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Are You Ready For A Machine With A.I. And E.I?

With Rana Gujral

Published on: Jun 21, 2019

Artificial Intelligence and Emotional Intelligence are two of the current buzzwords anywhere. Technology is unstoppable, and people keep on getting better in utilizing it to provide products and services that make entrepreneurs’ daily operations manageable. Rana Gujral, the CEO of Behavioral Signals, built an enterprise software company that delivers a robust and fast evolving emotion AI engine that introduces emotional intelligence into speech recognition technology. Rana walks us through his journey from being a software engineer to building this brilliant software. As he shares three different buckets of capabilities of their product, catch the three core tenets of entrepreneurship and some massive takeaways.

Are You Ready For A Machine With A.I. And E.I. Combined? with Rana Gujral

Before we introduce you our guest, I like to read a review. This one is from Zmanplan, “I listen to a lot of business podcasts. This is the first time I’ve gone niched with and dove into my cultural background, Asian. It’s a lot more than I expected. It goes into the realms of heart-based connection and into the realms of being divinely guided, culturally aware and open to your greatness. Good stuff.” Thank you, Zmanplan, for your nice review. I’m glad you feel that way. Please keep reading and sharing this podcast. We appreciate your support and review. I have a new tool that I want to share with you. Using your cell phone, text these four letters, AWOP, to the number 64600. You will receive a link to my virtual business card brought to you by EasyCard. With that link, you have access to all podcast episodes. You can search by the guest’s name, by the ethnicity or by the keyword from the episode title. Check it out, it’s really cool. Let’s get started.

We’re going to have an exciting discussion about artificial intelligence and emotional intelligence with our guest, Rana Gujral. Rana Gujral is an entrepreneur, speaker, investor and the CEO of Behavioral Signals. In 2004, Rana founded TiZE, cloud software for specialty chemicals and held the role of CEO until his exit in 2016. Rana held leadership positions at Logitech and Kronos Inc. Rana has been awarded the Entrepreneur of the Month by CIO Magazine and the US China Pioneer Award by IEIE. Please help me welcome, Rana Gujral.

Thank you, Kimchi. I appreciate you having me on the show and I’m looking forward to this conversation.

Thank you for being here. Briefly share with us what was your childhood like in India.

My childhood in India was a very traditional Asian household upbringing. It’s very goal-oriented. My family was affected by the India-Pakistan partition. As a result, we were one of the people who lost everything and came to the Indian side with nothing. Almost out of abject poverty, my grandfather raised three sons and all three became top doctors in the country. My father was a very renowned orthopedic surgeon. I grew up in a very proud family, proud of their accomplishments, lots of academic and professional success. I was groomed to be a doctor. I intended to be one. I was in love with the medical profession for a long part of my childhood, then something changed when I got my first computer.

When I got my first PC, I fell in love with computer science and I decided I don’t want to be a doctor. I wanted to be an engineer. Eventually, I became an entrepreneur sometime down my career. Initially, my early childhood was very much around being focused on achieving those milestones, focused on building those early capabilities around getting into competitive schools and building those life skills to achieve what others had achieved before me. It was nothing to do about entrepreneurship. Nobody in my family was an entrepreneur and there was no inspiration to be an entrepreneur. I was very much so around following a traditional trajectory of a typical career of an engineer or doctor and being successful in the profession.

From a doctor to an engineer and then moved to become an entrepreneur, who was your role model growing up?

Growing up, I had some strong influences from a few people. In terms of early childhood, it certainly would have been my dad because he was the person I wanted to be like as successful, be as competent, achieve those capabilities and those abilities. At a point when I decided to chart out a different territory and take on more of an engineering approach to things and eventually look at entrepreneurial activities, those inspirations have to come from other people. I’ve had a lot of help in terms of guidance, mentorship from a few people who have guided me through my career and through my early childhood. Some of the advice has stuck with me, which is something I still hold dear to with myself, my belief system, things that I valued and things that I’ve made decisions based on. It’s changed, but during my early childhood, I was inspired by the father.


