent on data clean ups. Therefore using a good ATS system, setting up proper and standardized templates to gather manual data etc. would ensure time spent on this is minimized and data is in a more accurate manner

Analyzing data to pinpoint areas of improvement in the recruiting process has become an essential part of today’s business landscape. It allows us to determine which strategies are yielding results and what can be done to improve them. Collecting relevant metrics helps identify bottlenecks and roadblocks that hinder progress or undermine candidate experience. By tracking applicant engagement and convert rate, we acquire an accurate understanding of where our recruiters need to focus their efforts, ensuring improved performance in the recruitment cycle. Taking a data-driven approach allows us to optimize our process for maximum effectiveness.

Implementing changes based on findings can be challenging, especially when it involves a complex system. It is important to create a detailed plan that breaks down the steps needed to reach the desired outcome. This can include items such as conducting research for better understanding of the issue and brainstorming potential solutions. All stakeholders should be involved in developing the plan, as input from all perspectives will help in refining and improving it. After creating the plan, it should then be thoroughly tested before implementation begins. This will ensure that issues can be discovered ahead of time and any unforeseen obstacles can be addressed beforehand.

My favorite part about data and TA is reporting to stakeholders as well as my team. Running a monthly review or quarterly review of outcomes is HUGE! Sometimes you get caught up in the minutia of daily tasks and don't see the impact until it's presented with visuals and hard data.