6 min read

Learning from Failure: Why Measuring New Hire Failure Rate is Great!

Measuring New Hire Failure Rate in an actionable way and acting on the data will save your company money. In this blog, I'm taking a look at how your organisation can save significant sums of money and minimise workforce continuity risks by measuring and understanding your new hire failure rate.

Since recruiting and onboarding new employees is expensive, retaining new employees past their earliest phase of employment is critical. When you reduce new employee turnover you save money. A powerful tool for enabling this change in your organization is measuring New Hire Failure Rate.

What is New Hire Failure Rate?

New Hire Failure Rate is the percentage of a group of hires that leave the company within a set period of time. More specifically, it's people hired during a specified time period who leave the company within a certain number of months divided by all of the hires from that specified time period. The time to termination is a lever that can be adjusted but generally ranges from 90 days to 2 years. It's a powerful measure because it spans recruiting, onboarding, and employment. A lot of data is captured during each of these phases, lending to a large number of factors available to analyze. 

Measures similar to New Hire Failure Rate include New Hire Retention Rate and New Hire Turnover Rate. Either one could be substituted for New Hire Failure Rate with a similar value proposition.

New Hire Retention Rate is the same thing but the inverse and has a more positive name 🙂. It puts the focus on those who stay rather than those who leave.

The New Hire Turnover Rate calculation is a bit easier to perform but the measure can be more difficult to interpret due to it being based on headcount rather than hires.

Why is it costly?

New hire failure is almost universally a negative thing. Even if you're losing hires who are not a good fit for your company, it's costly. Situations like seasonal holiday hiring at a retailer might be an exception in some cases but can be excluded from your analysis if necessary.  Some specific reasons that losing employees early in their tenure is costly include the following:

  • The rate is surprisingly high at many if not most companies. A quick internet search yields numbers in the 20% to 80% range. This article isn't going to cite specific numbers since plenty of other articles already do that and your company is unique. If you were informed though that half of your new hires leave in the first year would you believe it? If I were a leader in the Talent Acquisition or Human Resources areas, I would certainly want to know the rate at my company.
  • Hiring and onboarding costs a lot of money. New hire failure increases the amount of both processes that need to happen. Monetary costs include the following.
    • Talent Acquisition employee salaries
    • Paid sources
    • Training resources
    • Time spent by hiring managers interviewing and onboarding people
  • Companies get little productivity from employees who are not yet up to speed. Employees leaving early in their tenure are leaving before they're productive.
  • People leaving teams is bad for morale of those teams. People in senior leadership leaving can be bad for morale of the entire company.
  • Brand reputation can suffer.

Why don't all companies measure New Hire Failure Rate?

You'd be hard-pressed to think of a People Analytics metric that's more powerful and actionable than New Hire Failure Rate. So why isn't it usually a key performance indicator for Human Resources and Talent Acquisition teams?

Calculating New Hire Failure Rate is surprisingly tricky

Hires from a specified time period that terminated within a certain number of months divided by all of the hires from that specified time period sounds easy enough. But you have to ensure that both the numerator and denominator come from the same group of hires. So you need to know the hire date but also the termination date at the same time. And you need the differences between those dates bucketed so that you can adjust the "Time to Termination" between 3 months, 6 months, a year, etc. to find the sweet spot. You also have to offset the group of hires back from the current date to allow enough time to know whether the hire terminated or not. By this, I mean that if you're looking at New Hire Failure Rate within 6 months, you don't want to include hires from the past 6 months since you don't yet know whether they'll terminate within 6 months.

new hire turnover rate graph

New Hire Failure Rate Example: My colleague Phil Schrader, One Model's Solutions Architect, performed this new hire failure rate analysis from scratch in less than 5 minutes. Could you do that with your existing HR analytics today? Take the People Analytics Challenge today! 

The measure itself isn't actionable unless you know other things about the hire

Knowing that your company has a high New Hire Failure Rate highlights that a problem exists but does not help you solve it. In order to improve retention, you need to know as much as possible about the hires who are leaving (and the ones that are staying for that matter). Luckily, companies leveraging modern applicant tracking, onboarding, and HRIS systems have a lot of useful data available. Unluckily, this data is often not available in a useful way. To improve your New Hire Failure Rate, you need to be able to slice it every which way to find the attributes and areas to focus on. Unfortunately....

The hiring process spans two separate teams and often two or more separate systems

The Talent Acquisition and Human Resources functions both involve hiring but in most companies, they're two separate teams.  Not only that but they often leverage two separate systems (ATS and HRIS) to manage their processes. Even companies who use one system such as Workday to manage both Recruiting and HR suffer from the data from the two functions not being cleanly linked together for analysis. On top of this, there's often data related to onboarding such as survey data. This is extremely valuable data when tied to outcomes like early tenure terminations. Unfortunately, many companies use a survey vendor separate from their ATS and HRIS vendors and obtaining survey results comes with its own set of challenges.

How can companies measure it in an actionable way and save money?

The first thing you need is a People Analytics team. A People Analytics team services both the Talent Acquisition and Human Resources functions. Since New Hire Failure Rate spans both teams, it's best to have a neutral third party reporting it. This should help prevent false assumptions about the causes of high rates stemming from the other team. There's also the word "Analytics" in " People Analytics", and some analytical prowess will be useful in tracking down the causes. Tracking New Hire Failure Rate is only valuable to a company if they act on the findings. The function of a People Analytics team is to provide actionable insights, so they're well-positioned to maximize the impact of the measure.

A People Analytics team needs the right tools in order to be successful. The best tool to measure New Hire Failure Rate is a People Analytics platform.  A People Analytics platform provides:

  • All of the data in one place and joined together in one data model (subliminal hint)
    • Core HR data such as Business Unit, Job Level, Location, and Manager
    • Recruiting data such as Application Source, Time to Hire, and Recruiter
    • Candidate Survey results
    • Onboarding Survey results
  • A complex yet intuitive way to deal with time
  • All of the attributes structured into dimensions for grouping and filtering the data
  • A compelling visualization layer for distributing the insights to the people who can act on them

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Watch my colleague Phil Schrader perform a similar analysis in One Model


At this point, it should be clear that performing a one-off analysis of the drivers of New Hire Failure Rate would be very difficult. 

How can companies achieve even more success?

Saving your company money was mentioned in the introduction to this article.  In this article, Phil describes how you can leverage One Model to calculate source costs and cost per hire.  If you know how much it costs to hire someone, you know how much money you’re losing when they leave the company right away. Being able to go to leadership with dollar figures, even if they’re estimates, can be a very powerful driver of change in your organization.

Last but certainly not least, companies can maximize success in measuring New Hire Failure Rate by leveraging Machine Learning. This is a great use case for a causal analysis highlighting drivers of new hire failure. An advantage of performing this type of analysis using machine learning is that it’s far more efficient than doing it manually. A tool like One Model’s One AI is able to take all of the attributes from all of the data sources described in this article and run them through a classification algorithm, returning the most predictive of both new hire failure and retention. It can do this in an intuitive way that doesn’t require Data Science skills.  If that sound too tricky, embedded insights in One Model powered by One AI can deliver various onboarding retention statistics right within storyboards.

Most things that save you money in the long run require some up-front investment.  Measuring New Hire Failure Rate is no exception. Like installing solar panels save you more in the long run than installing water barrels, leveraging a People Analytics team and platform to measure New Hire Failure Rate will be much more impactful than a one-off analysis. This is an opportunity to achieve quantifiable results and further cement the value proposition of People Analytics teams.


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