Khanh Vu immigrated to America as a young child. As he grew up among American friends and worked for American companies, he found himself straddling two worlds – he was expected to act one way at home and another in American society. In his role now as the leader of the Society of Asian Scientists & Engineers, he helps others who find themselves existing across different spaces.
In today’s episode, Khanh explores data from the point of view of needing your numbers to know if there are issues – what really is the makeup of your community, your organization vs your leadership? Are there groups getting left behind? You can’t know that unless you look at the numbers. He addresses the resistance to being transparent with these numbers, and that we MUST move beyond that.
What You Can Do
Ask yourself: is my team or my organization honest and transparent with the data on our people? If so, what story is the numbers in your organization showing? If we aren’t, why not? What would it take for us to open up? Are we collecting that data but sitting on it? Or have we not even begun to collect it?
Click to read the auto-generated transcript of today’s episode
Hello and welcome to Heart, Soul and Data, where we explore the human side of analytics to help amplify the impact of those out to change the world. With me, Alexandra mandarins. Today we get to speak with Khan Vu the Executive director of CS Society of Asian Scientists and Engineers, and Kannan, I met this past year at the conference for the Colorado Nonprofit Association, and I was there presenting about a value based decision making framework with data and we hit it off and I really wanted to bring him on to share about both his professional expertise as an engineer and a mathematician himself around data, but also how, as an executive director of a nonprofit, tackling some really challenging cultural and systemic issues and helping the advancement of Asian scientists and engineers. What role does data play in that? How does he view data? How does he look at data within his own organization? We also have some very interesting conversations about the challenges facing Asian scientists and engineers in the advancement of their careers and how it is a very multi faceted challenge.
And I think that understanding the complexity of the issues that we’re all here to solve, whether they are issues around particular groups of people or issues around environment or issues around whatever it is, the things we’re here to solve as nonprofits, they’re not small, simple issues. Otherwise we would have solved them already. So we have a great engaging conversation about both the challenges his organization’s trying to solve and the role that data can play in doing that when there isn’t necessarily a clear, obvious solution at hand, and that the change you’re trying to bring about is going to take a long time.
So enjoy. I am thrilled to be joined today by Khanh Vu, who is a kindred spirit in the STEM field. Do you mind introducing yourself and tell us where you’re also calling in from all over the world these days?
Well, thank you for having me on the show. I attended your workshop and I love that. In word, we talk about collaborating and introducing you to some of my work. So I’m very excited. My background, see some identifiers. I mean, immigrants, the first generation chemical engineering by training worked in the petroleum oil industry for a few years, have a real estate license.
Did we tell it Higher education was retired in my thirties. That’s a whole different story too. And then so my passion working for a nonprofit as a volunteer, and then eventually the CEO and executive director of the Society of Asian Scientists and Engineer. I also go by the E in.
It’s perfect. Thank you so much for joining. And I know we’re here to talk about data in part from that engineering and STEM point of view and all of the wonderfully dynamic background you bring to this. It’s one of my joys of seeing how everyone has different paths to coming to data into science. And I think it makes it that much richer and more valuable.
But we’re also here to talk about your because you have this hands on experience with being so involved in a nonprofit as well. So you have a professional experience with science and data, but you also have that professional experience with nonprofits. And I think that combination is incredibly valuable for what we want to talk about. And I was curious.
Let’s start because I think this is an area that is so easy to mess with. Just what does data actually mean to you? When we use that word to you? What is data.
Away? You dive into this. You know, given that. We don’t ask small questions on this show, right? Raw data and zeros and ones, I mean, I’ve programed a machine language. So, you know, data is just information, right? It’s just information from advice. Information measured in tables, graphs, whatever. It’s basically basic information.
In your mind, what do you actually have to do to do that to make it useful? So we talk about that really at its core in a digital age, data, zeros and ones, but strategically it’s any information. So how do you actually take that and make any sense out of putting it to use?
There’s this beautiful diagram that I seeing on the Internet and shows that data is like a bunch of Lego bricks, that you just smash them a draw from off. And that’s your data, right? But it doesn’t tell a story, right? You can sort it out in stature by colors that kind of tells a story or you can build a basic piece and that tells a story, or you can create a marvelous Lego house with a garden and everything like that that tells a story.