What were the suggestions or guidance that you still remember?

Give your best to whatever you’re doing, never do something half-heartedly, strive for perfection and take pride in your work and lack of entitlement. Those were the basic grounding middle-class value systems that we grew up with. When I came down to the States that has stuck with me quite so much. I feel that some of those value systems are becoming more and more alien to the new generation. Those are the things which I’m quite valued as much. We live in an instant gratification world and people expect results almost instantaneously, so there’s less emphasis on perfection. There’s more emphasis on maximizing the output. It’s definitely transformative. I’m not going to judge and say one is better than the other. I’ve lived by some of those value systems and I try to stay true to that.

I noticed that there’s a different mindset in that too. I own my own company and I’m working with a business coach. That business coach says that 70% is good enough. If you need to get the product out, you test it out so that you have a chance to enhance and correct it later, but don’t wait until it’s perfect 100%. In that way, I agree because if I wait until I’m ready 100% and if the product is perfect, I will never start anything. It depends on the situation. 

It’s also a very different mindset. I certainly feel that mindset has evolved for me as well. Would I advise that mindset entirely to an entrepreneur? No, I won’t because at the end of the day, oftentimes as an entrepreneur, it is more crucial that you keep making progress whereas you achieve perfect results. It’s hard to be judgmental about those value systems. I grew up with that early on and that is appropriate for a specific career path. That’s also a difference between how an entrepreneur and how an employee thinks or what an employee is expected of and what an employee is taught to do. It’s around building perfection, getting competence around a specific skill and perfecting that. Whereas if you’re an entrepreneur, time is of the essence and you need to make progress.

Progress trumps perfection and getting something done absolutely perfect. You need to keep moving. You can try out different things and you need to test out different ideas. It’s guerrilla warfare. It’s a Wild Wild West. It’s a different approach if you’re working in the RDO or a research organization and you’re solving a particular problem, but that approach is the right approach for that situation. You can’t have that entrepreneurial approach in research because research requires manic focus. Research requires almost pedantic attention to a particular task at hand for years. You’re not necessarily looking at testing a variety of different hypothesis. You’re looking to solve one. It depends on what you’re looking to do and it depends on what problem you’re trying to solve and the different approaches. It’s a little too harsh to say one is better than the other or one approach works for everything aspect.

What was your career path look like?

After my undergrad, I started off as a software engineer. I loved that job, but I felt that I wanted to do more. In fact, I got an early opportunity to be a mini-entrepreneur in a larger company. This was in Kronos where I had this opportunity to go lead and bring back the time cog business, which was the legacy of Kronos. It was a very interesting project because not everybody believes in the success or viability of that initiative. It was something largely because most of the culture there was software driven and they want it to more invest on the software side of things, but we worked on it. I had this opportunity to build out the concept, build out the team very early on my career and see how those results come to fruition when you bring it to market. The project was a mega success. That was a product that we built using less than $10 million in investment, which was a lot of money if you think about it.

The first year revenues that we achieved of that product were over $40 million and then it kept on right after. In a few years during which I was with that company, that product bought in $1 billion in revenue and $10 million investment. It still is the world’s largest selling time clock. It’s every major TSA station and every major hospital or retail like Walmart, Kroger or Whole Foods use that time clock. It was a revolutionary system and it still is. It was very impactful for me to see that firsthand and learn from that experience. I spent a lot of time in corporate doing interesting things and building interesting products, some successes and some failures. We’re learning from most of those experiences. I had an amazing opportunity around 2012 when I was tasked to do a turnaround for an iconic technology company that had shrunk from its leadership position to a position of bankruptcy.

It was a situation where it had a lot of debt on the balance sheet. It has hundreds of millions and it was losing a lot of money every year. We looked at that situation, we looked at the product experience, the consumer sentiment, and we bet that innovation would bring it back to life. We focused on the turnaround, which was my first corporate turnaround. We turned it to profitability and market leadership position in about two-and-a-half years so that was a phenomenal journey. Right after that, I did a SaaS startup that focused on building a very specific platform for machine learning, especially chemicals and the unified machine learning to predict some of those trends of commodity pricing. I’ve never looked back from that. Entrepreneur early experiences are such a rush. You are always looking to make an impact and that impact is very gratifying and largely more satisfying than anything else that comes out of it. Here I am with yet another adventure at that.

