On this episode of Navigating Forward, Lisa Thee sits down with Shantha Mohan, who is an author, mentor, and Executive in Residence at Carnegie Mellon University. They chat about the challenges that people can face when making the jump from a technical individual contributor role to technical leadership. Shantha shares stories of her own career path from an individual role to eventually leading teams around the world — including some of the challenges she faced and how she overcame them. Hear some of the advice she gives her students, including what you should be doing every day and how to know when it's time to find something else to do.
Find Lisa at https://www.linkedin.com/in/lisathee/
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Welcome to Navigating Forward, brought to you by Launch Consulting, where we explore the ever-evolving world of technology, data, and the incredible potential for artificial intelligence. Our experts come together with the brightest minds in AI and technology, discovering the stories behind the latest advancements across industries. Our mission: to guide you through the rapidly changing landscape of tech, demystifying complex concepts and showcasing the opportunities that lie ahead. Join us as we uncover what your business needs to do now to prepare for what's coming next. This is Navigating Forward.
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Hello everyone, and welcome to the Navigating Forward podcast. We love to bring you the most innovative movers, shakers and luminaries today. Today we get the opportunity to bring you Shantha Mohan, who is an executive in residence at Carnegie Mellon University. Shantha is a distinguished author and an expert in leadership, software engineering, and of course, we can't have any conversations about software today without talking a little bit of AI. So welcome to the podcast today here Shantha.
00:01:14:17 - 00:01:18:27
Thank you so much for having me, Lisa. It's a pleasure to be here talking to you.
00:01:19:00 - 00:01:29:24
Oh, the pleasure's all mine. So, we got a chance to meet a few years back collaborating on a book called Demystifying Artificial Intelligence for the Enterprise. So, it's so nice to reconnect here.
00:01:29:28 - 00:01:32:03
Oh, yeah, absolutely. Absolutely.
00:01:32:05 - 00:01:42:08
So, for someone that doesn't know anything about your area of expertise, can you give us an overview of what you do and how you apply that as a mentor and guide at Carnegie Mellon?
00:01:42:10 - 00:02:55:12
I will be happy to do that. I would say today what I do is help individuals reach their potential by mentoring and coaching them. And I do this in many different ways. One of which has to do with the fact that I am associated with Carnegie Mellon University's Integrated Innovation Institute, where I am an Executive in Residence, and in that role I participate in delivering courses on innovation and entrepreneurship and also career strategies.
And I work with students to help them, you know, reach their full potential, whatever that might be. I would also say that I help technical people become a more rounded leader, and that is why I wrote my book. I wanted people to know that leadership, yes, you need the technical ability when you are leading technical teams, but a lot of what you would do in leading teams is really all about your emotional intelligence. And so those are some of the things that I do.
00:02:55:18 - 00:03:14:07
Those are very wise words. And so much of the employee engagement model is driven by the emotional intelligence of the leaders of the teams that we're all working as part of. Can you give us some thoughts on your concepts on leadership from your most recent book, Leadership Lessons with the Beatles?
00:03:14:10 - 00:05:13:05
That book is all about how you, as somebody who is technical, can learn all about leading people. Because when technical people are very good at their jobs, the tendency in management is to say, oh yeah, go ahead and lead this team. Here’s, you know, your team of people to lead. And we are not very well prepared if we haven't really gone to this thinking of how do I manage a team?
Now, you know, from going from an individual contributor to manager role, it's not easy. And we think that all of us are prepared for it. There are some people who are prepared for it because by nature they have learned over the years, depending on what experiences they have gone through, to be able to work very well with people.
But for the most part, technical people are so focused on problem solving, which was me when I started my career. And I learned through a lot of experience how to become a better people person. So, when I think about what I went through and wouldn't it have been great to have somebody tell me how to lead a team better, I think I would have been, you know, a thousand times better than I was.