So with the data bricks or data information, it’s really how you view and how you want to tell your story. I think that translation, it’s an art. We all collect data. What is that law where we’re collecting more data now than ever and story and we don’t have enough capacity to store all the data that we’re creating, right?
So it’s not a lack of data. It’s really the art of how do you tell that data? And I love math. One of my bucket lessons to go teach calculus. I really want to go back and see, I think in calculus first and second derivative, I mean, in areas of the graph science. So I mean, till my oldest son is in really freaked out and I said, I can’t wait for you to get the calculus so I can.
And I always said, I’m going to substitute for your math teacher one day. And he said, You know that you can tell in my school you cannot substitute for my class. Anyways, I love I’m a math. I still can do calculus 30 years later. I think that the story is the key, right? You have to know your audience.
You know you have to know your message and you don’t have to know the format. Is that a paper? Is it a presentation? Is it in a video? How will it be received and what is the emotion? And that’s why I love your presentation. It’s about what are you trying to tell? What is that story with the emotion that you’re trying to elicit from your audience?
What will they walk away with at the end of the day? And that’s your key. I went to John F, John F Kennedy High School here in Denver, and I’m calling it from Denver. As you asked earlier in our English teacher actually was in attended Kennedy and she actually met Robert Frost, the famous American poet Robert Frost. And she attended and she retold the story to us as someone asked him like, you know, the his famous poem, The Road Less Traveled, by which road do you take?
And the student asked Robert Frost, like, What did you mean when you wrote that poem? And Robert Frost turned around and asked the students, or How did you interpret it? Right? So when you’re listening to a poem or presentation and that was explained to me, symphonic terms is like Beethoven or Mozart. Whoever wrote the symphony and had something in mind, the conductor has something in mind, and the audience is receiving the play.
The people in the orchestra plays it with something know, and the audience. We see that. So each one of those parts, if you want to take it, how you intended versus how people are receiving it to how the audience is, you really have to go through that whole storyline to get the most impact at the end of the day, you know, because you could only say, I want to present this in any way.
Totally different impression I got. I did see that coming. But anyways, I know that I answered your question like a lot of metaphors by poetry that helps frame that.
It’s the power of story, right? I mean, that’s why we use metaphors to explain things, because the way that it is most accessible to us to understand things is having something that is relatable, that makes sense to us, that connects to how we see the world and connects to our understanding, our conceptual map of how the world works.
And I think that’s why one of the most powerful parts of what you said, that it’s not about a lack of data. Most of the time the data are out there. There might be a lot of work to get them into a shape that is usable in any capacity. But the data exist out there most likely, or they can be gotten, and it’s actually paring away the stuff you don’t need.
Right. My son is super into Lego, so I loved that analogy because I have literally thousands of Legos all over my house and he has this giant bin of Legos and you do not need, you know, 4000 pieces to build the helicopter that he’s working on. In fact, he has to sort through and discard, you know, put aside, put down, say, nope, these aren’t for now.
And just find the pieces that are necessary for building. And yes, the first step is sorting, right? It’s finding those patterns, finding those connections, saying, all right, what actually is present in this giant jumbled up mass of Legos? And then it’s setting a bunch aside and saying that’s not relevant to what we’re trying to do. But you have to know what you’re trying to do before you can say what’s not relevant to it.
So to your point, knowing the audience saying, How do we bring together the conductor’s point of view and the audience’s point of view and our orchestra’s point of view and understand where we’re trying to go, what we’re trying to achieve all together. And then it makes it clear which Lego pieces you need. And you’ve got to do all the hard work to put them together in a way that makes sense and and gets you where you’re trying to go.
So I think your analogies and menopause were perfect. Thank you. So now that we have kind of a sense of that overarching view of the journey and I agree with you completely about what data is and how we can make it useful, How does your organization, how does SAS use data you have?
We’re a relatively young organization and first ten years we were focuses on college students. So the help being relevant, being in the know of the things that make college students tick. You know, social media was huge for us. We connected through that. We used YouTube. And the younger generation I think are more about impressions then they’re not as data driven.
