CURT NICKISCH: Before we start the show, I have an announcement. Some of you know that this podcast has been around since 2006.
PAUL MICHELMAN: Hello and welcome to the very first edition of the HBR IdeaCast, a soon to be bi-weekly audio show from Harvard Business School Publishing. My name is Paul Michelman. I’m an executive editor here, and I’ll be your host.
CURT NICKISCH: Between that first episode and this one, number 826, there have been some changes to the podcast icon, to the way you listen to the show, probably, to the host. The theme music has gone from that acoustic guitar, to driving electric guitars…
SARAH GREEN CARMICHAEL: Welcome to the HBR IdeaCast from Harvard Business Review, I’m Sarah Green.
CURT NICKISCH: And on to the strings of this episode’s musical theme. Despite all these changes over the years, some things have remained the same. The IdeaCast has always offered insightful conversations with leading thinkers in business and management, and another constant has been someone named Adam Buchholz. You hear Adam’s name in the credits – he’s had his hand in the podcast for 13 years. He produced hundreds of episodes before stepping up to manage HBR’s podcast portfolio. Now he’s moving on to a new challenge in a new organization. Adam, you’ll be remembered and missed. All the very best wishes to you in the future. And with that, on to our show.
Welcome to the HBR IdeaCast from Harvard Business Review. I’m Curt Nickisch.
The list of companies paying the price for bias against customers is a long one. Like the $50 million settlement that JPMorgan Chase paid after its mortgage brokers charged Black and Hispanic borrowers more than white ones. Or, the lawsuit that Sephora settled with Asian customers whose accounts had been blocked, suspecting them of purchasing items in bulk to resell them. Or, the reputation cost paid by Starbucks when a manager called police on two Black men who didn’t order anything. The manager assumed they were loitering. Turns out, they were waiting for a friend.
On this podcast, we’ve talked a fair amount about bias in hiring, in who gets promotions or who gets funding for their startup. But, one of the biggest places bias is at play is in the everyday interactions between companies and their customers. And with greater awareness in recent years, towards these risks and real costs, many companies are looking for concrete ways in which they can improve these customer interactions for the better. That’s where today’s guests come in.
Alexandra Feldberg is an assistant professor at Harvard Business School, and Tami Kim is an assistant professor at the University of Virginia Darden School of Business. They’ve been studying how to combat bias at the customer interface. And, they’re the authors of the HBR article Fighting Bias on the Front Lines.
CURT NICKISCH: Ali, thanks for coming on the show.
ALEXANDRA FELDBERG: Thank you. It’s great to be here.
CURT NICKISCH: And Tami, thank you, too.
TAMI KIM: Yeah. Thanks for having us.
CURT NICKISCH: I’d love to start just by finding out what drew each of you to study this, to look deeper at companies and bias at this customer relationship level.
ALEXANDRA FELDBERG: Part of what I love about the research that Tami and I have been able to do together is that we bridge disciplines. I think about people within the companies. Tami, being a marketing professor, thinks about the consumer side of things. We’ve found this research to be a great synthesis of our interests.
TAMI KIM: I think, also, aside from our academic experiences, I think both Ali and I probably confidently say, as avid shoppers, we’ve had many interactions often times, you would just psychoanalyze a lot of interactions. Why do we get a certain discount in this particular interaction? Or, oh could we have gotten a room upgrade through some of our conference travels together? There’s definitely a personal aspect to it as well.
There are just countless number of interactions that we have as consumers, for both very big and small purchases. And, that’s also one of the reasons why we thought it was so important to explore this domain, given the sizeable amount of time we spend with service providers.
ALEXANDRA FELDBERG: Absolutely. I think that the other thing that I think has been captivating for us has been just the really subtle ways that bias can manifest in these exchanges. It’s not just about whether an exchange occurs, but it’s about how much does someone go above and beyond to be helpful to you, what’s the manner in which they actually deliver the service. These elements of the exchange I think are often really subtle but really important to our experiences as consumers.
CURT NICKISCH: What are some of the main ways that you’ve seen bias show up in customer-employee interactions?
ALEXANDRA FELDBERG: We key in on three main ways, that we see bias in these interactions. The first is just the exchanges, the provision of core products and services. Actually going and being able to get that vegan poppy seed muffin that I got this morning.