Are you still investing in other people’s businesses or are you heading the company as well? You also have invested in this company financially as well.



AI And Emotional Intelligence: Entrepreneurial experiences are such a rush. You are always looking to make an impact and that impact is more gratifying and more satisfying than anything else that comes out of that.

I haven’t invested in the company that I’m leading, but I’m a fairly active investor and I’ve regularly been investing over the last few years. In fact, I’ve been working with a few major funds out of the Bay Area and also a few of the syndicates. I’ve also invested in a lot of companies as an Angel and I still do. Most of my focus has been around both CPA. It’s the sweet spot where the company’s right about to scale, I could bring in my experiences and my abilities around getting them towards that point of inflection. There are a few things that I know more than others in terms of specific technology areas and I tend to get biased towards those investments. The companies that I tend to understand myself and potentially I could run myself, those are the businesses that I can add more value to others. I do actively invest and I love that whole process and experience.

I was an Angel investor as well before so I know the drill. Only invest what you know, invest in the industry that you know. Don’t invest in something you have no idea how to run it. 

Investing is an interesting adventure. Most Angel investors don’t make any money out of their investments. That’s very true. That’s because Angel investment is inherently very risky. If you’re investing in a concept, you’re not just investing in a company. There isn’t a company at an Angel around the stage. It’s a bunch of people with some ideas and you’re betting on that. You’re investing in people and on their track record. Oftentimes, most Angels tend to invest in certain domains that they have a specific bias around. There’s this specific passion. That’s not business driven. It’s mostly passion driven and interest-driven, which doesn’t have the right business outcome at the end of the day but it’s fun. I tend to not operate in the Angel investment mindset. When I make my investments, I’m investing in the business and the entrepreneurs are important. I tend to not invest in a very early stage. Most of my investments are in full seed and pretty around so it’s not super early. It’s after most of the initial, the filtering has been done. I feel that my value is helping them scale not helping them prove out the concept.

Tell us about the Behavioral Signal software. Who is it for?

Behavioral Signals is a deep tech company. What we do is we use emotions from voice or speech and we apply that capability into a variety of different industry verticals. You can think of our product or our core offering as our platform, which is vertical agnostic. We have an emotion engine, which is delivered in the form of an API or an STK that we call the Oliver API engine. It is then consumed into a variety of different industry verticals. We sell it to contact centers, inside sales, customer experience and customer engagement type of verticals. In there, we go after traditional KPIs such as matching the right agent to the right customer, monitoring engagement, monitoring attrition, helping the agents do their job better when they’re speaking to a client. Helping them with cues such as you’re speaking too fast or speaking too slow and just general aspects of why sentences. It’s also helping them understand how the client is feeling at a certain point or if the client sounds angry or the client sounds engaged, sad or disengaged, etc.

Those are the two traditional KPIs that we go after. We also have very specialized prediction engines. For example, we have the ability to predict based on analyzing a voice conversation if the person who’s saying something will do what they’re saying. In a debt collection conversation, we can predict with up to an 82% accuracy if the debt holder is going to pay or not pay. In a way, we’re looking out into the future, the crystal ball and making that prediction, which then businesses use to make decisions. We also will sell into other domains and other verticals. One of our plans is using our technology to predict a propensity for suicidal behavior because they manage up a platform that caters to patient’s depression so that’s more applicable for them. We also apply the technology into robotics and virtual assistance. Any interaction between a human and nonhuman, we give the nonhuman the ability to understand the intent and the emotional state of mind from the human side. Those are the major capabilities that we offer to a variety of different verticals.

Your software has artificial intelligence in it and you also incorporate emotional intelligence in it to assess the other person. During the debt collection call, can your software predict the percentage of a likelihood that the debtor will pay or not pay based on their voice or based on the word that they use?