So that's kind of what I do in my book, which is to tell people how to be a good leader with respect to leading a team, but also about certain attributes that are kind of very important for a good leader. For example, being optimistic in the face of hurdles and get over them. And how do you be a role model for your team? How do you stay in there? And, you know, in spite of all the troubles that come at you, how to be tenacious.
00:05:13:07 - 00:05:40:12
I couldn't agree more. I think as we all turn in to this giving back season of our careers, it's easy to look back and say, Boy, if I only had somebody who could have walked me through this, it could have been a little bit more graceful. And as a graduate of corporate America, I can definitely attest to your feedback that a lot of technical folks that are exceptional individual contributors get the opportunity to manage people.
But sometimes that can be, that can lead to toxic work environments and other challenging things. So, breaking through some of that and helping them to lead from a stronger position is incredibly important to the morale and the productivity of teams right. So, do you mind getting into it a little bit with me about what emerging trends you're seeing in the field these days that you think we should be paying more attention to?
00:06:07:09 - 00:07:11:10
I think that, you know, as you said in the beginning, no conversation is complete these days regarding work, you know, with AI, right. The artificial intelligence is pervasive, but especially now with gen AI, generative AI, we are finding many, many different ways to make life easier for yourself, make you productive and so on. And I think that it would be a shame if we don't take advantage of what gen AI has to offer, but at the same time we have to be highly aware that it comes with its own problems.
So having a balanced view, not totally buying into the hype, but not totally bringing it down and having a very balanced view of what all it can do, but also what harms it can bring can help you take advantage of what's going on today in the, you know, world of technology.
00:07:11:10 - 00:07:45:07
Yeah, I. think we all see the opportunity there, but there's a responsibility that we all have to make sure that we're guarding for things like bias, guarding for things like hallucinations, making sure that we have a human in the loop to ensure that the output is what, the level of expectation for making the business decisions that can be accelerated by tools like AI. I know your background originally was in the retail space. Can you talk about some ways you've seen AI innovate in retail that people can be thinking about?
00:07:45:08 - 00:09:27:08
Sure, sure. That was the chapter in the book that you mentioned before, Demystifying AI for the Enterprise. So, my chapter was on AI in the retail space. So, if you look at AI in retail space, it's been quite a while since AI has been, you know, being used in the retail space. So, take for example, all the recommendations you see on Amazon, our other e-commerce websites. You know, AI’s behind all of that.
And more recently of course with again the gen AI explosion using chatbots to help, you know, navigate what you need to buy and how you can maximize your experience as a customer. All of those are possibilities, but also because of all the advances in computer vision technology, we are finding that more and more retailers are using things like drones equipped with cameras going through either the retail warehouses or even the retail stores, in order to be able to see where out-of-stock is happening and how to quickly pare that.
All of that is happening and also, for example, in stores today, I think that shrink is a big, big concern. And again, you know, AI is helping identify where that shrink is happening and how to avoid it. And coupled with RFID, you know, a lot of retailers are trying to combat that problem.
00:09:27:10 - 00:10:01:20
Okay. So, I heard some of the first applications have been really in that e-commerce space with recommendation engines. We're starting to see the insertion, and I think we've seen it for a little while now, with gen AI of chatbots making it a more frictionless customer experience if people need more assistance beyond self-serve. Moving into the supply chain piece of things, using computer vision to be able to check when perhaps you have shelves that need to be restocked. And in terms of shrinkage, is that asset loss?
00:10:01:23 - 00:10:39:06
Yeah, shrinkage in retail means really losing your inventory for any number of reasons. And losing the inventory in the CPG space, consumer goods, is very different from groceries where that shrinkage happens because of waste. So, it's a different problem in different sections of retail. And one of them might be that people are walking out with your goods without paying for them. That's shrinkage, but at the same time not controlling in your inventory well and you know, things spoil.
00:10:39:14 - 00:10:46:08
Okay, so shrinkage can happen because of human action, or it can happen because of overstock on things that don't sell before they expire.
00:10:46:08 - 00:10:47:03
00:10:47:06 - 00:10:51:20
Can you talk a little bit about how people are applying AI to solve some of these challenges?
