20+ Metrics for Effective Data-Driven Recruitment

Over the past 30 years, there has been a significant transformation in the recruiting industry. The employment market of today is very different from responding to an advertisement in the newspaper or being headhunted by top recruiters worldwide. It also constantly offers new options, such as social media posts and recruiting platforms meant to catch your attention.

When you make hiring decisions, from choosing prospects to developing hiring strategies, you engage in data-driven recruiting. Data-driven recruitment teams are –

  • More effective in getting top talent,
  • Able to cut down on expenses, and
  • Proficient in enhancing candidate experience. 

Implementing objective recruiting judgments based on a range of information, in addition to the standard resume screening, interviewing, and job offer extension is known as data-driven recruitment.

Data-driven recruitment teams monitor the effectiveness of the hiring process using a variety of indicators and apply the findings to constantly iterate and improve it.

How do you create a data-driven recruitment process?

1. Decide on important data sources and their metrics

When you examine the hundreds of data points that recruiting softwares are gathering for you, it can be overwhelming. Choosing the ones that are most relevant for your business and team is extremely critical.

At a first principles level, you need to set a precedence on your quarterly/ yearly hiring objective between Cost Per Hire, Quality Of Talent or Time to Hire.

It’s extremely critical that your whole leadership team including functional heads are aligned on the selection of this primary metric. This helps not only select the right metrics to be tracked but more importantly are a deciding factor on which red and amber indicators to act on first. Just to give you a few examples –

Some of the metrics you may choose to track include:

A. Quality of Talent Metrics

If Quality of Talent is your “output metric” you want to optimize for; it will be difficult to effectively focus on Cost and Time both. You might decide to focus on the following –

Top of the Funnel Metrics
  • Hiring Funnel Conversion Ratios – Applied to Screened to Interviewed to Offered to Hired
  • Conversion by Channels – Job Boards, Referrals, Agencies etc.
Post-hire Metrics
  • Early Attrition – Employee churn within 90 to 180 days of hiring is a clear indicator of bad hires
  • Job Performance & Ramp Up Time
Talent Branding Metrics –
  • Career Page Analytics
  • Candidate Feedback Ratio
  • Glassdoor Ratings
  • Offer Decline Ratio

B. Cost Per Hire Metrics

For Cost Per Hire, we need to be able to optimize both internal and external costs.

External Costs

External hiring costs including agencies, job boards/ Linkedin, automation platforms, assessment providers, referral bonuses etc.

  • Cost per lead by Channel – This helps find the biggest leaks when it comes to acquiring candidates, be it be job boards or referrals
  • Cost per offered Candidate Lead – This helps understand the channel effectiveness while looking to optimize. Remember even though a channel might be costly, it might be the most effective.
Internal Costs

Internal meaning recruitment teams, interviewers and other non-invoiced items. Usually, if you are able to optimize “Time to Offer” described below, this metric is a direct benefitted.

  • Internal Cost per Offered Candidate – This helps understand internal costs including interviewer cost
  • Cost per Offered Candidate by Function/ Vertical – There might be a certain vertical which is spending more than the rest of the org.
  • Offer to Joiner Ratio – While this is not a direct “cost” metric, we have seen offer dropouts and candidate ghosting leading to increase in internal costs.

C. Time to Hire Metrics

Hiring cycle time is function of sourcing time through to offer and finally hire. While candidate quality and channel mix affects time to hire in a big way, as far as the hiring strategy goes, this metric needs its own attention. Especially at times when your business needs rapid team growth, this metric should be your north star. It can be split into the following –

Sourcing Time Metrics
  • Position Approval Time – In a few organizations, critical velocity is lost owing to multiple levels of approvals
  • Candidate Database – The strength of your nurtured candidate database defines your outreach velocity to help advertise the opening to a larger set of talent pool who already know your brand
  • Job Posting Time – The time it takes to make your position visible to a larger set of active talent pools.
  • Agency Onboarding Time – For a few positions it might be critical to get specialist recruiters & recruitment agencies get started early in the hiring lifecycle.

    Note: Spottabl brings this metric down to a few hours by matching your job opening to the right specialist agency. Over and above that, vendor onboarding and contract negotiations end up wasting vital time in the most important phase of hiring. Spottabl removes the hassle of contracting with multiple vendors and brings all of them on a single platform.
Time to Offer

Time taken from an applicant or a candidate lead entering the funnel to her receiving an offer is an important set of operational steps that can be easily optimized for. It’s almost in no way having any external dependencies and hence it’s the biggest component of “internal” costs.

  • Screen Select Time – Depending on your process, this includes screening resumes to selecting and calling candidates to check on their fitment.
  • Assessment & Assignment Time – Sending assessments and assignments to candidates is huge candidate drop-off point. But if you have a large number of openings and hence a large top of the funnel, this becomes an important metric to keep track of an aggregate level.
  • Interviewing Time – With cutback on in-person interviews and hiring drives, this metric has suffered the most. Interview scheduling and candidate no-shows have been the biggest friction points in the “days” it takes to offer a candidate.

Post offer, there’s not much you can do to optimize on time, apart from relying on cost and quality metrics to make sure that candidate engagement is prioritized.

2. Collection of Data

After choosing the data to track, you need a plan to collect it. 

Using website analytics, you can determine the visitor numbers the careers page as a whole or even specific job listings are receiving in comparison to the total of applicants. This will help in tracking the conversion rates of your careers page and determine the number of talent moving from viewing job listings to really applying.