I think in our organization, as far as I understand it, we still use data, no doubt about it. But I think we’re not the hard core like if you compare us to was the Chemical Engineering Society. They’ve been around for another ten years. I’ve been to their national conference. It’s very technical. It’s a terrible society. Our Vive is more about me.
So we do things around the community, we do take surveys and things. We’re definitely in our second decade. We’re approaching more professionals and so we’re definitely taking a lot more surveys, data and testing our audience to understand what they need as we program and look for developing programs for their benefits. So in that data sense, we do a lot of our stories on our audience, and I keep track of some of the social media to see how effective we are.
So I think that’s where we are as an organization. We’re not a technical side, even though our members are technical by nature. But our focus is more about leadership development and about connecting some of our college students with talent. So it’s a talent acquisition and now we’re going into professional development leadership. And the unique challenge of space for Asians in STEM is about promotion and leadership development.
There’s a ton of Asians. Some of the technical companies, the I.T. companies or software companies have anywhere from 30 to 60% of their technical workforce. They are aged, but you look at the top level, I can call out Amazon. I guess I could make fun of them because my wife works for them. So somebody at Amazon, but you know, you look at their technical workforce, it runs around 50 to 60% of the technical world is Asian.
Asian, right. But you look Jeff Bezos or Andy Jassy, now the CEO of Amazon, wholly is within two level. I think there’s only one Asia within two levels of Andy, which is, you know, 5060 people or something I guess. Right. There’s only two there was two people. I think he moved on and retired and then there’s only one that I know.
So you move from 50 to 60% of a technical organization at the technical level and then to just less than 2%. That’s a pretty amazing. And the story there is that it’s a cultural issue. Part of it is a cultural issue. Part of it is, for example, personally for me is, you know, my father was speaking, he said, don’t look at me.
Not so when I first worked for my boss, Mr. Mueller, his German name, right? One day he pulled me aside and he goes, Kon, are you listening to me? I was like, What do you mean my listening to you, my ear is pointed at you. Yeah, what else would I need to show that I’m listening? You. You. No, you have to look me in the eye.
And I’ve never heard that. No one ever told me. You got to look me in the eye to tell. To indicate that you’re listening. That’s weird, because, you know, how does your eyes listen, technically, that this is salary aligned. So I started learning was like, Oh, this behavior is culturally, You know, when my father as an authority figure speaks, I’m not expected to look him in the eye.
I’m looking down and I’m not challenging any of his thoughts. Right. That’s not expected of me. Right. And we know that Western leadership, you’re supposed to be engaged. You’re supposed to be a typical American meeting. Mueller my boss told me this Tuesday, Con, I know you have ideas. You speak up like, Well, I’m just trying to be respectful.
I’m the junior engineer, you know, I’m one of my seniors to speak. You know, it’s typical meetings. You wait for everybody to speak. You’re never knows. And it’s an art. You have to learn how to interrupt at the right moment or else seems rude. And as a child, I never learn how to interrupt, learn how to interrupt. And I was like, fumbling.
Right? And so some of these stories, some of these things that we’re talking about risk and we’re talking about, you know, how we lead Asians in general are not taught these American skills or say, these Western skills, very British skills of how to challenge, how to show respect through challenge, how to inquiry that deeper inquiry that engage in dialog.
So all these skill sets, that’s what we try to help professionals do so that they can have a better sense of what Western leadership looks like.
It is funny how distinctly American those workplace cultural norms are, and it’s so easy not to recognize it when you know it’s the fish and water, right? You grow up in it. It doesn’t seem any different. My husband’s British and it’s funny because I swear he did not speak in my family for a year and a half because in order to get a word in edgewise, you have to interrupt somebody.
And he was just not going to be rude and interrupt somebody. You don’t do that. He would wait until someone gave him a chance to speak or there was a lull and it never happened. And he has had to learn how to just slip these things in, you know, quietly and make a space for himself to be heard.
And so I definitely relate very much to that, that it’s just a different way of being. And I know I mean, even just what’s considered rude, there is no one truth out there, right? There’s no objectively rude behavior. It is entirely cultural. And so, you know, your example of it’s rude to looks at somebody or it’s rude to not look at somebody like, okay, what am I supposed to know how to do if I didn’t grow up just enmeshed in those norms?
