H@H Ep. 31 – On this episode of the Here@Haas podcast, Dr. Andreea Gorbatai joins Ray to discuss her time at Haas and research in the field of organizational management. We talk about a few experiments that Andreea had participated in, including how Wikipedia found realized which pages were most viewed, and why women raise more money than men in crowdfunding. Finally, Andreea tells us how organizational management has evolved in conjunction with big data, and why it’s already a science versus just a set of soft skills.
On the gender bias in venture capital – “Men and women entrepreneurs are asked different questions and namely, women tend to be asked questions regarding prevention. Like have you thought of what happens if things go bad? Which places the whole response and the discussion in a preemptive, negative, more fearful sphere.”
On the evolution of soft skills – “Soft skills have this reputation of being unscientific or being the leftovers after you do the scienc-y stuff. But the truth is that if you don’t understand how, confirmation bias, for example, factors in how you make estimates, how you estimate numbers in your predictions, it does affect your hard skills.”
On what is needed to successfully manage teams amidst the COVID crisis – “The perfect confluence of having the scientific understanding of what’s going on, and then having the soft skills to be able to show consistency, empathy, in terms of how you communicate as a leader.”
Intro: Hey listeners, before we get started with today’s show, we just wanted to let you guys know that we have a new domain. It’s haaspodcasts.org and it replaces the old onehaas.org. But it features our here@haas and OneHaas alumni podcasts in addition to our new OneHaas undergraduate podcast. So, please take a minute to check those out.
[00:00:25] In addition, we have an MBA blog with entries written by current and former students. Also, if you want to be part of our amazing podcast crew, there’s a Join the Team form. Okay. Now onto the show.
[00:00:41] Welcome to here@haas, a student-run podcast of the Berkeley Haas community. Today, we’re joined by Dr. Andreea Gorbatai, an assistant professor in the management of organizations group at Haas.
[00:00:56] Andrea will be teaching Leading People in the evening portions for the EWMBA this fall. Welcome to the podcast, Andrea.
[00:01:05] Andreea: Glad to be here.
[00:01:06] Ray So, before the show, we were talking that you grew up in Romania and I saw on your profile that you went to Dartmouth for undergrad and then began your graduate studies at Harvard. At what point did you realize that you wanted to study organizational behavior?
[00:01:23] Andreea: My interest in academia started with mathematics. I really liked studying mathematics. I liked developing proofs. I admired the beauty of mathematics as a science but somehow in my mind, it never connected with the real world. Nobody ever explained to me, I’ve never come across explanations of how mathematics translated into the real world. So then when I started my undergraduate studies at Dartmouth, I discovered economics and it felt like a very natural application of mathematics because you have functions like demand function, supply function. They have an elegance to them, they have a beauty to them in representing what happens in the real world.
[00:02:09] And as I progressed in my undergraduate career and majored in economics, I realized that the predictions of classical economics don’t really match what happens in the real world. So that’s, in some ways I would say, that’s like one, the roots of my interest in sociology.
[00:02:27] Sociology studies people in groups, teams, organizations, markets, at aggregate levels. Progressing from there, from my undergraduate studies, I have worked in economic consulting and in management consulting, and one particular issue I’ve come across in my management consulting work was the idea of knowledge repositories.
[00:02:48] I was working for Deloitte consulting. There were lots of great projects, lots of great minds, and the knowledge repository for all the deliverables produced for all the knowledge shared within the organization was just a mess. It was impossible to search. It was disorganized. People were incentivized to submit materials but there was no quality check.
[00:03:10] There was no tagging, labeling you as just so the incentive was to contribute but not rated by quality of contributions or any other criteria. So, I realized that there’s a problem in how people self-organize, how people cooperate, how organizations function that doesn’t reside in an abstract sort of like the mathematical world.
[00:03:32] And it doesn’t really reside at the individual level. It’s more of a problem of aggregating groups of people, which is organizations. So, this is how I ended up applying to the organizational behavior program at Harvard where I got a master’s in sociology and a Ph.D. in organizational behavior.
[00:03:51] Ray Wow.
[00:03:53] Andreea: So I actually majored in applied mathematics as an undergrad. I did actuarial science. And, I guess it might be a good thing that you didn’t find out about it because that would have taken you down a whole different path.
[00:04:06] Ray: Alright. So fast forward several years, uh, you did your masters and your doctorate at Harvard; tell us how you got to Haas.
