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Get insider info on SAP SuccessFactors HCM suite for core HR and payroll, time and attendance, talent management, employee experience management, and more in this SAP blog.
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Bias has been and continues to be prevalent in nearly every aspect of daily life, and the level of bias is different in nearly every instance. From simple things like: which person do you hold a door for, which line do you choose in a grocery store or at airport security, or what candidate do you invite in for an interview. The answer and reason why is different for every person, and some people don’t even think of it as bias. Now, this is not meant to be a Debbie Downer blog post, but rather, I am attempting to help you understand the complexity and pervasiveness of bias. The most difficult aspect of this is that most people don’t even know they are doing it.

How often have you perked up a little bit when you meet someone who grew up in your own home town when you are half way around the world? Or have you ever taken a slightly harder look at a resume because of where that person went to school? Both are a form of bias.

If you are recruiting a salesperson you want them to be competitive – or a developer to be a code ninja. If you have ever used those words, you are focusing on masculine traits or, oftentimes, male candidates. Just like using words such as supportive and committed are seen as feminine. Decisions like this are subconscious and seem harmless, but the result of these subconscious actions have larger, detrimental real-world effects. To use a blaring example, there is no lack of research regarding gender inequity in STEM. Only 28% of the world’s researchers are female. Partially, it got this way because men hired men – those who were of similar upbringing, similar schooling, and people they just seemed to get along with. Is this purposeful bias? In most cases, no. But in some lines of work and some industries this is very conscious and borders on (or is way beyond) legal.

To help combat this problem, and help our customers combat this problem, we are taking steps with a larger initiative coined “Business Beyond Bias.” Recruiting is on the front line of the business, and is the largest single contributor to be a change agent when it comes to creating a diverse corporate makeup, outside of corporate culture of course – but this is a chicken and egg scenario. One of the first implementations of Business Beyond Bias is with the Job Analyzer as part of our Q1 release within SAP SuccessFactors Recruiting.

Part of SAP SuccessFactors Recruiting, Job Analyzer is a toolbox of machine learning functionalities for recruiters when creating job descriptions. There are two key tools:

  1. Language Analysis targets those words identified as masculine or feminine and provides gender neutral replacement terms. This helps remove subconscious bias to ensure job descriptions are compelling to all candidates, regardless of how a candidate identifies. This tool also provides key skills information and related skills information to help drive the right candidates to apply.

  2. Salary Analysis analyzes data from similar jobs based on both defined data sets and publicly available salary data. This data is then compiled, along with the present inventory of similar roles to provide guidance on salary to help get the right candidates in the door quickly.

We are pleased to provide tools and technology to not only help businesses run at their best but also help improve our society and culture by creating an inclusive environment for everyone. Stay tuned, this is just the beginning for SAP SuccessFactors in the fight against bias.

Learn about the other new features and enhancements to the SAP SuccessFactors HCM Suite in our Q1 2018 Release Highlights document and hear from our Head of Product Amy Wilson in our release highlights video on YouTube.