Yet in South Korea, they tell you the level of bowing, depending on how far you are from the person you’re bowing to. If you are a new entry level employee and you’re meeting the owner of the company, you bow at 45 degrees. You basically look at the floor. Yeah. All right. And so we don’t value you. That sits at that seat.
That would be weird, right? But these cultural things happen and we don’t know. Those are ingrained in us because we were taught at such a young age and we know that our heads are wired and teenagers. Yeah, it is hardwired in there. And so things that we learn when we’re young, it’s this tape recorder that I have to unwind sometimes even now.
I mean, I’m in my fifties and I still have to think, okay, see, I thought that show that you were listening, you know, I have to say that in the back of my mind, because if I have to default, I will not look at people because that’s what I was trained to not look at people. So I have to override my basic programing, Right.
To do that actively still to this day.
And I think this is such a complex and interesting challenge that you’re supporting so many of your members in facing those same challenges, like you said, that there are it’s not just a systemic issue within the organized Asian, though. There are those. And so those need to be addressed. But it’s also about preparing people to put their best foot forward and say, no, I can show that I am ready for this.
I’m going to make sure people hear my great ideas. But in order to do that, I need to do this in a different way. And I was thinking about that. There is a few data points, right, that are essential to your work to know the issues that you’re facing. Right. The fact that you can cite here is the proportion of, you know, Asian engineers and computer programmers at lower levels, and here’s the proportion in leadership.
And we can see these very stark contrasts that signal a problem. They’re telling us that data is there to tell us that there is an issue there. But I was curious whether and maybe how data might come into play as well in understanding are we making progress, Are the interventions that we’re trying when you’re dealing with sort of abuse air quotes that people can’t see around soft issues like cultural adaptation or behavior modification, those are hard things to measure and hard things to change.
And so I was curious if there’s also a place for data or evaluation around your interventions in tackling this like very clear issue in, in that promotion.
It is a very loaded question. Sorry, No, no, no. It’s great because we have to be about this deep right? If we want to solve the systemic issues, we have to have systemic solutions. Yeah. And these long matrilineal problems have built up over decades. You’re talking about from Vietnam, where 3000 years of culture impact on us. Flip it overnight in a couple of years or even in my lifetime.
Right? There are things that are buried in my head subconsciously that was carried down culturally from my parents. And so I think what we’ve done and we’ve only, you know, honestly, professional development is only about a three, four year journey for us. So we do a lot of service, as I mentioned earlier. So we survey audience, we talk to folks who have broke through the bamboo glass ceilings, especially for Asian women.
They’re the least promoted, by the way, of any ethnic and gender, any group, Asian women. So we asked the leaders who have made it what have got them there, How can we help and pool and educate in what we like to call give cultural agility to our folks so that they can learn? Because I can’t go back to my dad staring him in the eye and tell, This is your idea about that is whatever, Right?
That’s not going to happen. Right? Right. So from that cultural context, I have to be self aware that, yes, I may be able to do that now with my American colleagues, but it’s not changed at home.
Little bit, but not to the degree that, you know, that I have to be agile at work. And so for the immediate, what we’ve done is we’ve gathered data and ideas and then we test that ideas like, Hey, this is what we can execute. We give you options two, three, you pick which two, and then we go back and we, you know, the typical scientific method, engineering method, you have an idea and a hypothesis, test it and then you evaluate it.
And so we do our surveys. Did you enjoy it? Did it make a difference? Did you bring something back to your workplace? That’s not I think we’re on this cusp of how do we track people through their careers because we know people move careers all the time, right? And they change companies now more rapidly than ever before. It’s crazy, right?
I mean, you have an idea. They expect you to have at least three or four companies that use your recipe. If you stay at a company for 1050, you’re like, What’s wrong with you?
Which is so different than from 30 years ago?
Exactly. You know, lifetime employment isn’t a thing anymore. So try to track people and how they use the stuff that we help them is we’re trying to figure out that long to study. Right. To see we do make that impact. We make enough of an impact in this society. There are over 2 million Asian scientists and engineers out there in the United States.