The second is in terms of how willing people are to go above and beyond. We call this the extras that happen in the interaction. When you go to hotel, are you going to be offered a room upgrade for free? And then, the last is etiquette. Really, this is the manner in which service is delivered. If someone is smiling at you, do you feel like the body language is inviting and warm.
CURT NICKISCH: In your research, you find that customers with more white sounding names, for instance, can be called by honorifics more often. Can you give some more examples of just things that you find really emblematic of bias?
ALEXANDRA FELDBERG: We have a bunch of studies that really think about the information that service providers, people in the front lines are willing to give, and the volume of information. One study, where we look at hotel workers who are the front lines, we basically reached out to these service providers with people with different names to signal things like race and gender. We ask, really simply, for restaurant recommendations. The thing that I always find so interesting about our findings here is that there are actually differences in the number of restaurants that people with different names get recommended. We did all sorts of stuff to make sure that we were sending out emails to similar people, we controlled for all sorts of aspects of the experiment to make sure nothing was confounding the companies and the hotels that we were contacting. It’s fascinating to me, again and again, that there should be no difference in the number of restaurants that people get recommended. We see that that is the case. To me, that’s the kind of thing that I find so interesting. Even if you’re willing to help someone, or even if people are willing to provide the help, the information is quantifiably different.
TAMI KIM: In addition to the number of restaurants, we also saw that when emails came from white sounding names, hotel service providers were much more likely to go provide extra information. It’d be things like, “Check out these museums in our city.” Or, “There’s a library around the corner that’s lovely to check out.” It’d be information like that and our email inquiries didn’t ask for. But still, going back to what Ali was talking about, the information was quantifiably very different. It wasn’t just in response to the direct inquiry, which was about restaurant recommendations, but also so much more than that.
CURT NICKISCH: What do you think is happening in the minds of people who are doing that? What’s the root thinking there?
ALEXANDRA FELDBERG: From my perspective, I do not think that the differences that we see across these service providers is conscious. People aren’t intending to systematically give different information or resources to customers. That, I think, is partly why we find it so interesting. Our experiments aren’t really picking up, because they’re across different organizations, they’re not picking up one person’s bias. It’s in aggregate. For any one person, it’s not like someone is necessarily even being unhelpful. In some ways, it’s like people are just willing to give more information or better services to some people than others but I don’t think it’s intentional.
TAMI KIM: Often times, we think about discrimination as somebody being hostile against someone. But I think in this case, we’re seeing that discrimination can also happen from people being nice because here, it’s people are being nicer to certain groups of people.
CURT NICKISCH: Some people might say this is a human thing, it’s hard to tackle, it’s very nuanced. Why should companies buckle down and address this?
ALEXANDRA FELDBERG: Simply put, companies are not taking advantage of the resources, the talent they have at their disposal and leveraging the people at the front lines, if they’re not ensuring that there’s consistent, equitable service. So if you can act in a really favorable way toward one person, ideally you want that to be happening across every service interaction, to find new customers, to bring people into your business. To me, that’s the business case for this.
CURT NICKISCH: How do you start? As an organization, how do you start recognizing and confronting this issue? Yeah, and addressing it.
TAMI KIM: We emphasize the importance of actually first diagnosing the problem. Often times, we see that companies like to jump to solutions. They might create a diversity taskforce, or immediately shut down stores and order all the employees to go through implicit bias training, things like that. But, without understanding what’s actually going on in your front lines, there’s just no way that companies can effectively address that problem.
What we advise in our article is, before you do anything, you first need to diagnose the problem. You can do this in a few different ways. I think, in our minds, the most important step is to just go out and talk to your customers. And, make sure that you’re talking to a diverse set of customers. Not just your prototypical group of customers, your customers that tend to shop most often at your store, but go out and talk to people who aren’t necessarily your prototypical customers to figure out what their experiences are like, if there are any specific experiences or anything about your company that’s turning them away.
CURT NICKISCH: That’s classic management advice, identify the problem before you go out and try to solve it. Is it that people think they know what the problem is because they see the effects and just jump to conclusions? Or, why is it so hard to step back and assess what the problem really is?
TAMI KIM: There are probably a few different things that are going on. One of them is sometimes a big scandal erupts, like in the case of Starbucks, and they feel as if they need to do something to address that. It’s a very reactive process. At least in Starbuck’s case, just because there were two Black men that were arrested, doesn’t mean that’s the only problem that might be happening at the front lines. What would probably be more effective is for companies in those types of situations to take a step back and actually fully assess the situation, to come up with more comprehensive solutions. But, in light of many different social movements that have happened over the past few years, there’s also an increase amount of pressure from consumers.
