#85 Interview Episode: Changing the world with DeepTech Innovation w/ Sandeep Hardikar

Welcome back to another episode of the Process and Automation Podcast with the Automation Guys. The episodes with our interview guests are the most favorite ones, so I'm very excited to have another interview guest here on the show. So welcome, Sandeep Hardikar from Network Science. Very excited to have a conversation with you today about automation process and everything around that. So, and a bit of deep tech, I understand. And yeah, Sandeep, do you like to give a quick introduction to yourself?

Yes, of course. Thank you. First of all, Sascha and Arno for inviting me. It's a pleasure to be on this podcast. I've heard a few of those podcasts of yours and I'm quite inspired already. So I hope that this conversation today goes very well. A quick introduction. My name is Sandeep Hardiker, CEO and co-founder at Network Science, a company that focuses on innovation in the deep tech space. We aim to change the world in the way the world innovates and provides and is able to really make a massive impact in the way we drive our business, we create inclusive society, and of course, work towards challenges around climate change. We believe that innovation is a broken process at this stage. And in partnership with deep tech startups from around the world, we hope to change that. Thank you for inviting me again, Sascha and Arun.

Very exciting. So yeah, between myself, Arno, myself over the last 15 years or a bit more, we have worked with plenty of companies in that space when it comes to process automation and workflow, those kind of areas. Where do you see the competitive edge for Network Science in the market?

It's too early to answer that question, Sascha, frankly. We ourselves are quite young, but we do believe that we are creating a competitive edge, primarily in two areas. One, in the way innovation is undertaken by enterprises. As I mentioned, I think it's a broken process. And there is loads of work to be done to formalize it, put a structure to it. And especially when organizations have to deal and interact with startups, that's the process that we are changing. We're bringing in very structured process towards that. The second thing that we are bringing on the table, which is very different than others, is how do you look at commercial innovation? We also believe that while you're looking at innovation, especially in the deep tech space or in the digital space, one of the things that most organizations and, and, and service providers miss out is looking at innovating in the commercial aspect of it. Just one example towards that, we recently launched something called a zero-cost transformation, helping organizations undertake transformation but at a zero cost, which means you bring in an element of innovation, deep tech, you can adopt AI, but it is done in a purely gain-share model. And hence there is a large amount of risk and reward that we also bring on the table. So that's why that's getting a lot of, lot of uptake and acceptance in the market, because innovation in itself, I think it will not work. Innovation plus technology innovation plus commercial innovation is what our competitive advantage is, and we would like to build on that.

Yeah, especially with the, with the complexity of the, so of the the environment out there, I think it's very difficult, isn't it, otherwise to get started and to try out and can be very costly. And I can imagine zero-cost transformation is very appealing.

Yeah, it does, does sound very appealing. And I am just very curious, Sandy, in terms of sort of innovation with inside the kind of commercial space, you know, what are the sort of use cases out there that you guys can help customers with, you know, what is a typical sort of solution out there for problems that exist? I sort of understand where this is going in terms of the innovation side and structured innovation. I'm just wondering if somebody knocks on your door, what is the sort of thing that they ask for? What are the sort of things that you present to people that you feel adds value and benefit? And, you know, as you guys as a company progress, you know, where this sort of potentially will end up as?

