We’ve talked through how to reduce bias when automating a high volume of applications using the Greenhouse Auto-Reject feature, but what about when it comes to automatically advancing candidates?
Our own Auto-Advance feature in application review gives users the ability to set criteria that will automatically progress candidates from application review to any future stage of the interview process. Essentially, you configure the candidate application questions and the responses to those questions will trigger the candidate to automatically advance to any future stage in the process.
In order to get the most effective use of this feature and mitigate the unbalanced impact that automated tools can have on people of color and underrepresented groups in the process, it’s important to know our best practices for automatically advancing candidates.
First, let’s take a look at some of the benefits of automating this part of your hiring process.
The benefits of Auto-Advance
Using Auto-Advance in application review creates efficiency through an intentional and instant prioritization of your applicants. Many recruiters are already prioritizing direct applicants through bulk application review – Auto-Advance takes this to the next level by automating that process for you.
Whether your company is always fortunate to receive a high volume of inbound candidates, you’re working on a reduced-size team and in need of increased efficiency or you’re experiencing a higher volume of applicants than anticipated this year, using the Auto-Advance feature can help save you time and resources on application review while moving top applicants forward quicker. Auto-Advance is also a good place to start for recruiters who may be wary of automation but looking to test new systems for efficiency.
Some things to consider when using Auto-Advance
Do not use protected class as a criteria
It is illegal in the US to make hiring or employment decisions based on an individual's protected class, which includes race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age (40 or older) and disability and genetic information (including family medical history). Therefore, you cannot ask any interview questions that directly or indirectly ask candidates for that information or use that information to affect your hiring decisions.
Even though Auto-Advance criteria are not the final hiring decision, using a candidate’s protected class to determine their eligibility for employment could be considered disparate treatment. Instead, we encourage you to use Auto-Advance responsibly by using questions that align with necessary attributes from the scorecard. Given the legalities surrounding this particular use case, we encourage you to consult your legal team before considering any criteria that may identify a candidate’s protected class.
Be aware of disparate impacts and check for unintended side effects
A disparate impact occurs when a neutral-seeming practice or policy results in an outcome that disproportionately impacts a certain group. In the case of automatically advancing candidates, the impacted group to consider are those who are not advanced by the set criteria – in other words, those who are not receiving the same advantage.
To mitigate any unintended impacts on underrepresented groups, prior to implementing your Auto-Advance criteria, we encourage you to first consider who might be part of that disadvantaged group. For example, if you set up an Auto-Advance for candidates who have achieved an MBA, you will be giving an advantage to candidates who identify as white and therefore disproportionately impacting candidates of color. Therefore, before implementing an MBA as a criteria, consider whether it is actually necessary to be successful in the role.
By nature, disparate impacts are unintended and therefore often get overlooked. In order to verify that there are no disparate impacts to your criteria, we encourage you to review your Pipeline by demographic report* to ensure that candidates of all identities are moving through your pipelines equitably.
Layer criteria to increase effectiveness
Often, one attribute alone will not suffice to progress a candidate without a traditional resume review. However, multiple questions can provide enough information to qualify a candidate into your hiring process. This is particularly useful when there are specific, necessary requirements such as hours and location. Here’s an example:
If you’re hiring warehouse team members, the ability to lift more than 25 pounds alone probably isn’t enough information to guarantee an interview. However, imagine that you could automatically progress all candidates who answered yes to all of these questions:
- Are you able to lift 25 pounds?
- Are you authorized to work in the United States for any employer?
- Are you 18 years of age or older?
- Are you able to work onsite at our warehouse in (location)?
- Are you able to work full-time (40 hours per week) and all overnight shifts (8 pm to 5 am)?
You can see how this dynamic mix of specific criteria would help you fast track eligible candidates into your process.
If you’re unsure of what criteria will be the most impactful for automatically advancing candidates to the next stage, a data-driven review of your most successful employees is a great place to start. Look at the skills and attributes that make those employees successful and use them as your starting criteria.
Reduce friction for internal applicants
A strong culture of internal mobility can produce many benefits for your company, including boosting employee engagement, increasing tenure and saving cost and time in sourcing. One way to promote a culture of internal mobility is by reducing application friction for current employees.
Along with configuring a clear and transparent internal job board, you can further reduce friction for your internal applicants by bypassing early interview stages. In many cases, you can skip an initial recruiter screen for internal applicants and in some cases you may be able to jump two stages and automatically advance candidates to a take-home test or onsite interview.
Consider this example, for a sales manager role. You could set up the following multiple-question criteria:
- Are you a current employee?
- Have you been employed with the company for less than 1 year?
- Is your current manager aware that you’re applying to this role?
- Are you currently on the sales team?
- Do you have prior management experience?
Depending on their answers, internal candidates could bypass one, two or even three stages of your internal interview process, reducing friction for both the internal candidates and the recruiters.
If you’re not yet convinced of the benefits of Auto-Advance or you’d like a way to test it out, try out Auto-Advance in conjunction with a two-step application review. Build criteria into your job post that automatically advances candidates to a second stage of application review. This will allow you to test out your criteria and see who filters forward. It’s also a great opportunity to test for disparate impacts before committing to a specific rule.
We recommend using the Auto-Advance feature in application review when your process requires an added level of efficiency. And as with all aspects of your process, it’s important to do so in a structured way that is aimed at reducing the biases that are all too common in hiring.
We hope these tips help you save time while considering the value of diverse backgrounds and experiences in your application review process.
*Pipeline by demographic report is available to Expert tier Greenhouse users
Ready to see this feature in action and mitigate bias in your hiring practices? Request a demo today.
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