Let me give you two perspectives. If you think about our core capabilities as to what we offer, you could think of our capabilities in three different buckets. The first bucket is the core tenants of speech or conversation, which aspects such as diarization, which is a technical term that means who’s speaking when. If there are multiple people engaged in a conversation, we can parse that conversation and analyze when X is speaking and when Y is speaking, etc. An aspect such as speaking ratios and speaking rates, who are speaking faster, who’s speaking slower, who’s cutting someone else off, etc. The other bucket is the specific aspects around linguistics. That’s where the NLP and ESR come into play where the speech to text of converting the audio into words, which is what we call the what part, which is what is being said.


AI And Emotional Intelligence: You cannot replace humans. Humans have a tremendous amount of capabilities.

The third part is the emotion engine part, which is the how part. We know the what part, which is what is being said, but we also deduce how you were saying something. It’s not just what you’re saying, but how you’re saying it. The how part is the core capability and the core value add we offer into our emotion engine package, which then can be applied to a variety of different industrial use cases. In terms of how that is used, it’s a combination of linguistics in NLP, which is what words you’re choosing to use and a combination of intonation which is tonality. It’s about 20% words and 80% tonality. How you were saying something, the emphasis on the words, how you’re pronouncing something, how energetic you sound or how disengaged you sound and how you are emphasizing certain phrases are more important than the actual words that you use. That makes this capability somewhat language agnostic because you could apply those technologies to multiple languages. You might be using different words, but the way they are communicating their emotions are largely the same.

I understand what you are saying, which is very smart. I have a suspicion that it would not be the same as human interaction. Let’s say you are in front of somebody and you can assess that person. Let’s say that person is a foreigner, that person is 60 years old, and that person is not feeling well so they don’t want to talk that much. Those emotional intelligence from a being, that will beat the machine from just by evaluating the tonality, the word used, the speed of the language and things like that. The software did an amazing thing by incorporating those things. That’s cool.

Humans have amazing abilities and they’re taking into account a variety of different cues. They’re taking into account body language and they’re taking into account visual features and facial expressions, etc. We’re looking at one very specific aspect which is understanding voice and tone. If you are doing apples to apple comparison, it’s a comparison between somebody listening to somebody else on the phone and talking to somebody else on the phone versus the software analyzing the conversation simply by using audio. You have to take all those other elements out.

You’re not seeing the person in front of you. You’re simply analyzing intent based on the conversation and that’s how a business works. When you call into a call center, you’re on the phone then you’re talking to an agent. When you’re talking to a virtual assistant like Alexa or Google Home, that assistant cannot see you and you are just a voice for them. A lot of those things are more geared towards a business setting. The use cases that we go after are specific use cases around processing audio. That’s our expertise.

When are you saying that, I have a movie running in my head and say, “What about a nice robot saying, ‘How are you doing now? You don’t feel well? May I get your tea?’” You are confirming that it won’t be the same as a human being interaction with another human being. This is a machine and all you’ve got is the evaluation of audio. 

We do not intend to replace the human. This is a misconception around artificial intelligence. When people think of artificial intelligence, people think about a technology that is going to replace a human, but that’s very far from the truth. It’s very misleading to think that way. Artificial Intelligence is essentially a capability that allows humans to do what they do better. It’s helped them with the tasks that they’re focused on and now you have a tool that can help you around certain aspects of cognitive processing, around image resolution or around voice processing. Let’s take an example. You have a call center and you have a call center agent. Call center agents are very well trained. They have proper context around how to speak with someone and how to respond to anger, emotion, and sentiments around that. They’re able to deduce emotions from voice because they’re humans and all humans have that ability.

The reality is a typical call center agent takes hundreds of calls a day and thousands a week. After a few months on the job, they are tuning certain things out which are obvious to them. As soon as you point those things out, they’re able to catch it. If you have now on your 100th call a day and you have a client speaking to you in a disengaged or angry tone, maybe you’re not very sensitive to that because it’s your 100th call of the day. You’re exhausted and you’re ignoring some of those cues. The software in the back end, which is prompting you and reminding the agent of certain things like, “You’re speaking too fast or you’re speaking too slow. The client sounds angry.”