[00:04:15] Andreea: So, I guess the way things work in my field is that people complete a dissertation, submit a dissertation in their respective fields that gets defended and approved. And in the process of completing their final year, students apply for professor jobs. My field, by and large, does not do any postdocs so people finish their Ph.D. and move to being in a faculty position, either tenure track or non-tenure track.
[00:04:44] Okay. So, while graduating from Harvard, I have interviewed four professorship positions in different parts of the United States and Canada and Europe and, well, Haas by far my favorite. I think multiple reasons my colleagues are fantastic. So, our department has, you know, world-renowned psychologists and sociologists. The overall collegiality interactions with the rest of the faculty at the business school are very strong, like we have sessions where we share our research with colleagues and other departments.
[00:05:21] So, I think in a lot of other schools, I wouldn’t know, for example, of research as someone in the finance group or accounting group is doing. Whereas here we have these brown bag lunch sessions where people present sort of a high-level picture. These are questions I’m looking at, this is the data I have. So yeah, that gives opportunities for, you know, it’s not just collegiality and community but actual collaborations across departments or, you know, understanding of different perspectives that people can have on the same phenomenon on the same data set.
[00:05:52] Ray: So then let’s move towards your area of research and expertise.
[00:05:58] I think your research focuses mostly on social mechanisms related to knowledge production and information sharing but you also study the role of language and emotion on markets. So, actually, I want to start with this one first because you did a study with another professor from Kellogg and it seemed like as I was reading through your paper, kind of the gist of this study is that women are better than men at crowdfunding. So, actually, I just want to ask you about this and maybe just tell us a little bit about the study and what you did to come to that conclusion.
[00:06:40] Andreea: There’s always a lot of nuance to how one interprets research findings. So, there are multiple levels to what you just said and how that relates to my research project. So, first, I would say there have been other researchers who have looked overall to see how women and men fare in pro funding settings.
[00:07:01] And there’s been a rather consistent finding that women are more likely to meet their fundraising goals and they’re more likely to raise more money on average than men. So that’s a finding that was established before my work. Researchers from NIU and Wharton have found a couple of years ago that for women in technology, so women who are posting projects related to technology, there is particular motivation in terms of receiving funding from women who are donating for the purpose of furthering the cause of women in technology. So, what they essentially termed when we refer to women giving to women would say there’s homophily when you have a woman giving to women to further the particular cause. The researchers referred to it as activists’ homophily.
[00:07:55] So it’s not just, it’s like I’m giving to people like me but I’m giving to people like me because I know people like me have been systematically disadvantaged in this setting.
[00:08:03] What my study adds to that proposition is that women one can debate whether it’s nature or nurture.
[00:08:12] Andreea: But statistically speaking when researchers and linguistics have looked at the way men and women speak over a large sample of communication, so things like diary or stories or emails, women tend to use different linguistic patterns than men in some very consistent way.
[00:08:32] So the average for women is different from the average from men. There was some overlap of course. So, there are women who speak was linguistic markers that are closer to men and men who speak with linguistic markers that are closer to women. But, some things that stand out are that women tend to use more positive emotion words.
[00:08:49] Women tend to use more words that have to do a social connection, was relating to others and sort of like care-taking, caregiving related words, and women tend to use more words that have to do with senses, was perceptions feel so like velvety, colorful. So, when looking at the descriptions what my coauthor and I did is that we looked at the descriptions of how men and women proposed projects on crowdfunding platforms.
[00:09:20] They’re specifically looking at Indiegogo, you know, our data. And we matched as closely as we could using natural language processing. We matched the type of project. So, in other words, we wanted the same type of product and then also comparing for similar levels of funding.
[00:09:39] So you don’t want to compare a project that requires a thousand dollars in funding to see David Richard Stargate was the project that requires $50,000 because obviously there’d be different, maybe there’s different complexities, there’s different hurdles to reach the two limits. So,apples to apples.
[00:09:55] Ray: apples to apples.
[00:09:56] Andreea: Exactly. As you said, the other prior finding in the literature has been women tend to ask for less money as well. So, you don’t want to say, well, women succeed at attaining their goals just because they ask for less, obviously, the hurdle would be lower.
[00:10:15] So, comparing this, we basically find that women are more likely to reach their targets in our setting. So, looking at the purely small business and technology areas, we find that women are more likely to reach their goals. And we find that 20% of this difference in likelihood is explained by the language that women use. So, women basically use language that has to do more positive emotion and better relating to the needs of a potential customer, connecting with the customer, and using more sensory words.