Our training reaches maybe a few thousand at this point in time. So we’re not, you know, on any scale to do that by using the imagination. But we’re doing more localized and the people we touch, evaluating them, doing surveys. So some of our scores are really high. So the early indicators to say yes to your lung, to know questions yet to be determined, we hope that the near-term measures indicate that the long term trajectory and path and trend leads to moving the needle in a much bigger way.
And I think what you just described is the nature of a lot of work with these big gnarly problems. What are they, the B hags? I figure there’s a some acronym for like big, hairy, audacious goals, like when you’re trying to tackle something that isn’t going to change overnight for so many reasons. Like you said, 3000 years worth of culture.
And honestly, you’re then bashing against also such entrenched American corporate culture as well, right? It’s on both sides here. It’s not just on yours. And but the idea is that, all right, we’re in here for the long haul. This has to be a long, slow change. So we want to keep our eye on what we’re trying to change long term.
We want those proportions to be much more equal and the opportunity to be a lot more equal there long term. But short term, what we can measure that we’re going to see a difference in is like you’re saying, those smaller stats. Do we feel like people like when we talk to people after participating in professional development, are we getting reports back that this is something that improved their daily work life, that this is something that really resonated with them and gave them a new tool that they didn’t have before?
And like you said, that you’ll test ideas because it’s unclear what’s going to help necessarily. And so you’re also doing research, basic research of finding out what has worked for other people. Can we try that? Is that something we can replicate or not? And I think a lot of nonprofits are in that space where they’re not going to see a lot of movement quickly.
And the big measurement, but they’ve got their eye on it to know what the scale of the problem is and what they can focus on is how effective are we in the smaller steps short term leading up to that bigger change?
Yeah, these long term problems, you have to keep at it. I mean, I think as they say, as X approaches a limit of something, Right. I think when the United States integrates and truly accepts everyone for who they are, I think it be better. But that’s theoretical, right? How can we be a catalyst? We can wait for my kids kids and, you know, once their third or fourth generation, some of these changes will happen because they’ve integrated and they’ve changed the culture.
But I’m not going to be around four or five generations. So how can I, in space as an organization, be a catalyst to accelerate some of these changes? You know, somebody asked me one time, like, why don’t you make the companies change? It’s like, yeah, kind of make this great 100 year organization, try to change our culture. I don’t think so.
But I think there’s some truth that is that Americans company companies could use more Asian leaderships, more thoughtfulness, more methodical thinking about deep understanding of companies rather than, okay, what’s the fastest thing to earn our quarterly report? So we get our stock prices right. But I think we you know, there’s a happy medium somewhere in between. And so as long as we get enough Asians leadership positions, I think that will start changing culture.
The whole 8020 thing, you can get 20% in there to really lead. It will start shifting the culture of the 80% right? So I think there is some of that aspect That’s that’s what drives us. We know that we can contribute to company success, American success. We just have to work at it and really tap the potential, the potential leadership of our folks that’s untapped right now.
Absolutely. No. And I think that is a very pragmatic approach. Again, saying, you know, in a perfect world, sure, maybe we could have the system change completely and then people wouldn’t have to change at all. And there’s a lot of barriers to that happening. So while maybe that will be a longer term goal, we can look at how can we make changes locally that are going to have a much quicker impact there that are will be better for everyone, right?
Diversity makes companies stronger. We know that hybrid vigor, the more diverse an organism itself is, or an organization, the stronger and more resilient those organizations or organisms are. I’m curious, you mentioned a lot of survey data, but there’s also some other data that you’re bringing in. What have been some challenges or struggles that you’ve had in in getting useful data around such a complicated topic in terms of personal development and cultural agility, which I love that term.
I don’t know if you could speak a little bit to any challenges that you’ve had around like effectiveness of surveys or getting surveys that are actually help you take actions on either sunsetting a program or bringing a new professional development program on board.
I think in the beginning it was hard to get data, period in the sense of companies had the data, but they didn’t share what percentage of their leadership was Asian, which was the entry level. They saw that as proprietary, right? And so in the beginning we would ask some of these companies like, sorry, it’s proprietary. We can’t share that with you.