Yeah, sure. Great question, Arno, because most organizations today, when we come across, there are two kinds of conversations that happen. One conversation is, we've been asked by our board to become an AI company. Can you help us with that? Now, it's very difficult, frankly, to help organizations when they're at that stage. They really don't know what they want to use. AI for looks like they just want to please a few people, that we become an AI company, so to speak. And that's not the space that Network Science operates into. We operate into space when organizations come to us saying 6 areas is what we focus on. One, we want to reduce our cost of operations. So anything to do with cost, right? It could be cost of operations, cost of acquiring a customer, cost of launching a new product. Or it could be growing. I want to launch a new product faster, better, cheaper in the market. Or the third area is risk. A massive amount of challenges organizations are facing either in the cyber risk area or health and safety area. The fourth area that we are innovating or helping clients innovate is around data. How do we create one view of our customer, one view of inventory, one view of everything that organizations are undertaking? More and more companies are also asking us in the sustainability space. So how do I become a net-zero company or how do I adopt ESG standards for organizations? And the sixth area is around customer experience/user experience, which is how do I create a mobile app, for example, which is far more intuitive, far more, you know, better than anyone else in the market. So when organizations come with specific business challenges or business aspects or vectors is where an organization like Network Science is able to make a big difference rather than, rather than, you know, working on use cases or trying to find a use case when organizations say, I want to become an AI company.

Yeah. And just in terms of sort of if you just look kind of recently at the sort of customers you guys are helping, you know, what are some of the sort of exciting outcomes that you're seeing that Network Science are providing these customers?

Well, I mean, thankfully, we are— because we are on the cutting edge of innovation, we always find ourselves, first of all, thrown challenges which are not being solved earlier or which can be solved only through new means or next generation technologies. So I'll give you a couple of examples around that. Very recently, we signed a large contract with Schneider Electric where the organization wanted, you know, because of COVID they were not able to do something called as factory acceptance tests. Now when equipments move from factory and they're accepted by the clients, they have to go through an audit process of whether the equipment is fit for purpose or not. And they were not able to do a simple test. And that is where we deployed an augmented reality-based a solution which uses natural language processing for anyone to be on site while the client is offshore somewhere sitting maybe in Mexico or in India or in Germany and remotely able to do a factory acceptance test where the client is speaking, say for example, in Hindi, which is an Indian language, while the person on site is understanding the same thing in German. And vice versa. So that was a very interesting innovation that we brought on the table and reduced— helped Schneider to, you know, one, not only reduce the cost of travel but also improve their acceptance at a big level. The second example is we're working with a large financial institution, a bank, which provides mortgage loans to multiple you know, consumers, and they've got a million consumers. And they were not able to, you know, they did not know at every month who will pay on time and who will not. And hence the ability for them to address or engage with these consumers were the same as anyone else. We brought in a system that uses machine learning to predict the behavior of every consumer. And hence, 10 days before the, before the start, before the due date every month, now they're getting a list of all the million customers, and we are able to, with high probability, say who will pay on time and who will not. And hence, the way they engage with people who will pay versus the way they will engage with people who will not pay has, of course, is very different. Allowing the customers to improve their engagement metrics, to improve their collection metrics, and also at the end of the day, use technology where it matters the most rather than just using technology for the sake of it. So these are two big examples where we have seen organizations using deep tech in the best possible way. We have seen, for example, H&M uses our technology on cybersecurity basis. We've seen wind power companies using it for using virtual reality. So there are many, many such use cases that constantly come our way, and we are happy to service those.

Yeah, pretty much every company can, going forward, will have to deal with those kind of topics, isn't it? There's no way around it.

Absolutely. And today, you know, thankfully everyone talks about generative AI, everyone talks about, you know, the Apple Vision Pro and things like that. The core will be, can you really implement that in your core business process? Yeah, if you can, then you have the competitive edge. Because our belief is it is not your, your, your competition is not going to be AI. Your competition is going to be the company that uses AI the best.

Absolutely. Yeah, 100%. That's, and this is what we talk about here on the podcast a lot, is actually, is actually a lot of use cases because it's key to actually get going. Because just listening and just playing around with ChatGPT and others doesn't really implement the change, isn't it? So, and then the minority of companies are not really getting there. They're just— same with RPA, we have seen in the past, isn't it, Arno? A lot, just a few trials here and there, but then it requires the real, the right partner to really get it going and make them make that impact. It's not as easy. As it seems.