[00:10:48] Ray: And, this is written, right? Like emails, like we’re talking about texts that’s written, like you’re not recording conversations. Okay. So maybe the use of just different words, like you mentioned, right? And, indicate positive emotion, that indicates, I guess, a willingness to cooperate or collaborate, maybe more telling at least in the field of crowdfunding.
[00:11:11] Andreea: To add to our findings and other things that we have looked into, we have looked into whether, uh, women are more likely to give to women who use these words or it’s a more general, like a more universal phenomenon. When we have found that both women and men are more likely to give to people who use these words and, you know, by the fact that some of like more of these people are women, women benefit from this but like overall, you know, you’re a student, you’re doing your MBA, very often when we talk about that elevator speech or we talk about, you know, how do you do a pitch as an entrepreneur? We say, you know, be like, upbeat and competent and be excited, propose it as a win-win.
[00:11:54] So women, they’re more likely to use words like this. So, this particular language lends itself to being more successful in this setting.
[00:12:02] Ray: So, I think in summary, your study shows that a big part of why women are more successful in crowdfunding is the fact that they can come up with its elevator pitch with positive words, being able to relate to others and with sensory or emotional words, in a written form. They can kind of convey this in a written form a little bit more easily or at least more relatable, more understandable, to the crowd forming platform than men.
[00:12:32] So then if you just take this finding and apply it to non-crowd funding sources, like a VC pitch, is this disparity not as significant in favor of women or even reversed?
[00:12:44] Andreea: I would say there are several factors contributing to different results in the world of crowdfunding. One of them would be, as you mentioned, the audience for crowdfunding is very different than the audience for venture capital. So, venture capital is largely male dominated, whereas crowdfunding, the number of people contributing as donors is more even between men and women, right? Because you can contribute any, some, the barrier to entry is low, both on the side of being a participant proposing a project on a crowdfunding platform and on the side of donating money. And the motivations to some extent are somewhat different in a crowdfunding setting because in some ways you contributing to help, you know, people you admire or your friends in other ways, you’re contributing to pre-purchase a product.
[00:13:29] So you’re giving money to get a pair of headphones whenever they get produced. So you believe in that person but the strategy is somewhat different from having a portfolio was like distributed risk in a venture capital setting. So, that’s certainly a difference. The other thing that happens in the venture capital setting is that basically gatekeeping where it’s been shown men largely prefer people who look like them. So, there are more men overall in the pipeline, in the process.
[00:13:59] There’s been studies that have been done was a flip scenario where you are varying the picture of the entrepreneur and you’re giving people the same text and basically in the situation where you have a male entrepreneur and in particular where you have a handsome looking male entrepreneur. They are rated by far as more prepared, more competent, more coherent for the same than a woman entrepreneur.
[00:14:26] So, there’s an overall societal bias for what a stereotypical entrepreneur would look like and that tends to favor men. So when you’re hearing a woman delivering the pitch versus a man delivering a pitch, the content is only part of what is being judged.
[00:14:42] Andreea: Um, the other interesting finding that I’ve seen in this field regarding venture capital and pitches is that in a venture capital competition, men and women entrepreneurs are asked different questions and namely, women tend to be asked questions regarding prevention. Like have you thought what happens if things go bad? Which places the whole response on the discussion in a preemptive negative, like more fearful sear. Whereas men tend to be asked questions about scaling and prospects and how to grow the business.
[00:15:16] And that gives you more room to say positive things, just because it’s much easier. So, there’s not only differences in how men and women’s pitch delivery gets judged in venture capital settings or like angel investor settings, but also in the follow-up questions that they get asked which is something different from crowdfunding, where you deliver your pitch and you leave it there for people to read and decide. It’s not as interactive as a face to face setting.
[00:15:42] Ray: Right. And, that is super interesting because when you think about questions on prevention, you’re already assuming things are going to go bad. Right? Whereas when you ask questions about scaling, you’re assuming that your initial product is good and you’re going to now distribute it. So, this type of bias can really tell a lot about people’s mindsets even before, you know, a company is formed.
[00:16:07] So, okay, I want to shift gears to your work in studying social mechanisms, in particular related to knowledge and information sharing.
