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Turn Quality of Hire into insights for a competitive advantage

February 6, 2019

The importance of TA analytics

Given the competitiveness in the marketplace today, recruiters and hiring managers are looking for an edge—one that consistently produces candidates who fit today’s job requirements and add organizational value for years to come. Understanding who they are and how to attract them takes insights that only an analytic approach can provide. Recruiters’ experience and managers’ gut feelings no longer make sense in today’s digital employment ecosystem.

According to Forbes, the most valuable metrics for staying ahead of the labor market competition provide an understanding of the sources and drivers of employee retention, future leaders, and highly successful employees over time1.Each of these metrics measure Quality of Hire.

The issue: Why HR should measure QoH

Essentially, each TA leader is looking to solve for the question, How does the business know it is truly hiring the “best and brightest”? This is where QoH comes into play. It represents the value new employees bring to the company and demonstrates TA’s ability to bring in the right talent, through the right sources, using the right tools. Especially given that organizations are regularly measuring performance, it makes sense to use that data to look more closely at those individuals rated the highest. Measuring QoH also provides insight into the capabilities of the full hiring team: sourcer, recruiter, and hiring manager.

What hiring managers typically care most about are things such as a new hire’s job performance and productivity, ramp-up time, engagement with the company, and retention. However, most organizations focus on tracking “activity” metrics, such as time to fill, cost per hire, requisition aging, and the like, while struggling to identify a systematic approach to uncover the more meaningful “outcome” metrics that managers value. What is needed is a systematic approach using integrated TA and HR/talent data to identify patterns to guide decision-making.

Some types of metrics that are used to measure QoH are:

  • Performance metrics, evaluations, and feedback
  • New-hire retention/turnover rates
  • Competency ratings
  • Validated pre-hire assessment scores
  • Speed to competency
  • Cultural fit
  • New employee satisfaction
  • Manager satisfaction

Organizations use any number of combinations of the above metrics to define Quality of Hire. Deloitte has defined three primary categories of measurement (efficiency, effectiveness, impact), which are leveraged across four (progressively sophisticated) types of analysis (descriptive, relative, analytic, and predictive). QoH is an effectiveness metric that is used in calculated analytic or predictive measures.

The impact: Why it’s important to get it right

We maintain that it’s essential for every organization to measure Quality of Hire to build sustainable strategies that consistently produce high performers, future leaders, and SMEs, as well as avoid the costs associated with mis-hires, including recruiting costs, lost productivity, overtime, morale issues, and training and onboarding costs. The key is to use QoH to identify the most effective strategies for sourcing, attracting, hiring, and training the best-fit candidates for employment.

Historically, most of the data around the quality of new hires has been highly subjective in nature—manager or occasional new-hire surveys, inferences from engagement surveys, etc. Yet the data needed to make a more quantitative analysis, the ultimate yardstick of performance, already exist in your HRIS in the form of ratings, retention statistics, promotions, diversity successes, etc. In fact, so much data are available the question quickly becomes, What data should inform your choices?

How to do it: Examples

Today’s HR organizations collect reams of employee data. Mature HR analytics organizations integrate HR and talent data with Talent Acquisition data to inform hiring decisions, looking at things like tenure, performance ratings, competency ratings, new-hire (30-, 60-, 90-, and/or 180-day) performance reviews, pay increases, promotions, employee engagement (where individual engagement is available), and high-potential status or ratings.

Ideally, metrics are calculated using both pre- and post-hire data. Pre-hire metrics include measures of assessment scores, academic performance data, experience and industry data, source of hire, etc. Future-looking organizations invest their time conducting statistical analyses to determine the underlying correlations and predictions that exist between this pre-hire data and post-hire data. For example, including the measurement of speed of promotion in previous companies may serve as a predictor of future performance ratings or high-potential status.

This in turn, serves as a critical input for recruiters to develop their recruitment strategy. Through predictive analytics, organizations can now determine the extent to which sourcing through social media and employee referrals gets them the best hires, leading to increased investments in both these sources in the future. In the new age of digital and social media recruitment, it becomes highly essential to determine what channels of recruitment yield the most effective and productive new hires.

The next big step is to work in tandem with the finance team and convert QoH metrics into dollars. For example, a regression analysis can be conducted with QoH metrics versus company profitability, revenue, and other objectives to determine the real impact that new hires are making to the bottom line. The result is that your QoH metrics will be aligned to critical organizational outcomes, thus demonstrating the ultimate impact of TA efforts on the business, and their value.

Where to start

To develop a more comprehensive TA decision-support capability, start by asking your hiring managers and leaders what outcomes of recruiting they care most about (e.g., Cost to hire? Performance? Retention? Engagement?), then categorize or identify key metrics that help you understand efficiency, effectiveness, and impact. Build on your (most commonly) existing descriptive analysis and reporting to identify which data points and KPIs to mature further. We suggest working with experts to develop more sophisticated approaches using statistical methods.

Our experience suggests that the business will come along on this journey as you jointly learn to interpret the new analyses and then refine the metrics that matter the most, such as cost of quality hire per source, speed to competency, and source of best cultural or retention fit. It all begins with aligning to the business strategy and building a decision-support process that confirms TA’s contribution as a strategic partner that both enables and delivers superior business outcomes.

Bill ClearyBill Cleary, GPHR, is a senior manager in Deloitte Consulting LLP’s US Human Capital service area. Bill’s primary focus has been on complex global HR transformation projects with extensive experience focused on talent acquisition.
Charles GoretskyCharles Goretsky, is a manager in Deloitte Consulting LLP’s Human Capital practice, with a focus on enhancing the effectiveness, efficiency, and business alignment of HR and Talent Management functions and their analytics capabilities.
Navti NarangNavti Narang, is a consultant in Organization Transformation at Deloitte India (Offices of the US), specializing in organization culture and employee engagement assessments, change management, and learning organization advisory.


1 Tom McKeown, “The Top Five Predictive Models for People Analytics,” Forbes.com, August 27, 2018.

Originally published at Capital H blog