Yeah. Yeah. And at the same time, I think it is incumbent on innovation providers like ourselves also to constantly speak about what's happening out there. How are other organizations using deep tech and really making a difference in the business processes? Because more and more people will listen to these you know, to these use cases, either through podcasts or other means, they will get the confidence that they are not the early adopters anymore, but there are many, many other organizations who already used it, and hence they should, if not, if not try now, uh, at least they should, they should start building a business case around it.

Yeah. So intelligent automation, hyperautomation, AI. So you mentioned cybersecurity, uh, and DTEK in, in, um, as, as a category. Looking a bit into the future, where do you see things developing in those areas? And yeah, where do you see network science fit in?

Tough question, Sascha. I mean, I hope I could have— I could see the future and possibly invest in it myself. But looking at what's happening and looking at the requests and the work that we are undertaking right now, there is an interplay between all the technologies that are becoming very critical. I think deep tech, if you break that down, hyperautomation plus blockchain will make a big difference in the way organizations use their, you know, change their business processes. The ability for an organization to build new capabilities will come in when you create an interplay between hyperautomation, blockchain, and machine learning, for example. The capabilities will be far different than what they are today. It will bring in great amount of transparency in, for example, in the supply chain. They will be able to control a lot of their costs. And the moment you add the sustainability angle, then it is going to blow this this thing up completely. So it's the— so where I see companies developing is not using one technology or two. I see companies using an interplay of multiple technologies to make things happen. Number one. Number two is the use cases which are going to be far more critical than the technologies by themselves. It will— of course, you've got to use technologies, you know, which will be, you know, you can't bring in bring in the capability because without the use of technology, but use cases adding and adding the commercial innovation together is going to make a big difference for, for organizations. Number 3 is the— there is thankfully now with, with the way things are changing, brands don't really matter anymore. Companies are no longer looking for organizations like the IBMs and the HPEs of the world to bring innovation. They are looking for the startup ecosystem to bring innovation on the table. And the more and more they will work with the startup ecosystem, the more innovation will happen on the ground in the operations. I think that's the big change that we see happening. And hence our play is around these areas, bringing the interplay between multiple technologies together. Make commercial innovation as important as the technology innovation, and bring in the startups to the fore, bring the startups in front of the clients, and to a certain extent, force the clients to think very differently over the next, you know, in their next transformation. I think that's where we see the future for the business operations.

Very exciting. Thank you.

Yeah, very fascinating there, Sandy. So it seems like it's a model based on lots of collaboration between tech startups. You know, it seems like you guys are actively seeking out innovative technology, deep tech, and really connecting that with customers that's got a desire to actually transform Perhaps that has got a need to innovate, and it looks like you guys are the catalyst for that, if that's my assessment of, you know, what Network Science does as a company. So, you know, Sascha did mention, you know, all these terms about intelligent automation, hyperautomation, you know, all the things that the analyst always throws out there. It's interesting that you mentioned the fact that, you know, it is a sort of a play between kind of what startup companies provide as technology versus what businesses need and the sort of intersection of that. So with that in mind, obviously there are a lot of technologies available on the market. Me and Sascha, not a week goes by that we discover there's a new technology, obviously with generative AI, that's a hot topic at the minute. So there's a lot of things out there, and I guess that the question from my side is, you know, what is the advice you want to provide to companies out there that really want to start with their innovation journey specifically inside their business? And you've mentioned a few sort of categories earlier. All of those are very interesting categories, but just generally speaking, you know, what is your advice for people to started on those?

Sure. So, you know, my one and only advice to any company that I talk to is that it is not a technology project any longer. It is not a CIO project, not a CTO project. It is a CEO project. It is a board mandate.

Yeah.