[00:16:15] I think one of your papers, it’s called The Paradox of Novice Contributions to Collective Production. I think you mentioned how collective goods fail to satisfy consumer needs in the absence of direct information from those consumers. Um, and it seems like it’s basically saying that people don’t really know what other people want. Can you tell us just a little bit about some of your work in that area?
[00:16:43] Andreea: Yeah, of course. So, it’s this is a prime example of how some of my early work has come out of my training in economics. When it’s actually both my training in economics and my own experience using the internet using computers. So, in economics, there’s a nobel prize that’s been awarded for work on free writing and public goods production. And the main problem when it comes to public good production has been how do I allocate these goods? How do we decide who contributes? Like what is being contributed to them and how do I avoid people taking more than their fair share or not contributing enough when it comes to public goods and comments?
[00:17:29] And, what occurred to me as a user of computers was that one of the things that was happening in early 2000 was a proliferation of information of knowledge. And knowledge is free. it’s a public good. We can consume it. You can benefit from it.
[00:17:45] And this does not preclude you, other people, from consuming it, right? So, it’s sort of interesting because that raises the idea that one of the solutions to public good production is, for example, status.
[00:17:55] If we really admire, if we somehow social the reward people who produce public goods and we say, wow, Ray’s amazing. It’s such a cool blog post. I want to recommend it to people.
[00:18:05] Ray: Podcast. Podcast episode.
[00:18:08] Andreea: Podcasts are an excellent example. Thank you. Yeah. So, Ray producers, an excellent podcast. Ray will produce this podcast for free because he gets recognition.
[00:18:17] Like people will know about him. People will know to admire the work.
[00:18:21] Andreea: So, that’s one potential solution to public good production. But one funny thing that happens when you start looking at things like open-source software is that you, as a user, would download a piece of software and it kind of does things that you wanted to do but like not really anything. It wasn’t a piece of software you paid for or you would write to customer service, you would upgrade, you would ask for more features, you can, you can protest and somebody who can signal what you want. But if it’s an open-source product, it basically does what the original producer wanted it to do. So there’s a very large literature.
[00:18:57] The, you know, field that’s referred to as user innovation and the premise of it is that a lot of inventions actually come from people solving a problem they have. So, for medical equipment, for example, there will be people who have to wear medical devices on them and they will come up with innovations because the medical devices are uncomfortable, like, malfunctioning or has a problem. And they find a solution for themselves. And this may apply to other people or it may not for sports, right? So there’s someone who wants to do a super cool track on their skateboard or on their bike and they will do things to the bike and other people become interested in it, then they say, Hey, why don’t you make a company that sells this add-on for bikes or skateboards or whatnot.
[00:19:43] So, there’s an entire field that has found that somewhere around 50% of innovations put forth by small companies come from basically user innovation. The founder of the company, someone who had a problem and solved it by creating those products. So that’s what happens on open-source software.
[00:20:03] Very often someone writes software that they need and then they will put it in a public repository. And the particular phenomenon that I studied in the case of Wikipedia. Yeah. Is that the pages that were being created and they had a lot of detail and they were, you know, well-referenced and very developed, were not necessarily the pages that were highly viewed that were not the pages. Do you think or are of the highest interest, right?
[00:20:25] So the people who were very dedicated. I’ve interviewed people are contributing to writing Wikipedia pages are people who are very dedicated to their, uh, contributing for free and creating a high-quality encyclopedia. But to some extent that they were not necessarily producing the things that were most used.
[00:20:42] So what I did is that I tracked down the person who was maintaining at the time that we could PDL servers, who was a Lithuanian hacker, listening.
[00:20:52] Ray: Oh, wow. Sounds exciting.
[00:20:55] Andreea: And I got the server logs for page views because you don’t know how many people are seeing a page. You kind of think that a page like oxygen or New York City would have a lot of views but I do not know necessarily to what extent the quality of that page is aligned.
[00:21:11] Does the number of views. So, I basically looked at this and I looked at the people who were contributing to the page and interviewed people contributing to the page. And one thing that I found is that Wikipedia had this really it’s a deceptively simple but very effective way of replacing what would normally be the price mechanism.
[00:21:30] So in a market, you produce things and people don’t want them, you can sell them. If you produce things and the price is too high, people don’t buy them, right? If a lot of people buy them, then you can raise the price. And, you know, there’s a supply and demand mechanism that functions very well.
[00:21:47] Whereas when you’re producing things that are afraid, there’s no visible mechanism. There’s no visible way to….