We’re like, we’re just trying to help you. You know, just hiding the data away doesn’t make the problem go away. And the other thing is, don’t you want to be a better company? Don’t you want to tap into your leadership potential of all these people you already hired? Right. And they’re like, oh, it’s tertiary on our list of things to do.
So we’re like, So we’re continuing to fight that. It’s like, yeah, it’s a problem, but it’s not a big problem. You know, we have other things. Granite There are other challenges with companies. I mean, getting more African-Americans, more Hispanics, more natives in STEM. Is it me 100%. I don’t think it’s exclusionary, right? It doesn’t have to be this or that.
I think, you know, if you really want to achieve to be a really great company, you really you’ve hired these people who are in your pocket already. They are. You’re, you know, and you want to develop leaders and you want them to be able to grow and prosper and bring new ideas. And so that’s that messaging has been hard because sometimes they don’t want to share that data.
And even if they share the data, they’re like, not our problem or our talent side. It’s really funny. I mean, our students are someone I would not, you know, as a student, I was not as judicious. And I say focus on girls as much, but I mean, I was a bad student, but I wasn’t a great student, right?
I got through college. I mean, you round up I was a 3.0, but our average student GPA is 3.5. I think 15 to 20% of our folks have a 4.0. They’re just incredibly smart. But they here’s the challenge. Asians are quote unquote, and I don’t like this term, but I’ll use it since people know what it means overrepresented in STEM relative to the general population.
And so hiring talented folks from companies come to our careers. They literally they don’t say in these words, but they basically said, can we have enough Asians in our company? So we don’t need much like, don’t you want talented folks? Period. Right. And I was like, okay, So some of these conversation has been difficult because of these proceed biases and perceived priorities.
And so the data is there, The acknowledgment of the necessity. And what we’re trying to do is help companies and help executives advocate for their employees, Asian executives or people who sponsor the like the Asian ERGs, which stands for employee resource groups to advocate for themselves. And that’s the other things Asians in general don’t advocate for themselves. We were not taught to raise our fists and go, Hey, we need this, right?
You’re like, Follow the rules, stay within the lines, you know, solve the problem, make sure it matches the answer in the back of the book. Right? Right. But we know that life’s problems. There is no book and there’s no answer to the back of the book that we have to match right now. To your point earlier, there are so many varieties of answers we just have to start working at it.
And we haven’t as a collective, we haven’t advocated for ourselves as much. And I think there is awakening within the Asian community of advocacy, but it’s still relative to the scope of other talk about the women’s right to vote, right? That’s been around for, I think almost 100 years now that work, right. The civil rights movement that’s been around since the sixties, you know, the fifties.
Right. And so I think just within this last decade or two, the advocacy for Asian Americans to find their voice in advocating for themselves is just starting to hit some stride. So we still have a long way to go.
Absolutely. I’m curious, you mentioned new access to the data was really difficult, one, because companies may have felt that they’d rather not admit a problem than share it and try to tackle potentially difficult problem. Do you have any advice, any solutions or approaches that seemed more effective in helping organizations kind of open up and be willing to look at data?
Because this is something that is challenging internally, as well as working with a potential partner where sometimes, you know, I was talking to it’s a from the Colorado Hospital Association about health equity and hiring equity. And she was saying you have to take that first step of being willing to look at the data and see just the nature of how it is.
And I was curious whether you had any advice for either organizations struggling to do this internally with themselves, where they’re scared to look or other organizations that you might be trying to partner with and help them look at that scary data. If you had any successes with that or approaches that were more successful.
I’m smiling. You can’t see this on the podcast because I’ve gone through many, many conversations with companies like this. Yeah, they actually have the data. They actually know because they’ve passed what they’ve told it on to it because they know once they release it, things have to happen, right? Priorities change. And I would say the people who are the gatekeepers of that data is it’s not as bad as you probably are imagining.
Yes, there’s going to be some work. There’s probably going to be some alignment, but it’s for the better right at the end of the day, you know that we align priorities, realignment, where it is, it’s going to be different. And so it’s take a deep breath. It’s not as bad as you may think it is. And I think that being honest and transparent, I think that’s the better long term solution because I think we’re going to get there.