00:10:51:22 - 00:11:44:08
So, one of the things that people do is to identify patterns in their data. So, data is fundamental to everything. So, if you have the data collected, you can analyze it to see where the shrinkage is happening. Are you losing your goods because they are taken out by people? Or are your losses because things spoil, and your expiration date is here, and you haven’t restocked for those products? Or you ordered too much. So, all of this analysis, you know, machine learning can help you look at your data and give you the lay of the land, if you will. And then you have to start taking actions up against where your most payback is and then go after it. So that would be one of the things.
00:11:44:10 - 00:12:10:14
So, it can really, machine learning can really help with prioritization of making sure that you solve the right problems first in terms of the best impact of the business. But then also my guess is it allows us to reset some of those strategies more real-time versus waiting for perhaps every monthly analysis that we used to do maybe ten, 15 years back. Because you can work with the data so much more rapidly to find those insights.
00:12:10:14 - 00:12:12:03
00:12:12:05 - 00:12:27:07
So, I think just like computers, humans typically learn more from their failures than from their mistakes. Can you talk about a lesson you learned through your career that you took with you and how you navigated and grew from it?
00:12:27:09 - 00:14:43:17
I told you that I wish you know, I had all the lessons I was telling people about in my book early in my career. It used to be that I had a couple of problems with how I approached work. One of them has to do with the fact that I was super sensitive about criticism. I didn't realize that, that I was always defending myself when I was talking to people that brought up something. And I also was super critical of myself in terms of how I would do my work that I should have done it better, and that carried onto my team as well. You know that I was expecting a lot from myself and my team. So, these things were my blind spots. I really didn't think about them. However, when I was going through my career growth, at one point my boss told me, I think you would benefit from some leadership coaching.
And I said, Sure, I will do it. And so, I met with my leadership coach, and she told me that the best way to understand exactly who you are and what people think about you is to have a 360-degree feedback. And I said, okay, how do we do this? So, she said, we're going to ask a few of the people that you chose, some from your reports, some from your peers, some from your, you know, supervisors, our people above you, and yourself as well. So, we'll gather this feedback about you and then we will sit down and talk about how do we look at what's being said and how to make yourself better. I said, okay. So, we went through this 360-degree feedback and the things that I mentioned, which is, you know, I am super sensitive to criticism and that I am expecting a lot out of myself as well as my team came up as things that are really things that I need to work on.
00:14:43:19 - 00:14:48:26
How do you change how you feel about something? What a challenging discovery.
00:14:48:29 - 00:16:08:01
the thing is, you have to, I have always been somebody who wanted to do well, and I realized that if I don't do something about these things, they could be career limiting. So that that's a big enough incentive because I want to do well. And so, I said, okay, you know, this is how I am being viewed, this is how I'm being perceived, I've got to do something about it.
So, I worked with this leadership coach who coached me how to overcome these drawbacks, and that has been just phenomenal for me. It's really helped me grow in my role as a leader. I ultimately headed up the entire software engineering in my company. I had teams throughout the world, and it stayed with me.
You know, what I was not doing well. And I consider that as my failure was that and acknowledging that was my failure and being able to turn that around. And turning around, like you said, it's not easy. And that's why that coach was very, very critical for my career journey, because she helped me and this is what I tell people, you know, get help, be vulnerable.
00:16:08:03 - 00:16:40:15
Success is definitely a team sport. It's usually not an individual thing. So, it sounds to me like by hearing it from different perspectives, you were able to internalize it in a way that allowed you to grow from it. What advice do you give to the young people that you're mentoring today, knowing that they're walking into a rapidly evolving work landscape where the technology is changing quickly and there's a lot of change management that needs to happen throughout their careers. What advice are you giving your students today?
00:16:40:22 - 00:17:56:05
I tell you know, the youngsters to be always curious and always learning. Never stop learning. If in your job you feel you're not learning something new, you've got to find something else to do. To me, you know, being curious, thinking for yourself, everybody will tell you many different things. But ultimately it's you who has to decide what you want to do.