If it is not a board mandate, then you are not serious. If you want to talk about digital transformation, digital transformation as the two words have been used for the last 10 years. Today, the world has moved away from digital transformation because it has become quite mainstay, quite the standard. Every company needs to be a digital company. So the way you need to think as the CEO or the board is how do I adopt deep tech or AI in my core businesses? Because without that, I don't have any more competitive advantage. And that's the only— and if the CEO and the board needs help, then companies like Network Science exist for that. Happy to help you touch, feel, and experience deep tech. We're happy to do pilot projects for you. We're happy to bring in commercial innovations like ZCT, where you say, oh, I don't have the funds to implement. Okay, we say, okay, fair enough, we'll bring in a new way of helping you adopt deep tech. But you have no choice but to create reasons within your company to adopt deep tech if you want to stay relevant as you move forward. If time allows, I can give you a recent experience that I had when I met with— so we were called by a very large law firm, and when we went in, they said, you are deep tech guys, can you help us adopt AI? And I told them that, you know, if you're looking at only to adopt AI, then I can't do much. Tell me reasons why you want to adopt AI. And it was very interesting where the CEO told me that he had gone to a conference and he realized that his business is now under threat and under danger. And I was taken aback and I said, tell me more. He says, we charge close to about $40,000 to $50,000 for any large company to do the first draft of litigation. That's where we spend about 10, 15 people who study a lot and come up with the reasons and a first draft of litigation. However, I went to a conference and there was one person, a young chap, maybe 30s, had opened up ChatGPT. And he asked, he started asking me questions, I gave him a situation. And based on the prompts, in 35 minutes, this person came up with the first draft of litigation. The same thing that I used to charge $40,000, this person is able to do it at almost free of cost. Of course, it does not have the context of my company and the situation, which we can bring in, but there is no way I can charge $40,000 any longer, possibly $10,000. And that is what is driving behavioral change in the CEOs and the board. Now they believe that it is no longer a side project. It is now time for them to adopt if they want to continue having a sustained competitive advantage.

Yeah, I guess some companies are probably in a space where they said, well, you know, we've got Office 365 rolled out, we're on our way to digital transformation, or we've got a few RPA bots kicking around. We're well within our digital transformation journey. We're safe. But that example you've used there is absolutely just next level where it's— I can imagine that's quite a rude awakening to a chief exec of a law firm that look at that and think, wow, all of a sudden you become, uh, you feel redundant, right?

Yeah, of course. I mean, and, you know, slowly and steadily these people will also realize that, uh, they are, they are already lagging behind. You, you won't be able, able to retain your employee base, uh, if, if, you know, if you don't bring in such kind of technologies on the table. And, you know, so it's, it's a, it's, it's an It's a good time to be in, in the innovation space, but at the same time it is very tough as well because you've got to show results and not, not do innovation for the sake of doing innovation.

Yeah. And I guess like it's back to the point where, you know, we sometimes speak to prospective customers and they say, you know, we've got, we've got robots, we save. Thank you very much. We're like, that goes beyond robots these days, right? RPA or conventional automation is, you know, it simply doesn't cut it anymore. A lot of the new things we see is sort of in the intelligent automation space, intelligent automation-driven outcomes, autonomous automation. So there are a lot of these technology concepts that are not just in the analyst papers anymore. It is things that, like you said, startup tech companies, you know, these sort of, sort of deep tech companies are, you know, bringing to the forefront. And it's, it's there, it's available. So, you know, it's, it needs to be adopted to, if for you to stay relevant. And I think this is always our message as well on the show. Is that it's never too late to get started with automation, but it's certainly something that, you know, should be on your roadmap and it should be driven from the top level. You should have really, really good stakeholder engagement and not just on a divisional departmental level. It should come from the top because ultimately, you know, I think there's so much at stake for businesses that has got sort of a, I guess, sort of innovation as sort of just a part-time thing to keep, you know, that looks nice and keeps the board happy, you know, whereas, you know, it should be at the forefront of people's thoughts. And, you know, we always talk about automation-first culture, helping people to think about automation-first culture in their business. So, you know, and I think it is hard, you know, it is hard to— there are certain industries are not very receptive to change. We see that a lot as well. Law firms is one of the industries, and there's several of those types of industries. So it is refreshing hearing your story about sort of top-level CEO that it's like the penny is dropping, right? And people are realizing that, you know, we have to really look at our innovation, you know, a lot more seriously and make that a very, very top priority within startup business.

