The 3 Best Moments for Data Analytics in Recruitment 

by: Tim Oyer and John Hess, Vice President, Sales and Executive Vice President, Operations |
June 17, 2021
Tim Oyer and John Heaa

Timing is everything they say, and it’s certainly true when it comes to recruitment and data analytics. Recruitment requires knowledge, precision and quick decision making, especially in a challenging labor market reshaped by the upheavals and fears of the pandemic. Well-curated marketplace and talent data built into the employment life cycle can aid in every one of those processes if it’s utilized at the right time. Leveraged all the time or incorrectly, however, data will blind recruiting and hiring managers to the human factors, like cultural and team fit, that are equally essential to effective hiring decisions. 

The fact is few businesses have data analytics built into their recruitment process tech stacks. While many organizations have invested in recruitment tech of some kind (assessments, digital application tools, video interviewing, etc.), analytics have stayed under the radar and off budgets. 

Data analytics is effective in optimizing recruitment processes and results 

Our credentials come from 30+ years of RPO (recruitment process outsourcing) work in which the data of talent acquisition is carefully tracked in order to demonstrate recruitment ROI and SLAs. Over those decades of balancing the work of recruiting and putting the power of data behind it, we have found three ideal windows for infusing rich data analytics into the talent acquisition process:

  1. Pre-Execution
  2. Execution 
  3. Post-Execution 

As comprehensive as it sounds, this 1,2,3 analytical approach is targeted to provide the right data at the right time. It starts and ends the recruitment process with data without making data the one-and-only employment selection factor. As businesses look to transform and grow post-pandemic, now is the time to consider what data can do to improve the team you have and the one you are building. Here’s how and when it works:

1: Pre-Execution
Prior to a recruitment initiative, data analytics can and should be used to assess the target marketplace for competitive factors. In the pre-execution phase, data analytics can help determine how benefits and remuneration plans can/should be adjusted to improve recruitment outcomes. The data to consider pre-execution of a recruitment effort would answer the following questions:

  • What is the supply and demand factor for the targeted skill group in the marketplace or marketplaces considered? 
  • What is the unemployment rate for the targeted skill group in the marketplace? 
  • Does the competitive landscape for talent put salaries or hourly rates too high?
  • Are there enough skilled and diverse talent sources (colleges, training programs, community resources, competitors, etc.) to fill the recruitment pipeline?  

This data can inform and set hiring manager expectations around talent supply, recruitment timelines and more. Based on marketplace and economic assessments, businesses might adjust compensation and benefit packages, widen the recruitment range to include nearby localities or even consider increasing flexible/remote work arrangements to bolster their competitiveness as an employer. 

2: Execution
Once the recruitment process begins, data tracking continues behind the scenes, tracking where the most effective hires come in from and how key factors (salary, job flexibility, commute, etc.) are influencing offers accepted. Across the execution phase, where recruitment and hiring takes place, data analytics help recruiting teams optimize and accelerate their results by zeroing in on the talent pools and strategies that are showing successful results and turning off those that are not working. 

The data to measure during recruitment process execution would answer the following questions:

  • How many candidates are we seeing per role?
  • What sources are providing the best talent?
  • Are salary expectations on par with what’s being offered?
  • Why are candidates saying yes /no to offers?
  • What is the hiring manager interview to offer ratio?
  • What is the ghosting (no show) per process rate? 
  • What is the speed per phase/task across the recruitment life cycle?
  • Are diverse recruitment and offer goals being made?
  • What is the hiring manager-to-interview offer ratio?
  • What is the ghosting (no-show) rate at each process step?
  • How much time is spent at each process phase?

3: Post-Execution
Some of the best learning and analytics occur after the recruitment effort is complete and all data is available. For example, final compensation data can help recruiters understand candidate mindset and competitive realties. 

  • At which salary point did candidates begin accepting offers and at what point was the offer too low? 
  • What percent of candidates progressed through each process/task step?
  • What benefits and perks were candidates looking for?
  • What skills were hardest to find (few to no candidates had them)?
  • Was the talent pool strong enough in the marketplace? This means looking at the number of resumes/applicants versus the number of viable candidates they produce.
  • Were diversity recruitment goals achieved?
  • What was learned from the hiring manager and candidate survey results?
  • What do the overall talent funnel metrics tell us about recruitment effectiveness?

In addition, early retention numbers can assess the effectiveness of the recruiting process and the recruiting team. For example, if early turnover spikes to a significant number, it’s clear some parts of the process, from the job requirements to the cultural fit assessment, are missing the mark. The right analytics can point recruiting teams to areas of weakness, identifying how the process can improve and more quickly deliver the right talent. 

Data Works
Adding data analytics to the recruitment process brings a new level of intelligence to talent acquisition. It arms businesses with the knowledge needed to:

  • Understand and analyze hiring trends and opportunities from all perspectives
  • Monitor key stats and make critical, real-time tweaks to improve hiring results 
  • Gain greater recruitment and employment predictability

The key is treating the data as part of the greater recruiting continuum—knowledge that can inform and improve talent acquisition teams and tactics—without overtaking the essential, human role recruiting experts play in engaging candidates. Good recruitment data, after all, has to come from people. To get data right, you have to get it right from the source: people. 

Recruitment Process Outsourcing (RPO) solutions from Advanced RPO can help you evaluate and improve your hiring processes to get the talent you need to succeed. Contact us today to learn more about our high-touch solutions.