I think the world is not going to get less transparent, you know, less corrupt. I think transparency is going at a blistering speed and people are going to ask for accountability. And would you want to be on the other side of history or on the direction that history is heading? Right. So that’s my question to them is I think a lot of this is done out of fear, concern for the work that they perceive that they are going to have to do.
But I think it’s a reprioritization and really solving these challenging issues of development. I mean, labor shortage right now being one one number one concern of a lot of companies, there’s not enough workers, good workers, right. Housing workers. While you have people in your organization who are there, you hired, you’ve done it. They’ve gone through the gates. They’re inside your organization.
Now, how do we help you tap into those and really cultivate those folks so that they can be true leaders? And there are cultural barriers. There are systemic barriers to why they’re not leading. And what we find out is that, you know, most companies don’t have the expertise and the scale that we can provide, because even at a large companies, they don’t want to put that energy into that because it hasn’t been a typical focus.
And what we can do is bring skills and economies and also a network and our expertise to help them solve that. So that’s my advice to those people who are the gatekeepers of the data and the decision makers is that I welcome that conversation. I’m more than happy. I’m not an in-your-face kind of guy. You know, somebody early in our career that why don’t we sue the pants, do what he has done right?
Just sue everybody, just sue everybody for discrimination as like that’s culturally not the way we do it. A little bit. Yeah. Do we really want to be on the other side of the legal age of everybody? And that’s just not culturally. We are right. We work with collaborators. Our way of leadership is about collaboration, is about working through the problem, working together.
So we have to stay true to who we are as a culture, as an identity to this. Yeah, we could hire go for the Asian Bar Association up with them and then start going after, you know, start me examples of people. But we’ve decided not to do it that way. We work with people who help themselves and try to in some cases.
There’s two really interesting things, lots of interesting things, but two things that stood out to me in what you were addressing. One, the idea that transparency is just growing generally and that for the most part, good things come out of that transparency. And it might be a rough beginning, but saying, you know, setting that vision of saying this is where we’re headed and the data that we’re going to look at is one step towards a future that hopefully we all agree we want stronger, more resilient companies.
We want organizations that perform at much higher levels because they’re able to better leverage all the talent that they have. But we’re not talking about making them do something that’s going to be harmful to their organization. We’re talking about methods of recognizing limitations within an organization and addressing those because we can see them in those numbers. And then the second step that I thought is really interesting is that you compared to JCP, like the idea that the data show fairly similar things right there, showing for both of these different groups that there is an access issue, that there is an equal opportunity in terms of promotion and access to executive positions.
But the data don’t tell you the approach, right? You get to decide that for yourself of how do we want to address this problem? And as the presentation that where we met, there’s more than just how fast do we solve this problem? There are values and preferences that go along with that. To say, well, even if approach a might get us there faster, what are the costs associated with that?
Not just dollar amounts, but cultural costs, personal costs, emotion and all costs that maybe aren’t the ones we want to pay or maybe just aren’t how we want to do things. We want to say this is our approach and that’s perfectly acceptable. And I think that is a wonderful way of explaining like, yes, we see that we have similar challenges we’re solving and we’re just going to do them the way that suits us the best and reflects our values and the things that matter to us.
And that’s a great summary. I wish I said it.
No, I just get to listen to what you say. So thank you. Well, I really, really appreciate your time here today. Thank you so much for talking with me. I’ve enjoyed learning about the cultural agility and the challenges that your organization, it seems, is really addressing, as well as looking at how data can play a role even in in very complex emotional cultural problems, that there’s still an avenue to support us, though it’s not at all what we follow.
It supports us in the activities that we’re up to. So if people would like to learn more about you, about CS, where could we send them?
Yeah, we’re pretty easy. We’re a non user organization, so anybody you Yeah, we’re not limited just to Asian or the STEM. Anybody can join us. You can sign up on SAIC, connect, talk on our website. You can follow me on LinkedIn. It’s pretty easy. There’s not too many countries. Other there are few countries, but not any other nonprofit sector.