[00:21:55] Ray: To gauge to the demand.
[00:21:56] Andreea: To gauge what is the demand? So, what the people who are contributors to Wikipedia are doing and I’ve spoken with him about this and then measured this longitudinally over time, it said they would pay attention.
[00:22:10] They would monitor multiple pages. And they would see when people we’re not regular contributors. So, sometimes even anonymous editors would attempt to add things to the page.
[00:22:22] So sometimes people will come and they will not know how to write, contribute to the page, but they will drop a link or they would correct a number or something. And they would infer from this. People are reading this page. If one person made a correction to the year, there must’ve been 20 people who looked at this page. There’s a ratio of like views to click-throughs. And they would infer, this is a page that’s important to people. This is a page I should pay attention to.
[00:22:50] It’s signaled. I should divert my attention to this because this is something people care about. And take away from it is that sometimes people who are contributing and horror, voluntarily producing public goods and have very good intentions, might not know exactly what is that they need to be producing.
[00:23:09] Right. So, you imagine even in a situation like public education. If you don’t have a way of percolating what is the demand for particular subjects for particular curricula, it’s very hard to aggregate a higher level and know this is what we should be offering.
[00:23:26] Ray: Okay. I want to shift then to your teachings at Haas. So, this fall, you will be teaching the leading people class for the blue and gold cohorts of the evening weekend program. Tell us about the class and what its goal is and what it focuses on.
[00:23:45] Andreea: So, the class is a core requirement class. Broadly speaking, it is an introduction to topics of leadership and management. So, it covers a range of topics from discussing teamwork, bias in decision making in teams, and in individual decision-making, negotiation, you know, vacations of networks, diversity, and inclusion.
[00:24:10] So it’s a broad survey of what it means to be a good manager, what it means to be a good leader, and the principle behind it.
[00:24:16] The principle that I like to use for the class is to rely on experiential learning. I use case studies. I use a lot of role-playing exercises where we take different roles in class and play out a scenario and then sort of unpack takeaways from this and then move on to discussing the theoretical principles of how one would go about dealing with this problem and discussing research findings because I always think management and leadership in general, soft skills have this reputation of being unscientific.
[00:24:50] Being unscientific or being the leftovers after you do the sciency stuff. But the truth is that if you don’t understand how confirmation bias, for example, factor in how you make estimates, how you estimate numbers in your predictions, it does affect your hard skills.
[00:25:11] It’s our brain. It’s important to understand your brain and other people’s brains and how social interactions work because it does affect how we think about harder things like predicting numbers, what do you think of a scientific.
[00:25:25] Ray: That’s a great point. I think in the last, I want to say 10, 15, maybe 20 years but definitely in the last 10 years, I know that people operations, like people sciences has become an ever so popular field, especially within the tech industry where instead of using traditional metrics to gauge how you’re hiring, like for example, years of experience, right? Someone who has 20 years of experience could have a much different profile than another person who has equivalent amounts of experiences but doing slightly different tasks or different roles under the same umbrella of responsibilities.
[00:26:07] So, this utilization of science in the soft skills, I can see becoming even more popular as we move into a world where, uh, especially now with COVID, like, it seems like there’s going to be a lot more remote roles.
[00:26:24] Andreea: The other thing that I tell my students is that when we think of, I don’t want to give away too much of my lecture but when I think of evidence-based management, we think of leading people, we think of managing people.
[00:26:39] There are multiple ways to get to the same finality and there’s no guarantee, right? People are not, people are not buttons, right? It’s not like you push this button and you’ll always get the same outcome. It’s not physics. So, you don’t always have a guaranteed result. Probabilistically, if you do this instead of that, you will get better results. There are a lot of other factors that contribute to that outcome when you were talking about a team, when you’re talking about performance, when you’re talking about negotiations, but there are demonstrated and proven scientific ways to improve your outcomes.
[00:27:10] Ray: Right. Yeah. And then we had Don Moore on the podcast earlier, I think last month. And he talked about really believing kind of improbabilities, right. And using probabilities and using expected values and using confidence intervals to make decisions. And just because a decision didn’t turn out well or maybe fail doesn’t mean it was a poor decision, right?
[00:27:32] And there’s a lot of decisions that are made that were good at the time. And, um, unfortunately, sometimes you just get unlucky with certain market forces. And so, one thing you mentioned earlier though, Andreea, that I want to go back to is just the management of organizations and being a good leader.