Yeah, and this is why, yeah, this is why we're doing this educational podcast here, trying to enable people around these topics. Very important because on the flip side of these new technologies, we hear also that people are frightened. AI is like really dangerous. Yeah, so definitely what we're doing here and hearing your thoughts on these topics is very valuable. And going through these use cases, as you mentioned, people need to hear about those use cases to make the next step. Yeah, very cool. Thank you. Yeah, before we finish the show, we always asking our guests a couple of questions which are not related to sort of the technical side or the business side. So just, um, really different questions. So shall we, should we get started?

Yeah, sure, looking forward to it.

Okay, so the first, the first question we have is, who is your idol and why?

Uh, many of them, many actually, but one, if I have to pick one, then it will be Vineet Nayar. Vineet Nayar used to be the CEO and chairman of a company called HCL Tech, and he revolutionized the entire employee culture within the organization and came up with a concept called employee first, customer second. A lot of us also have heard Richard Branson talking about the same concept. And there is a book that Vineet Nayar wrote about that. It's published in 16 languages by Harvard Business. And it really talks about how an organization, if it focuses on employees, and engages and empowers the employees, how it can really help customers change and innovate far better than otherwise. I follow him, I admire him. He's my idol, because I strongly believe that some of the concepts that he's mentioned are really very pertinent in our space, including something called trust through transparency, where he mentioned about how an organization can build trust with its employees by being absolutely transparent with everything that it's going through. We try to implement some of those concepts in network science. And I believe that if you are able to able to implement some of the concepts which are there in what Vineet Nayar has proposed, I think we would, we would become a very open culture, a very innovative culture, and an organization that has created a very different, very different context in this, in this world.

Yeah, very, very interesting. Yeah.

Yeah. Fascinating. Fascinating. So I've got one for you, Sandy. So imagine you can get all the contents and knowledge of a book instantly, which one would you choose? And by the way, you can choose more than one book as well. We've got some guests that said, why should we stay with one book? I've got the top 3 going on here.

Yeah, sure. Yeah. So there are 2 books that come to mind. One is, one is Blue Ocean Strategy. I think that's one book, which is phenomenal, you know, the way it— and, and I read that book, I think about 20 years back, when the first version came out. And it really blew my mind because we were completely, you know, it allows you to, it forces you to think about red oceans and blue oceans and how you should always be in the blue ocean, how you should force yourself to innovate, force yourself to take your ideas and create a market for itself using the Blue Ocean Strategy. And it also says that any company can start at any point in time to to move from a red ocean to a blue ocean. And that was really fascinating for me.

So that's the red ocean, that means there's too much competition, isn't it? And they are sort of biting each other. So that turns the ocean red, right?

Absolutely.

So the red ocean, the main competitive advantage in a red ocean is mainly pricing. So you basically race to the bottom. And it's a very small pie that you're fighting, everyone's fighting for the same pie. Whereas blue ocean, is how do you innovate, how do you bring in new ideas and increase the overall pie for everyone for that matter. And because you are the ones who are thinking differently and bringing in that blue ocean thinking, there is a high possibility that you'll gain far better than the others who may follow suit later, things like that. So that's one I found very, very fascinating. The other book that recently over the last 3 years that I have been I've possibly gone back to that book on a regular basis, is a book by the name Platform Revolution. And that is a book which talks about how marketplaces are being— are need to be looked at, how platforms need to be looked at, how you should create four-sided network effects. And that's what we're trying to do at Network Science also. We're trying to create the four-sided network effect where On one side there are startups, on the other side there are enterprises, and the interplay between the startups and enterprises and how do we create a value exchange platform between them, some of those concepts have been taken from the book Platform Revolution. So I will say those two are, I would instantly like to take all the knowledge and contents and possibly use that in my business.