CURT NICKISCH: Yeah. There was a survey in 2020 by Lending Tree that found that a quarter of those US respondents they surveyed had stopped patronizing a company because it was accused of racism.
TAMI KIM: Right. There is an increasing pressure from consumers as well, because they are no longer caring what kinds of products or services they are getting from companies but they actually care about what kinds of values companies stand behind. From that pressure, maybe companies feel like they should act.
CURT NICKISCH: Yeah. How does a company know that it has a problem like this, before it gets to this reactive stage?
ALEXANDRA FELDBERG: In some ways, there’s a positive thing here which is that companies are better equipped than ever before because of the data that they collect, to know how consistently and equitably they’re delivering service. Given all of the data that many companies collect today, I think ways to identify a problem are really to make sure, like Tami was saying, that there’s an ongoing conversation with a diverse set of customers that is happening to really understand the customer experience, and especially the service they’re receiving.
It’s important, also, to figure out ways to monitor and really be vigilant about monitoring the consistency of service that customers with all sorts of different attributes receive. That, I think, is a really important and ongoing step to take. We talk a little bit about this in the article, but I think this can’t be a one-off thing. It’s an ongoing process that we hope companies engage in.
CURT NICKISCH: What are some good ways forward?
TAMI KIM: There are a few different interventions that we suggest in the article. One of them is exposure, so just making sure that, as a company, you’re exposing your service providers to as many diverse backgrounds as possible and that they are able to serve as diverse set of customers as possible. Maybe this entails them revamping their training materials, so they’re reframing their prototypical customers to be heterogeneous rather than just one specific type of customer.
Another one is standardization. If companies can be sure that there are specific ways that service providers should behave when interacting with customers, especially as it comes to the three Es that we specified, which is exchange, etiquette and extras, then hopefully that can start to get at minimizing the gap in the types of service that are being provided to different types of customers.
CURT NICKISCH: Yeah. It’s interesting to think about the scripts that servers at restaurants follow. It can seem almost automatic. But, it’s fascinating how that standardization does create a more consistent and perhaps more equitable experience for people.
TAMI KIM: There’s a national restaurant chain, that instructs all their frontline workers to greet their customers a certain way. In many of our conversations with different study participants, what we’ve seen is that, often times, participants feel as if they’re being discriminated against at storefronts or when they’re boarding airplanes because they simply don’t get greeted. So companies, for instance, could standardize the ways in which they greet customers, or the ways in which they approach their customers, such that there’s as little variability as possible.
ALEXANDRA FELDBERG: I think that, often, excellence is something that many or most companies strive for in the service that they deliver. But, I think that equitability in service, I think to the extent that we can start to see that on par with or the same thing as excellence and consistency, that I think can go a very long way.
The last piece that we highlight in the article is the importance of making sure that people within an organization at the front lines are held accountable. The studies have shown that people are less likely to behave in biased ways when they think they’re going to be held accountable for how fair their actions are. To the extent that you can instill a sense of responsiblilty, and maybe it’s metrics that allow you to detect bias. You can talk about both signals that you’re serious about eliminating discrimination, and also can help people understand their own behaviors and be accountable for them.
CURT NICKISCH: I mean you’ve been studying this as the covid-19 pandemic has been impacting you know customer interactions, I just wonder if online retail is better or worse when it comes to customer interactions?
TAMI KIM: Actually a lot of the work that we’ve done has been before the pandemic. But you know I think one thing that’s important to point out is that you know pandemic or not, whether interactions are occurring online or offline, there are just many ways that biases can manifest. It’s just that perhaps the ways in which companies can capture the way in which those biases may manifest might be different. So for instance you might think about – let’s suppose that because of the pandemic a lot of these services interactions have moved online. Then the ways in which companies can track these or where biases could manifest might be in the types of language that’s used or the number of exclamation marks being used in service exchanges. As opposed to the tone of voice being used or the extent to which a service provider smiles at you if it were in an offline context.
CURT NICKISCH: Ali, you talked about data earlier. Is this something that big corporations have an easier time doing with their resources and their bent for standardization? Or, do startups and small businesses have a better chance at changing behavior because they’re just that much closer to the front lines?