[00:27:51] What are some things in your research that you found that are maybe some pitfalls to avoid in being a bad leader?
[00:27:58] Andreea: As gone more, uh, my colleague Don Moore, uh, has discussed overconfidence is definitely one that has been societaly encouraged and rewarded. So, that’s definitely one of them, I think very often one of the pitfalls that I’ve seen in addition to that is either over-reliance or blaming culture.
[00:28:17] So thinking that if you build it right, they will come. If you have the right technology,f you have the right idea, it will be obvious to people. Everyone will be on board. The organization will change. Everything will change. And if they don’t, if their fault and the culture was not right or because you don’t have the right people.
[00:28:37] And I think very often this sort of highlights the blind spot of how people work. Right? So, one of the things that I’ve seen very often and that’s research Stefan has found in their studies as well in my field is that especially in lower levels of management, people tend to be promoted from a technical position into a managerial position.
[00:28:59] And there is this temptation of leading by example. So, look at me and if you do like me, you will be successful and it’s a bias that can translate into discrimination. In a lot of settings, people who are like me, people who do things like me, are the promising employees and people who are different or people who don’t come from the same background, from the same understanding, they can’t keep up. I’m not going to give them interesting tasks. I’m not going to be engaging with them in the same, coaching them, or engaging with them to the same extent and this affects the way people develop in organizations and the dissatisfaction was working in organizations.
[00:29:36] So, I think that very often what we see is that there is a focus on getting the tasks done or there is a focus on having the right idea. And there’s not as much as a focus on communicating and implementing the changes or the technology is consistently and clearly and motivating people for change.
[00:29:59] Ray: Right. And that example that you brought up especially in the tech world and a lot of industries or roles where technical skills are valued, I’ve seen that many times in my career as well. It’s just whoever is the best programmer, for example, gets promoted to become the manager.
[00:30:18] Even though he or she may not have the best skills that are necessary from a management perspective. Right? And so, another point you mentioned was hiring people or promoting people that think like you, that look like you. Well, that basically goes against diversity, right? And diversity inclusion.
[00:30:39] Because you’re hiring the same people that either look like you or have similar personalities and that’s really against all of what diversity is about. So, in your studies then, how has the management of organizations have evolved over the time that you’ve studied them?
[00:31:00] Andreea: There’s two tendencies that I have observed, I should say. One of them has been in the study of organizations. The organizational theory field has had some of its seminars, works, and theories published in the late 1970s, early 1980s.
[00:31:17] And these theories evolved into different fields. I would say that in the past 10 years or so, what I’ve seen is, I’ve seen an increase in more precise measurement. So partly because of the availability of big data. We have emails, page views. If we were looking even within or organization, right? We have Slack channels, you’ll have all sorts of digital communication and deliverables and everything is documented electronically so you could see people, performance, appraisals, you can see applicants, cover letters and things like that.
[00:31:53] So you can process all that and it’s not only that you are processing large amounts of data so you can find correlations, you can find patterns, you can’t even find causation between different things.
[00:32:03] So for example, if you have communications in an organization, you could look at how a person’s email communication diverges in form and in content from in the language that’s being used from their colleagues as the person is thinking of leaving or is being counseled out of the company.
[00:32:20] Right. So, there’s visible patterns we can find in text data right now that we couldn’t find before. The other significant change that I’ve seen is that again, due to the availability of online platforms and software, computational methods, there are many more experiments that are being run in my field. For example, if you want to see how music shakes give diffused, right? You could have half of the people who are going just this. Spotify page or Pandora page gets one information about the song or via recommended something. And the other half is being recommended, something else or getting different information about how many times a song has been liked or something.
[00:33:00] And you could randomize that and run a natural experiment at a scale you wouldn’t have been able to do.
[00:33:05] So, there’s been more experimenting and there’s been more use of big data and computational technologies, which allows us to measure things much more precisely and pick up on patterns that are, you know, statistically more rare.
[00:33:17] Ray: Yeah. So, it sounds like in summary, then the presence and abundance of data, over the last 10, 15, 20 years, really, since companies and organizations have gone online has also evolved the way we track and make decisions within the management of organizations.
[00:33:37] Okay. And then today, of course, right now, as we’re talking and we’re right smack in the middle of the pandemic in the US. So, how has COVID changed the management of organizations in the last, let’s just say five or six months?