If you are using an applicant tracking system, most modern systems will be able to give you a dump of the data. This will allow you to track most time and quality related metrics. Cost metrics are derived from actuals that your talent acquisition function spends.

Based on how the data is sent to you, you might need to develop a system for organizing it all. This may be a spreadsheet, a program for data analytics, or whatever database is convenient for you. Setting this up can take some effort, but once you’ve done it, you must be able to simply update the data when fresh figures come in. Again, most ATSs provide a dashboard view of the data. But you can always create your own dashboards based on the tools that you are most fond of.

Make this data visible to you and your function such that each member of your team is able to track it on a daily and a weekly basis.

3. Choosing what actions to take

Utilizing data in recruiting entails more than just tracking it—it also entails taking action.

For example, you can investigate their source and discontinue advertising your opportunity there if you see that you’re getting a greater proportion of low-quality applicants.

If you see that more people are applying straight from your job posting on the careers page, think about spending money on search engine optimization (SEO) services to raise your website’s ranking on search engine results pages.

4. Be cognizant of the limitations of data

Data does not solve everything. 

Data can’t explain why something occurs. Combining many sources of data can provide in-depth insight, but an analysis of the result is still needed.

Your issues cannot be solved by data. Data reveals what your team excels at and where there may be issues that need to be fixed, but the necessary changes and the steps to be taken are based on discretion.

Not all data is objective. Be willing to interpret results cautiously if members of your team are the ones who generated the data. The outcomes, for instance, will be more trustworthy if applicants’ tasks are assessed by software as opposed to a person.

5. Refine by contrasting the preceding and succeeding values.

Knowing the status before and after any modifications have been made will make the data far more useful. Set benchmarks from past data and achievable goals for the upcoming months/ quarters.

Do the outcomes of your strategy meet your expectations? What can you change if not that?

To better your future recruitment selection attempts, data will enable you to identify your successful and unsuccessful hiring techniques.

Why do you need a data-driven recruitment process?

1. Accelerating the recruitment process

You may decide whether to automate or eliminate bottlenecks in your hiring process by gathering data that will assist you to identify where they are.

You should outline your hiring procedure by first acquiring information such as:

  • Application churn rate
  • Average hiring time for a certain job
  • Job advertisements against job boards, recruiting events versus employee referrals, and other recruitment approaches
  • Time required for each hiring phase: How long does it take you to the source? On how many interviews?

Your time to recruit will be more accurately estimated with the help of these insights. Furthermore, armed with this knowledge, you may credibly advise stakeholders on reasonable timelines.

2. Lowering hiring expenses

Your hiring cycle will be shorter and your recruitment cycle budget will be more effectively utilized with data-driven recruiting.

In addition to monitoring your source of hiring, you may assess the effectiveness of your present recruiting tech stack to determine if it is assisting you in locating talent.

3. Reducing hiring discrimination and developing more impartial hiring decisions

You may choose the ideal applicant for the job in an objective manner by using a data-driven recruiting approach. Additionally, it assists you in creating a hiring procedure that can be defended in court.

Additionally, it encourages Diversity, Equity, Inclusion, and Belonging (DEIB) inside your company. A diverse workforce stimulates innovative thinking, improves decision-making, and increases corporate success. Additionally, it guarantees that every applicant is treated equally, regardless of color, ethnicity, gender, or age.

4. Enhancing the candidate experience

Using the most recent technological advancements is simply one aspect of data-driven recruiting. It has to do with the method utilized to simplify and speed up the application procedure for candidates. In fact the simplest way of studying candidate experience is by simply asking them. This makes it clear to you which stage needs the most improvement.

Only 17% of businesses request input from candidates at various points throughout the hiring process.

Spottabl’s internal survey

With candidate surveys, you could measure the Candidate Net Promoter Score (cNPS). Additionally, your applicants will value any efforts you make to make the process quicker, easier, and more equitable.

The Hiring Flywheel

5. Proactive instead of reactive

Instead of just responding to the problem as it arises, you may anticipate your recruiting needs using data to guide your hiring strategy.

Setting expectations for a new hire requires accurate recruiting time forecasting. For crucial jobs like new managers in charge of leading new divisions during a product launch, this is extremely crucial.

6. Upgrading the quality of hiring

Recruiting the top candidates makes a significant contribution to the growth and profitability of your business.

There are several methods for selecting highly qualified applicants utilizing data. More accurately than applications and interview processes, work sample test results and fundamental mental ability tests forecast future job success.

7. Equipping the hiring team for success

Building a standardized method that enables you to make informed recruiting decisions is possible with a data-driven recruitment approach.

Since they can back up their decisions with hard facts, recruiters and hiring managers are more certain in the recruitment process.

Data-driven teams are more productive and bring additional value to the business because they function more cost-effectively and with greater efficiency.

Conclusion

Strong candidates may do inadequately in interviews, but in a data-driven framework, they might provide you with more details to aid in your decision. Data-driven recruiting is a far superior indicator than a CV or face-to-face interview, including assessments, personality tests, and skills competency examinations.

By using a data-driven recruiting strategy, you may create a hiring model that is consistent, more knowledgeable, and effective. In fact, as shown in the image above, data-driven recruitment leads into a self-powered flywheel. So, stick to the instructions listed above, and your hiring process will be improved.

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Anupam Choudhari

Anupam Choudhari

Anupam is the co-founder of Spottabl and heads Product & Tech. He has spent 8+ years building hiring and talent experience products. A data scientist and an AI in HR enthusiast, he provides some unique data insights in recruitment.

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