ALEXANDRA FELDBERG: I’m not sure they’re necessarily it needs to be seen as a trade off between big or small. I think that sometimes it just might be the data that’s being collected might not be the right data to understand whether bias is even existing.
I think we think about it as the data collection. What data are you collecting? And then, with the data that you have, how are you looking at it? I think any company can be empowered to say, “Okay, what information can I get on an ongoing basis about the behaviors happening at the front lines?” What are creative ways that I can look at it, analyze it, link it to customer attributes, like Tami was talking about earlier, that might be very revealing about things that we might not even be aware about.
TAMI KIM: Suppose that, in your conversations with different customers, like in focus groups, you find out that many customers complain about call time, how long they have to wait when they have to chat with a service agent. In which case, that would direct you to your data, to see if you’re actually collecting information on that. If you have it, great. But, have you looked at whether call time waits vary across different customer attributes?
Often times, what we’re seeing is that companies don’t really dissect their data, they just see it as an aggregate. “Oh, what is our average call time wait this month?” And then, has that improved or has that gotten worse? Rather than dissecting it, by looking at how that might vary across different customer groups.
That would be one example of ensuring that you’re using your data effectively, to make sure you’re incorporating equity into how you’re looking at service performance.
CURT NICKISCH: A lot of this sounds like it has to come from the organization, it has to come from the top, it sounds a little institutional. If your part of that chain that’s bringing this action to the customer interface, what’s your role?
ALEXANDRA FELDBERG: I think that’s a great point. There’s so many … We’re taking an institutional perspective in this because that is a really important level to be affecting change from. For leaders and managers, I think it starts with values. Again, this gets back to this idea of emphasizing consistency and equitability in service. So really, making those things important, well known, clear across the organization as things that are really valued in how customers are treated. I think that that’s a first step.
I think the second thing is, getting back to this whole point about diagnosis, really making sure that if you’re in a position where you have a lot of data at your disposal, where you manage a bunch of folks who are interacting with customers, you make sure that you have a thorough diagnosis of what’s going on. Only then, once you understand the situation, would we really recommend intervening. But, I think those two things, the values and then following a process of diagnosis and then interventions, would be the thing that I think could cut across any organization.
CURT NICKISCH: We started this episode with some examples in the introduction, of companies that took big missteps and paid a price for it. Are there companies out there, are there examples out there that you look at and you think they’re just great models for what companies can be doing to take steps in the right direction?
TAMI KIM: We’ve seen a lot of focus from organizations, on the issues of diversity and inclusion, in terms of in hiring. But, we actually aren’t seeing that much effort and focus being given to the issues of diversity, equity and inclusion at the front lines. What we’re hoping, with this article, is that we can engage in more conversations with companies, to make sure that we can encourage them to embrace change, and to start thinking about these issues and start engaging in these dialogues going forward.
CURT NICKISCH: Ali?
ALEXANDRA FELDBERG: I think that I’ll maybe take a positive perspective on this, is there’s so much data that companies have that they can take advantage of, to try to understand these interfaces. There is a lot of attention on hiring, I think we know a lot about hiring and where bias can happen, and some interventions at points of hire than can be really effective. I think we can take those learnings and apply them to people at the front lines.
I think this is a place that I think both of us find interesting. There’s not as much knowledge about it. It just hasn’t been so much of a focus, from our perspective at least, in the academic literature. I think like Tami said, we’re excited for this to be a place that companies increasingly focus.
CURT NICKISCH: Ali and Tami, thanks so much for coming on the show to talk about this.
ALEXANDRA FELDBERG: Thank you for having us.
TAMI KIM: Thanks for having us.
CURT NICKISCH: That’s Alexandra Feldberg, of Harvard Business School, and Tami Kim, of the University of Virginia Darden School of Business. Together, they wrote the HBR article Fighting Bias on the Front Lines. You can read it in the November December 2021 issue and at hbr.org.
One company they mention in that article is Ritz Carlton, where any employee can spend up to $2000 to improve a customer’s experience. We did an episode on that titled Setting a High Bar For Your Customer Service, that’s episode 717.
This episode was produced by Mary Dooe. We get technical help from Rob Eckhardt. Adam Buchholz is our audio product manager. Thanks for listening to the HBR IdeaCast, I’m Curt Nickisch.
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