Software giant SAP’s SuccessFactors HCM solution is in a constant state of evolution. New capabilities being rolled out to help managers enhance diversity are partly an outgrowth of SAP’s own focus on steering clear of having a homogenous workforce. EBN recently interviewed Dr. Gabby Burlaco, an industrial-organizational psychologist by training, who leads Solutions Management for the User Experience and mobile applications of SAP SuccessFactors technology. Edited highlights of that conversation follow.

Employee Benefit News: What are the primary shortcomings of traditional diversity initiatives that are being addressed by SAP’s “beyond bias” initiative?

Gabby Burlaco
Gabby Burlaco

Gabby Burlacu: When we brought together our customer advisory board members, we quickly noticed some patterns in how these companies were addressing diversity. A lot of them had won diversity awards, SAP included. Almost all of them did diversity training. So the latest focus in diversity is training to make us aware of our unconscious biases and trying to mitigate them. So it was this idea that, “Can we train away the biases that people inherently have and can we make any real difference by just being aware of the diversity in our organization?”

EBN: So I guess that doesn’t really tackle the problem?

Burlacu: Yes, we found that approach was insufficient. Training can’t always address we face every day in our jobs. And then simply measuring the numbers is just not enough to drive the actions that should be happening. Suppose you have an award-winning women-in-leadership program, and it’s very successful at getting women the skills they need to move up into leadership positions. But are those same programs then focusing on all the cultural issues and unseen barriers women may face once they get into those leadership positions? If you come back three years later, maybe you won’t find as many women in leadership as you found before.

EBN: So how is technology applied to give diversity initiatives greater enduring impact?

Burlacu: First, we need to think more broadly about diversity — it’s not just demographics per se. Companies need different viewpoints, different decision making styles and different cultural backgrounds. And that tends to be pretty well correlated with demographic differences. Plus we still need to focus on demographics so long and there are legal components, like EEO compliance. But what we’re really looking for are the underlying values that each of these different groups bring.

EBN: How can software such as the workforce analytics embedded in SuccessFactors help companies get below the surface of diversity?

Burlacu: The key is looking at the topic holistically. It’s not just about training, or even how and who you recruit and hire. As I mentioned in the example of female executives, so much goes on once you are already in an organization to either keep you there and engaged, or push you out. Research on performance management provides a lot of insight here. That’s the place you can see right away if managers think there is only one right way of doing things, and tend to penalize people who approach things differently. That can be a big impediment to diversity.

EBN: How is technology leveraged to highlight those situations?

Burlacu: The SuccessFactors HCM solution uses what we call “decision interruption.” That’s where as decision makers are using the solution to make decisions, they are now presented with different features, options, data, information — things that kind of interrupts that decision to say, “Hey, just take a look at this.”

EBN: You mean it flags a potential decision that could run counter to the goal of achieving greater diversity?

Burcalu: Yes. What the technology does in different ways across the full suite is it nudges managers towards seeing these different things. Take the talent review process. When managers get together, they discuss the performance and potential of the people on their teams, organize them according to their performance and potential, and whoever has the highest performance and potential tends to get the raises, the developmental assignments, the promotions. To introduce some bias reduction into this process the calibration tool looks at the data in the entire system that it would take the managers weeks to put together manually, and it surfaces alerts when a decision in that process looks potentially questionable.

EBN: How does that work?

Burcalu: There’s a rules engine behind it, so certain conditions raise the flag. You could configure, for example, to look at leave of absence periods for female employees, like maternity leave. Suppose that employee suddenly has a far lower performance score than she has in the past. That’s a red flag because research shows that’s a pattern that typically happens. The absence hurts your career and hurts the perception of the contribution you’re making to the organization. It doesn’t contradict supervisors; it just provides them with an additional point of information that they may not have seen before that could influence then how they approach that decision.

EBN: Can the system teach itself what to look for?

Burlacu: We work with customers to configure their own, but we also try to provide some best practices on the things to watch out for. But we do
leverage machine learning in some areas. An example is our recruiting module.
It does a number of things based on machine learning to help you write a better job description. One of the features focuses on identifying gender-biased language. Recruiters write job descriptions to be exciting, so they use really powerful action words, but research shows that some of those words deter certain populations from applying. The tool gets better over time at flagging these bias terms, as well as suggesting some equally exciting but maybe more gender neutral terms to use.

EBN: It sounds like your primary focus is gender bias.

Burlacu: A lot of it is gender because we had to start somewhere, otherwise it would just be a chaos of ideas. Women represent the largest proportion of the workforce, when you think about an unrepresented category.

EBN: What’s coming next?

Burlacu: One of the next areas that I find really exciting is differently abled, particularly employees on the autism spectrum. That represents a huge growing group and workforce segment. You see a lot of organizations, SAP included, building things like autism at work programs. But you also see those continued biases around how their performance is evaluated, whether they’re given opportunities to develop, things like that. I think we can do a lot there.

EBN: So, hiring, promotion — what are all of the basic points where bias can manifest itself, where you’re building functionality in the workforce analytics part of SuccessFactors to send up red flags to fly when unconscious bias may be occurring?

Burlacu: Here’s the list. First, it’s looking at who applies for jobs and who is hired. Who applies gives you insight on how you are presenting opportunities at your company. Next is looking at how people are managed. The “who is developed?” analysis looks at patterns in training and engagement initiatives. “Who is rewarded?” is about compensation patterns in a diverse workforce. And “Who is promoted?” speaks for itself. We have an eBook that lays out the whole framework.

EBN: Which of these bias areas are on your priority list for further development?

Burlacu: Compensation and equal pay. That’s not to say we have something on the roadmap that’s coming next month. Also, who gets promoted.

EBN: I assume companies have to set the parameters for when disparities, let’s say on pay, are deemed worthy of scrutiny?

Burlacu: Companies take varied approaches on this. It goes far beyond gender to ensure fair pay for the right kind of work. And also the way that compensation is evolving is interesting here, like the increasing use of spot bonuses. I think that could be a cool opportunity to zero in on a part of compensation that historically people say, “Oh, it’s no big deal,” and see what we can learn in the context of diversity.

EBN: Do these tools work for smaller organizations?

Burlacu: I can’t put a precise size limit on it, but from my perspective as a researcher, these concepts have merit, even in smaller organizations. And even without these tools, it’s important for employers to learn about unconscious bias, why it happens and what you can do to address it.

EBN: Do you have any final thoughts?

Burlacu: Yes. What I’m excited by is the way the conversation is beginning to change from “Are we compliant?” to “Do we have the diverse talent on board and in the pipeline that we need?” It’s very satisfying to be part of an effort to help employers get good answers to those questions.

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