It’s helping jog the attention of the agent towards the things that they already know by themselves. It’s helping them do what they can do by themselves. It’s not necessarily intended to replace the agent and it’s not intended to do the job of the agent. That example of a comparison between what a human can do and what a machine can do, I don’t think it’s appropriate because that’s not the intent of what we do as a company. It’s not the intent of most companies which are focused on artificial intelligence and machine learning. They don’t intend to do that. It’s mostly glamorized by media. When people think about artificial intelligence, they’re thinking about a super smart robot that would act like your friend. That’s not true. That doesn’t exist. You cannot replace humans.


AI And Emotional Intelligence: Success leads to fulfillment. If you’re not fulfilled, you’re unhappy, and happiness is a perpetual goal that most of us are striving for.

Humans have a tremendous amount of capabilities. What you could do is you can build a system that sees and processes colors as good as a human can. You can build a capability that understands audio as good as a human can and translate that into words. In fact, it’s better than a computer software system focused on and does NLP, which is it takes audio into text. It’s technically more accurate than most humans are. Most humans do not have that ability to deduce speech into text as fast and as accurately as a machine does. Those are different things. Those are the specific capabilities. Human to human interaction is multidimensional, it’s multi-focused, and it’s a completely different ballgame.

I understand the intention of your software. Let’s say there’s an agent from the call center, but the software is running in the background that monitors and guides the agents saying, “You speak too fast. You seem like you are angry so slow down. Be empathetic.” Is that correct?

It is correct in the use case of a call center. We solve more complex problems as well like predicting intent, which is where you are looking to make a prediction on whether someone who’s saying something will execute on it and whether they will do what they’re saying. Those are the different things which become very specialized and very domain centric. You have to build and focus classifiers around those situations of those scenarios and go off for solving those problems. Let me give you an example. Most people understand or know about Alexa. There are a lot of virtual assistants out there like Google, Cortana and Bixby, but Alexa is what most people are aware of. There was a simple interaction between two humans, me, myself, and you Kimchi. I asked you a question and I say, “Kimchi, would you like to do this?” You respond to me in a very sarcastic voice and say, “Sure.” I hear the word sure. I know what sure means and I know sure means positive confirmation. It means, “Yes, let’s do it,” but I also sense the sarcasm in your voice.

My natural response to you as a human would be, “Maybe now is not a good time.” I know you don’t mean it. Imagine how that interaction looks with something like Alexa. If Alexa asks you a question, “Would you like to do this?” You respond back with a very sarcastic sure. Alexa listens to the word sure and responds back with, “Great, let’s do it.” That’s why we don’t treat virtual assistants with respect. We usually yell at virtual assistants. That’s very common. We don’t think of it as something like us. Even though it sounds like us, we know it’s not real because it doesn’t have the ability to understand emotional intent. Our technology can change that. Our technology can give Alexa an ability to understand how you’re saying sure. If you say sure in a sarcastic voice to Alexa, if Alexa is using our emotion engine, she knows you don’t mean sure. She knows that you’re sarcastic and she can respond back in an appropriate manner as a human were to you and that would be a game changer for that equation. If you had a virtual assistant that understands your state of mind, you would interact with that assistant very differently.

That’s wonderful that this software can do it and I hope it reached where it wants to be. I can see that it can do a lot of great things for different industries like for suicidal prevention or for terrorists and those things. Thank you for saying this because I was like, “Someday, the hairstylist, my doctor, the dentist, and the lawyer’s job will be replaced.” They’ll just come in and we’ll be drilled by the robot. It’s not that case. 