[00:33:55] Andreea: That’s a very interesting question. And obviously this is a question for which I think the answer is still evolving. Um, there are a lot of organizations facing very critical financial situations users, the COVID crisis, and corresponding economic crisis in the US and elsewhere. And there are a lot of people in either unemployed or difficult child care or home caregiving situations, so I think it’s added a little complexity to organizations. I think one takeaway I would have from it is that it sort of the perfect confluence of having the scientific understanding of what’s going on and then having the soft skills to be able to show consistency, empathy, in terms of how you communicate as a leader to your employees. Being reassuring, being transparent, all these things have become much more important than before. I would say that before a lot of organizations function business as usual, to some extent your leadership matters, but to another extent your organization, culture, and structure already in place. So, it’s a difference between having a car that’s on the road and the car works and you have a driver who’s a, you know, they can drive, you have a leader who can lead. And now as a COVID crisis, it’s like being in bad weather, being some sort of crisis condition where, you know, having a leader who’s quick thinking, who is self-aware and all these things are magnified importance because it could be much more critical for the organization and for its employees.
[00:35:37] Ray: Right. And I think we’ve seen COVID hit some industries harder than others. So, I love your analogy, by the way. I’m just picturing like some people in some industries are like getting massively rained on there’s like thunder, and then other industries, you know, maybe there’s just a slight breeze.
[00:35:55] Ray: So lastly, we have some lightning round questions.
[00:35:59] Ray: I read that you were fluent in five languages, Andreea, so very impressive. And listeners, it’s on her page which five languages she’s fluent in. But if you were able to magically learn a six without putting much effort, what do you think it would be?
[00:36:15] Andreea: I think it would be a tonal language. So maybe Mandarin or Cantonese or perhaps Japanese, just because I think there’s a lot of things that get lost in translation that I would love to be able to access and understand in an original.
[00:36:29] Ray: Very nice. What has been a habit that you picked up good or bad while sheltering in place?
[00:36:37] Andreea: I would say that the best habit I’ve picked up during sheltering in place has been that I have learned to live was my negative emotions. I have had the habit of doing things like hobbies, activities, going dancing, going to yoga when I feel distraught or I feel upset and not having that same, especially like the social outlet for it, it forced me to look at myself in the mirror more closely.
[00:37:09] Ray: Self counseling. I like it. I like it. Awesome. And then what’s your favorite type of music?
[00:37:14] Andreea: I, so, that actually relates to my social habits. I dance Argentinian tango. So, I would have to say and hang on.
[00:37:25] Ray: Okay. And then is the music in Spanish or English?
[00:37:30] Andreea: Ir’s Spanish. A sort of 1930s, 1940s.
[00:37:33] Ray: Okay. And then what is one thing that you miss from living in Romania?
[00:37:40] Andreea: I think the thing that I’d miss most and this is perhaps tinted by my experience being in the lockdown as I missed the fact that people would be much more open to stopping by each other’s place or hanging out or spending time together in a way that’s more casual and less formal instructor then than in the United States where you have to be on someone’s schedule in order to get to see them.
[00:38:03] Ray: Yeah. And I would say, especially in the digital age where now even calling someone without notice, I feel like it’s a little bit weird.
[00:38:12] Andreea: Very intrusive.
[00:38:14] Ray: Yeah. Okay.
[00:38:16] Ray: So let’s just wrap with this, Andrea, if there’s just one lesson that you want students or listeners, in general, to come away with after listening to this episode, what would it be?
[00:38:26] Andreea: I would have to say that one thing I would like my students to take away from my class and from being at Haas, in general, is our principle of being students always. Though the world is a changing place and the volume of information that we’re being exposed to the quality of information we’re being exposed to is highly variable.
[00:38:48] The volume is very high. So, learning how to learn, learning how to find answers, relying on each other, I think is one of the most important aspects. And relying on evidence, on scientific reasoning in order to find answers to our leadership and management challenges.
[00:39:08] Ray: Awesome. Well, thank you so much for your time today, Andrea.
[00:39:12] Andreea: Thank you so much. It’s been a pleasure.
[00:39:14] Outro: Thanks for tuning in to another episode of here@haas. If you enjoyed the show, please leave us a rating or review on your favorite podcast player. For more episodes, check out our new website, haaspodcast.org. I’m Ray Guan. And we’ll see you next time here at Haas.