And so, to me, learning every day, and how do you learn? You learn by being curious. So that's what I tell the youngsters. And I also tell them about emotional intelligence. Be self-aware, and that's not something that you can get by not doing things consciously. So be very conscious of who you are, identify your strengths, your weaknesses, you know, those gaps that you have in your psyche to make yourself better. And also watch out what other people are telling you, you know, like the 360-degree thing helped me. You know, you can use all kinds of tools today, you know, online. Find out who you are and what people tell about you and then go fix yourself.
00:17:56:08 - 00:18:21:01
So just like AI, data is the key to being able to be clear on where you should prioritize your focus. So, for people that are maybe mid-career now, it's an interesting time in that data literacy is evolving as one of the key skills for succeeding and thriving in the workplace today. How do you use data to help with priorities for your decision makers that you're trying to influence?
00:18:21:06 - 00:20:36:11
Well, let me give you an example from what I'm doing today, which is teaching this course on career strategies to the incoming students at the Carnegie Mellon Institute. And what I wanted to do was to be able to reach out to each of the students in a way that is pertinent to them. And I say this because the students who come into the master’s course, Master of Science and Software Management, they come from different backgrounds. They have had a lot of experience, or they are just coming straight from their undergraduate classes. So, to be able to talk about career to all these students, you really have to know who they are, and you don't, you can’t do that without data. So, what I did was I launched a survey. I asked them about their background, and after I got their responses, I sat down, and I analyzed it. This is in a very small scale, right?
We are not talking about big data, but still data is data. And the data told me, you know, my class is made up of 20% of students have had at least four years of experience. So now I'm thinking, so how do I structure my classes such that they are meaningful to people who have already been in the workforce, versus another 17, 18% who have not had any experience at all. So, you know, in order to appeal to these different sections, how would I structure my lectures? How would I structure my workshops and activities? So that that's a very immediate thing that I had with the data. Of course, back in the days when I was running Retail Solutions, the company I co-founded, we lived and breathed data, retail data, right, big data. But this one here is very, very small data. But nevertheless, you know, without that data, I can’t do my job well.
00:20:36:17 - 00:20:47:23
So, Shantha, what is your why, what inspires you to bring your best self to everything that you approach as an entrepreneur and now as an executive in residence?
00:20:47:25 - 00:21:31:17
I would say my why actually has changed throughout in my life. When I was growing up in my career, it was a different why, that I just wanted to solve problems and be the best that I can be. Now the problem solving has always been there, but you know, that runs throughout my life. But today, having that in my career and I actually made that transition after sort of semi-retired, if you will, my goal today, my why today, is to see people succeed. So, it's really about how can I help people become the better version of themselves. That is my why today.
00:21:31:19 - 00:21:44:01
So, you've gone from putting the challenge on yourself to meet your potential, to focusing on helping others to meet their potential and build that legacy through the support of the next generation.
00:21:44:01 - 00:21:47:27
That's a fantastic way to frame that.
00:21:47:29 - 00:21:57:24
So, for people that are interested in learning more about some of your books and keeping tabs on what you're working on, where are the best places that they can keep tabs on you?
00:21:57:26 - 00:22:16:08
I am on LinkedIn, I'm on Twitter, Facebook. I'm quite active on social media, so you can always find me there. I also have a website, shanthamohan.com. You can find me there. And of course, my books are sold wherever books are sold.
00:22:16:08 - 00:22:39:18
Shanta, I do really believe in that you have to see it to be it. And I think you're a really inspiring woman in STEM, both from a leader perspective as well as a technical perspective. So, I really thank you for your time today and I encourage everyone to check out Shantha’s books, Leadership Lessons with the Beatles and Demystifying Artificial Intelligence for the Enterprise. Thank you so much for your time today.
00:22:39:18 - 00:22:47:04
Oh, thank you, Lisa. It was fun. You asked some wonderful questions. I really, really appreciated it. Thank you.