That’s not going to happen. Let me talk about something related to that. We can bet on two things. One is machines will become more and more intelligent. We can bet on that. The second thing we can bet on is we will be relying on machines more and more for a lot of day-to-day things we do. We’re doing that and that’s only going to increase. Those things are obvious and unstoppable. We, as a human race, are wanting to be more productive, we want to do different tasks than what we’ve been doing in the past, and we build tools for that. It’s no different than building a hammer to drive down nails because a hammer is a perfect tool to drive down nails, which is the purpose of the hammer. With those two things, with machines becoming more and more intelligent, with us relying more and more on the machines, it almost becomes imperative that a super-intelligent machine that we are dependent on or we are interacting with has emotional intelligence. Entities with emotional intelligence are ethically and morally sound and they make more responsible decisions.

Think about what is the classification of a very intelligent human that does not have the ability to process emotions. What do we call that human? We call him or her a psychopath. That’s a traditional clinical definition of a psychopath. It’s a very intelligent person that has no abilities to process emotions. We don’t want machine psychopaths. We want these intelligent machines to be responsible, make sound decisions and act in responsible ways. Some of these capabilities are often misunderstood, but like anything else, there’s a propensity for misuse which needs to be monitored and we need to watch out for that. There are amazing possibilities. It could completely change how we deal with suicide prevention or how we deal with employee engagement, how we deal with training and coaching. The list is endless.

My concern is that some human would say, “That can be solved by a machine. Why do I need to become better in my emotion? Why do I need to learn how to have higher emotional intelligence?”


AI And Emotional Intelligence: No matter what career path you choose, your success is dependent on your ability to deal with people, interact with other people, and work with other people.

We need not ask that question because we are not going to stop interacting with other humans. This is something which is an area of opportunity for a lot of humans as well. A lot of us do not have the core tenants of empathy. Empathy is the essence of building relationships and building great civilizations. Otherwise, we create a very selfish culture. Machines are not going to solve that for us. We have to solve it ourselves. If you want to make a more productive and more empathetic society, we need to be more sensitive to others. We need to react to others and relate to others and their state of mind. That’s what differentiates a human from other primates or other animals. Honestly, even animals have those capabilities and oftentimes, we get surprised as to how natural that instinct is in most animals. We’ve been blessed with other capabilities. Those are the things which we need to continue to build on. It’s not something which we could delegate to machines.

What we can delegate to a machine is to crunch numbers. We could delegate a machine to cut more grass faster or pull out more grass faster. We can’t rely on a machine to fulfill our basic human needs. I was reading an interesting report about how culture is changing in Japan. A vast majority of teenagers and young people in Japan have no relationships with anybody. They don’t have any social relationships. They don’t have any physical relationships. They live in a digital world. They interact with nonhuman entities and they think that’s normal. It’s shocking and it’s concerning. I was very worrisome that somehow some of these entities have filled the role of national tenants of humans and human interaction. That’s something which we need to be watchful for. There are capabilities that we could use to add value and there are capabilities we could use towards misuse. It’s up to us on what we want to do with it.

We need to be a responsible citizen. It’s our duty to do that. As a parent, you need to focus on that, not allow your children to misuse the technology and lose the human interaction. What is more important to you, is it success or fulfillment?

That’s a very easy answer for me because fulfillment is crucial and for most people, success leads to fulfillment. Success is a path to fulfillment. For others, they get to fulfillment without necessarily gravitating towards success. Their final destination is fulfillment because if you’re not fulfilled, you’re unhappy. Happiness is a perpetual goal that most of us are striving for. For a lot of people, unfortunately, they don’t achieve that. They achieve a tremendous amount of wealth and they achieve a tremendous amount of success, but then they’re not happy. They don’t feel fulfilled. Others get fulfilled in their idea of different ways without consistently gravitating towards wealth. For me, I’d say fulfilled but it’s a lifelong journey to feel fulfilled because fulfillment evolves. The definition of fulfillment changes as you grow, as you mature and as you avoid changes though it’s not a static view.

What is your mission and vision?

My mission is continuing to push boundaries, look to new ways and continue to learn. I get a lot of thrill from that. I’ve had that goal for the vast majority of my career and it’s still true. At Behavioral Signals, we are looking at solving a very complex problem and applying it to very interesting situations and impacting certain use cases that are tremendously valuable for a lot of people. That is very thrilling. Outside of the company, I have the same goals. It’s about learning, it’s about impact, and it’s about continuing to do new things and pushing the boundaries on whatever has been done in the past.