I'm very happy to as well. If you, if you send me a link to those, I'm happy to put it into the show notes. I'm sure our listeners will now be very interested to dive into those books. Yeah, so the next question I have for you, yeah, what's the best advice you have ever received?

Get started as entrepreneurs, right? You know, this, Sascha and Arno, you guys are entrepreneurs yourself. You know, 99% of the best entrepreneurs in the world never became entrepreneurs because they were so, you know, they were so caught up into their corporate environment that the salary, the check that comes at the end of the month was so attractive that it was very difficult for them to come out and become entrepreneurs. I think the world needs more entrepreneurs. I think the world needs more people who can take that risk. Best advice I got was, you know, you have gotten it in you, you've got a great idea. You have to get things done. You can't rely on books, you can't rely on advisors, you've got to do it all by yourself. And only when you do it, you'll realize how powerful your thought process, your entrepreneurial spirit is. So I think, sorry for the long answer, but this, this was, you know, to get started, become that entrepreneur, don't worry about anything else, was the best advice I received. And thankfully, I took that and took the plunge.

Yeah, I think lots of, lots of ideas, so thousands of ideas are probably out there, still in the heads of lots of people, just because they didn't want to take that risk, which is a shame, of course. So much good ideas, knowledge, maybe breakthrough, innovation is sitting somewhere in a drawer, not even used. But maybe, yeah, maybe we all change the world. Startup gets nowadays, it is more popular than 10 years ago, 15 years ago, isn't it? So everyone wants to be, more and more people want to be an entrepreneur. Of course, no one likes the risk. But I think with the right mindset, training, and those kind of things, we will see more entrepreneurs.

Yeah, and I think it's just perseverance. And like you rightly said, it, it, it can sometimes be a hard place to be in, but you do achieve good things. I think you can, you know, have kind of creative thinking without that being sort of, I guess, dictated by individuals, for example. And like Sascha said, I think good ideas are formed when you're a free thinker. And I sometimes sort of think it can be hard, but you get to a point where you think, oh, I wish I can clone myself. And then, you know, okay, you've actually reached something. Yeah, you've created a lot of thoughts and thinking. And if there's more of you running around and doing things, then Perhaps the world will be a bigger or a better place, especially in terms of sort of the innovation. So that's very good advice. Thank you, Sandy. And I've got one more for you. I'm going to sort of turn this more towards the Olympics. We always ask people if they could be an Olympic athlete, what sport will they choose?

Yeah, sure. Thankfully, I'm not calling it out as Usain Bolt here, Sascha, so—

Won't be the first time.

I would go for field hockey. It's my first love. It's an Olympic sport. And coming from India, India used to be a hockey powerhouse till way back in the 1980s. We've got some 8 gold medals in Olympics in field hockey, and after that, we've lost it. So I hope I come back if given a choice, if God gives me that ability to become an Olympic athlete, you know, be that, be the, you know, pick up the stick, play the hockey, play the field hockey game, and win gold for India.

Wow, that's very exciting. Yeah. Thank you very much. Yeah, so that's hopefully, or these questions were hopefully not too strange.

But it's fantastic. I love the conversation and interactions. Thank you, Sascha and Arno.

Great. And yeah, for our listeners, we will put as well contact information into the show notes. So, and for that, what would be the best way to get in touch with you and Network Science?

Yeah, so my email ID, sandy@networkscience.ai, best place for me to connect and respond back on.

Fantastic. Yeah, thanks a lot. It was a pleasure to have you on the show. And yeah, thanks for sharing your thoughts on innovation and automation and making the world a better place with technology and deep And yeah, so we will be back with another episode very soon. And until then, let's automate it. Unfortunately, that's it again with this episode of the Process in Automation Podcast. If you like this episode, please give us a 5-star rating and don't forget to subscribe to this podcast so you don't miss any upcoming episode. We hope you will tune in next time, and until then, let's automate it!