Yeah, so so love to continue the conversation. And if you’re interested, anybody’s listening would be interested in us helping you solve some of these challenges. Or, you know, to talk more about this, I just want to say thank you for having me on. Thank you. It was a great conversation. And again, I look forward to having more with you.
Excellent. Thank you so much. And we’ll include links to space as well as to your LinkedIn on our show notes. So feel free to check that out if you want to follow up. Thank you so much.
That was my conversation with conn, the from the society for Asian Scientists and Engineers sais. We’ll have links in our show notes to his organization. Say connect dot org if you want to join or learn more about them as well as a link to Khan’s linked in profile. If you’d like to follow up with him and follow what he posts, I really enjoyed learning not just about the complexity of challenges like cultural agility, which I think resonates with many of us.
This idea that we’re expected to be different people in different contexts, and how do you help people learn to do that? Especially when the differences in who you’re supposed to be might be so much greater for some of us than others? I also really enjoyed the idea of understanding how to embrace being more transparent with our data. The fact that data can help us know where we are around a certain problem or in a certain situation like equity in hiring.
But when you see that data, there’s no going back. You can’t then pretend that everything is okay, or you may find that people judge you or different organizations judge your organization based on those numbers. And that can be scary, it can be challenging. And sometimes it also just might be hard because you have to admit that there is a lot of work for you to do.
And I talk a lot about the fact that data have to be coupled with a commitment to where you’re going, what you’re trying to achieve. One, because as we talked about with the Legos in this episode, you can’t decide what data is helpful unless you know where you’re trying to get to. But two, that shared commitment and shared vision in what you were trying to achieve will make the exploration of the data and the findings that come out of that data easier for everyone because you know why you’re doing it.
So even if it’s a bit rough, even if there are parts where there may be disagreement, there may just be some hard things you have to face up to and own up to. Like I talked about in that essay, that episode with essay, which is episode 27 on health equity. If you want to listen to that one, again, we talk about how you really do have to make that commitment to seeing where you are, to that transparency and taking that step, being willing to dig up the numbers you can talked about that we have them.
They’re there. We just have to be willing to look at them and to share them and to be honest in assessing those numbers, that that’s a big step. And the data aren’t going to tell you what to do about it. Once you find it, they’re going to tell you that there’s a problem. And like Conn and I discussed, it’s on you to then figure out what do you do about it.
Maybe there’s some experimentation, some good old scientific studies where you test something, you see if it works, using some information coming back about it and pivot if it doesn’t. But there’s also an element of saying, how do we want to address this? What’s true to our values and our approach? And we can use the data to tell us if our approaches are effective enough.
They may not be the most effective because maybe the most effective route requires a cost that we’re not willing to pay or requires us to be somebody we don’t want to be, be organizations that that are not what our organizations are meant to do or where our strengths are, where we’re trying to go. So again, the data aren’t telling you where to go.
They’re telling you where you are and they’re telling you the results of what happens from your interventions or your changes. So thank you so much for joining me today. I hope you enjoyed this episode. And again, if you want more information, feel free to check out the show notes. We would love to expand this conversation and make it as open and accessible to everyone as possible.
So one, if you did enjoy the show, I ask that you give it a rating, you leave a review. It really does help other people find the show. If you think it would be valuable for them to. If you have ideas about things you want to hear on the show or if you have somebody you think would be great for us to talk to, please share that.
You can go to the Contact US page at heart. So data dot com let us know because I want this to be a conversation and information that is helpful for you. So thank you so much again for joining us and I hope that you are having a wonderful New Year. You have been listening to Heart, Soul and Data.
This podcast was brought to you by Merakinos. Merakinos is an analytics education, consulting and data services company devoted to helping nonprofits and social enterprises amplify their impact and thrive through data. You can learn more at Merkanis.com.
Khanh Vu is the CEO of SASE, the Society of Asian Scientists & Engineers, the largest nonprofit of AAPI talent and leadership. Khanh came to America at the tender age of 5 as a war refuge. He has had decades of experience in the non-profit sector. He is also a son, brother, husband and father. Learn more about SASE at www.saseconnect.org and connect with Khanh at www.linkedin.com/in/vuqkhanh/
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