What are the three tips that you want Asian-American professionals and entrepreneurs to know?

Those are the three pieces of advice that I give to any entrepreneur, not necessarily an Asian-American entrepreneur. In fact, I did a talk about these three pieces of advice and most of this has been imparted to me from the mentors I’ve had over the course of my career. The first one is around safety and how we value risk, which is getting comfortable with risk and not necessarily being in the mode of playing it too safe. If you are perpetually trying to avoid risk, your outcomes will be very much inclined and dependent on the risk that you take. The sooner you become comfortable with risk and understand that risk is part of learning, it’s okay and failure is part of the journey, the better off you will be. That’s a big aspect of learning for any entrepreneur, which is getting comfortable with failure, being able to take risks and being okay with risks.

The second one is cognizant of how and where you can add value. One of the things that were imparted to me early on was the single biggest tenant of being successful is to add value. You can add value to any situation and get the right outcomes or get a successful outcome. The question is, how do you maximize those opportunities around creating value and adding value? Oftentimes, it is around picking out specific positions and speaking to seeking out specific situations where there’s a lot of chaos, there are a lot of problems, and it’s not a perfect situation for a work environment or from a productive environment. You could come in and you could make a huge impact by changing certain equations versus going towards a scenario where things are working out well and you’re working with smart people. That’s something which I believe is a certain recipe for success. Seek out engagements and situations where you can maximize the impact and maximize your personal value creation.

The third part is related to the first one. Once you’re comfortable with risk, you understand how to work with failure. That’s something which most people understand intrinsically, but don’t internalize which is a failure is your friend. Failure is part of the learning and part of the journey. Failure is something that you need to embrace. You need to almost crave for it because the sooner and the faster you fail, the better your skills become, the faster you learn and gets you closer to the eventual path you want to be at and the goal you’re striving for. Those are the core tenants of entrepreneurship, which is risk and ability to take risks. Second is adding value and impact and creating situations around impact. The third is embracing failure.

Once you start to internalize those three and you start to invite that into your intrinsic ability to operate, decision-making and thought process, you become a much better entrepreneur. Why is it that a lot of very successful entrepreneurs are college dropouts? Look at Asian immigrants in the United States, you would have two paths for an immigrant. If you are immigrating with a lot of education, you tend to go towards a traditional path of career. If you’re immigrating without education, there is no bridge. There is no ladder. You are in the ocean. It’s either you would swim or you would sink. There’s nothing else. You’re going to go and open a laundromat or you’re going to open a bakery, you’re going to open a restaurant. You’ll probably do ten different things that would appear it off several years and eventually you make it work. The outcomes are vastly bigger for an entrepreneurial community from the immigrant standpoint versus the ones who go for a traditional career just in the creation of wealth, creation of fulfillment or success.

I obviously took the former path towards education, career and all that. I do feel that sometimes, education becomes important because education lowers our ability to take risks. You’re smart and you know what can go wrong. You process that and you will hyper-analyze that. If you didn’t know how bad it could be, your restaurant will fail or your laundromat is a bad idea, as much better ways to make a living, then you would never go there. You would never create an empire and you won’t have the biggest chain of restaurants in the next many years. Those are the success stories which can come across, but those decisions are not made because people have those other options. People have those safer options, which is like, “I’m going to go and get a job.” Get a job, work through that process and propel that out. It never changes when you’re a middle-level manager or a senior VP or even a C-level executive in a company. It’s still a job. You’re working towards that versus going out for something unchartered and building that out and taking it to the next level. If you want to be an entrepreneur, you have to think about those things and you have to reflect on it. You have to understand how that might play a role in your decision-making, and in your psyche.

This episode is all about an entrepreneur. You’re not professional. You don’t propose getting a job and get promoted. You’ll propose and say, “Start your company and make a difference.”

Entrepreneurship is not for everybody. My advice is it’s not that you should go and quit your job and go start a business. My advice to the entrepreneurs who already had that in their belief system that if you want to be an entrepreneur, you have to change your mindset. You have to think differently. You have to cut out the chords and you have to cut the rope. There’s no rope, you’re not going to swim out. You’re either going to swim or die. You will swim and then you will make it work. That’s the only way you need to work.

It’s perfectly okay to choose a typical traditional path and build perfection around it. We would be nowhere as a society without researchers. We’d be nowhere in society without our scientists. We rely on those capabilities. We rely on our smart workforce. We rely on people who take a lot of pride in their work ethic. There’s no way that work or that lifestyle is not impactful or meaningful. It’s just something different. When you’re choosing and you ask my advice, I’ll push you towards what my inclinations are. That’s not always the right approach for you.

It depends on personality. If you are the type of a risk taker or go-getter and you can motivate yourself, then entrepreneur would be something that you might want to consider. If you don’t want to beat other people to work so hard to have no certainty about your future and you are good at doing what you’re doing, your technical ability, then stay in a career. Learn how to interact with other people. Improve your learning emotional intelligence so that you can get more support. You can lead others in that arena. 

In fact, what you just said is important because no matter what career path you choose, your success is very dependent on your ability to deal with people, interact with other people and work with other people. That is much harder than it sounds because you’ll think that’s natural for everyone. It’s not. Those are the skills which are not taught in schools. Those are the skills which aren’t even not taught in homes. Parents don’t teach their kids how to interact with other people and schools don’t teach you that capability either. You are generally focused on academics, sports, math and science and that’s the emphasis. You’re not taught about how to deal with adversity. You’re not taught about how to interact with someone who is controlling your destiny or your output. Those are the different things which are super crucial for success, which are not found anywhere.

Those things are the things that we have to learn outside of school. What is the best way for people to get in touch with you, Rana?

I’m fairly active on social media. You could send me a message through my page, which is RanaGujral.com. You can follow me on Twitter or connect with me on LinkedIn if that’s your game. Let me know how we could collaborate. Let me know what interesting ideas you have. If something is intriguing you in this conversation, I’d love to chat.

Thank you for being here, Rana and sharing your experience and insight to help the Asian American professionals and entrepreneurs to become more successful. What about you, our readers? What is your number one thing that you will apply as a result of this talk? In order to be heard, to be seen and to be understood, you need to live life loud. If you want to know more, contact me. Take care now.


Links Mentioned:


Episode Qoutes

"Progress trumps perfection."
"Empathy is the essence of building a relationship and building great civilization."
"Final destination is fulfillment, but fulfillment is always evolved."
"Failure is your friend; it's part of learning. You need to embrace it."
"Sometimes education becomes a burden."
"Your success depends on working with others."

About Rana Gujral

Rana Gujral is an entrepreneur, speaker, investor and the CEO of Behavioral Signals, an enterprise software company that delivers a robust and fast evolving emotion AI engine that introduces emotional intelligence into speech recognition technology. Rana has been awarded the ‘Entrepreneur of the Month’ by CIO Magazine and the ‘US-China Pioneer’ Award by IEIE, he has been listed among 8 A.I. Entrepreneurs to Watch in 2019 by INC Magazine and Top 10 Entrepreneurs to follow in 2017 by Huffington Post. He has been a featured speaker at the World Government Summit in Dubai, the Silicon Valley Smart Future Summit, and IEIE in New York. He is a contributing columnist for TechCrunch and Forbes.

In 2014, Rana founded TiZE, cloud software for specialty chemicals, and held the role of CEO until his exit in 2016. Prior to TiZE, He was recruited to be a part of the core turnaround team for Cricut Inc. At Cricut, Rana led the initiative to build a first of its kind, innovative product for the DIY community and prompted the turnaround of Cricut’s EBITDA position from bankruptcy to profitability within a span of 2 years. Previously, Rana held leadership positions at Logitech S.A. and Kronos Inc., where he was responsible for the development of best-in-class products generating billions in revenue and contributed towards several award-winning engineering innovations.

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